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JPEG

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{{Other uses}} In computing

Computing

Computing is usually defined as the activity of using and improving computer hardware and software. It is the computer-specific part of in

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I developed my own Jpeg decoding function and when I displayed the image, its quality went down. But when I displayed the image on the internet brows...

Encyclopedia

{{Other uses}} In computing

Computing

Computing is usually defined as the activity of using and improving computer hardware and software. It is the computer-specific part of information technology...

, JPEG (icon [pronounced as jay - peg] is a commonly used method of lossy compression for digital photography

Digital photography

Digital photography is a form of photography that uses an array of light sensitive sensors to capture the image focused by the lens, as opposed to an exposure on light sensitive film...

(image). The degree of compression can be adjusted, allowing a selectable tradeoff between storage size and image quality. JPEG typically achieves 10:1 compression with little perceptible loss in image quality. JPEG compression is used in a number of image file formats

Image file formats

Image file formats are standardized means of organizing and storing digital images. Image files are composed of either pixels, vector data, or a combination of the two. Whatever the format, the files are rasterized to pixels when displayed on most graphic displays...

. JPEG/Exif is the most common image format used by digital cameras and other photographic image capture devices; along with JPEG/JFIF, it is the most common format for storing and transmitting photographic images on the World Wide Web

World Wide Web

The World Wide Web is a system of interlinked hypertext documents accessed via the Internet...

.{{Citation needed|date=February 2010}} These format variations are often not distinguished, and are simply called JPEG. The term "JPEG" is an acronym for the Joint Photographic Experts Group

Joint Photographic Experts Group

The Joint Photographic Experts Group is the joint committee between ISO/IEC JTC1 and ITU-T that created the JPEG, JPEG 2000, and JPEG XR standards. It is one of two sub-groups of ISO/IEC Joint Technical Committee 1, Subcommittee 29, Working Group 1 - titled as Coding of still pictures...

which created the standard. The MIME media type

Internet media type

An Internet media type, originally called a MIME type after MIME and sometimes a Content-type after the name of a header in several protocols whose value is such a type, is a two-part identifier for file formats on the Internet.The identifiers were originally defined in RFC 2046 for use in email...

for JPEG is image/jpeg (defined in RFC 1341), except in Internet Explorer

Internet Explorer

Windows Internet Explorer is a series of graphical web browsers developed by Microsoft and included as part of the Microsoft Windows line of operating systems, starting in 1995. It was first released as part of the add-on package Plus! for Windows 95 that year...

, which provides a MIME type of image/pjpeg when uploading JPEG images. It supports a maximum image size of 65535×65535.

The JPEG standard

The name "JPEG" stands for Joint Photographic Experts Group

Joint Photographic Experts Group

, the name of the committee that created the JPEG standard and also other standards. It is one of two sub-groups of ISO

International Organization for Standardization

The International Organization for Standardization , widely known as ISO, is an international standard-setting body composed of representatives from various national standards organizations. Founded on February 23, 1947, the organization promulgates worldwide proprietary, industrial and commercial...

/IEC

International Electrotechnical Commission

The International Electrotechnical Commission is a non-profit, non-governmental international standards organization that prepares and publishes International Standards for all electrical, electronic and related technologies – collectively known as "electrotechnology"...

Joint Technical Committee 1, Subcommittee 29, Working Group 1 (ISO/IEC JTC 1/SC 29/WG 1) – titled as Coding of still pictures. The group was organized in 1986, issuing the first JPEG standard in 1992, which was approved in September 1992 as ITU-T
ITU-T
The ITU Telecommunication Standardization Sector is one of the three sectors of the International Telecommunication Union ; it coordinates standards for telecommunications....

Recommendation T.81 and in 1994 as ISO
International Organization for Standardization
The International Organization for Standardization , widely known as ISO, is an international standard-setting body composed of representatives from various national standards organizations. Founded on February 23, 1947, the organization promulgates worldwide proprietary, industrial and commercial...

/IEC
International Electrotechnical Commission
The International Electrotechnical Commission is a non-profit, non-governmental international standards organization that prepares and publishes International Standards for all electrical, electronic and related technologies – collectively known as "electrotechnology"...

10918-1. The JPEG standard specifies the codec

Codec

A codec is a device or computer program capable of encoding or decoding a digital data stream or signal. The word codec is a portmanteau of "compressor-decompressor" or, more commonly, "coder-decoder"...

, which defines how an image is compressed into a stream of byte

Byte

The byte is a unit of digital information in computing and telecommunications that most commonly consists of eight bits. Historically, a byte was the number of bits used to encode a single character of text in a computer and for this reason it is the basic addressable element in many computer...

s and decompressed back into an image, but not the file format used to contain that stream. The Exif and JFIF standards define the commonly used file formats for interchange of JPEG-compressed images. JPEG standards are formally named as Information technology—Digital compression and coding of continuous-tone still images. ISO/IEC 10918 consists of the following parts: NEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINE

JPEG standard – Parts
Part	ISO/IEC standard	ITU-T Rec.	First public release date	Latest amendment	Title	Description
Part 1	ISO/IEC 10918-1:1994	T.81 (09/92)	1992		Requirements and guidelines
Part 2	ISO/IEC 10918-2:1995	T.83 (11/94)	1994		Compliance testing	rules and checks for software conformance (to Part 1)
Part 3	ISO/IEC 10918-3:1997	T.84 (07/96)	1996	1999	Extensions	set of extensions to improve the Part 1, including the SPIFF file format
Part 4	ISO/IEC 10918-4:1999	T.86 (06/98)	1998		Registration of JPEG profiles, SPIFF profiles, SPIFF tags, SPIFF colour spaces, APPn markers, SPIFF compression types and Registration Authorities (REGAUT)	methods for registering some of the parameters used to extend JPEG
Part 5	ISO/IEC FDIS 10918-5		(under development since 2009)		JPEG File Interchange Format (JFIF)	A popular format which has been the de-facto file format for images encoded by the JPEG standard. In 2009, the JPEG Committee formally established an Ad Hoc Group to standardize JFIF as JPEG Part 5.

NEWLINENEWLINE Ecma International

Ecma International

Ecma International is an international, private non-profit standards organization for information and communication systems. It acquired its name in 1994, when the European Computer Manufacturers Association changed its name to reflect the organization's global reach and activities...

TR/98 specifies the JPEG File Interchange Format (JFIF); the first edition was published in June 2009.

Typical usage

The JPEG compression algorithm is at its best on photographs and paintings of realistic scenes with smooth variations of tone and color. For web usage, where the amount of data used for an image is important, JPEG is very popular. JPEG/Exif is also the most common format saved by digital cameras. On the other hand, JPEG may not be as well suited for line drawings and other textual or iconic graphics, where the sharp contrasts between adjacent pixels can cause noticeable artifacts. Such images may be better saved in a lossless graphics format such as TIFF, GIF, PNG, or a raw image format

RAW image format

A camera raw image file contains minimally processed data from the image sensor of either a digital camera, image scanner, or motion picture film scanner. Raw files are so named because they are not yet processed and therefore are not ready to be printed or edited with a bitmap graphics editor...

. The JPEG standard actually includes a lossless coding mode, but that mode is not supported in most products. As the typical use of JPEG is a lossy compression method, which somewhat reduces the image fidelity, it should not be used in scenarios where the exact reproduction of the data is required (such as some scientific and medical imaging applications and certain technical image processing

Image processing

In electrical engineering and computer science, image processing is any form of signal processing for which the input is an image, such as a photograph or video frame; the output of image processing may be either an image or, a set of characteristics or parameters related to the image...

work). JPEG is also not well suited to files that will undergo multiple edits, as some image quality will usually be lost each time the image is decompressed and recompressed, particularly if the image is cropped or shifted, or if encoding parameters are changed – see digital generation loss for details. To avoid this, an image that is being modified or may be modified in the future can be saved in a lossless format, with a copy exported as JPEG for distribution.

JPEG compression

The compression method is usually lossy, meaning that some original image information is lost and cannot be restored, possibly affecting image quality. There is an optional lossless mode defined in the JPEG standard; however, that mode is not widely supported in products. There is also an interlace

Interlace (bitmaps)

Interlacing is a method of encoding a bitmap image such that a person who has partially received it sees a degraded copy of the entire image. When communicating over a slow communications link, this is often preferable to seeing a perfectly clear copy of one part of the image, as it helps the...

d "Progressive JPEG" format, in which data is compressed in multiple passes of progressively higher detail. This is ideal for large images that will be displayed while downloading over a slow connection, allowing a reasonable preview after receiving only a portion of the data. However, progressive JPEGs are not as widely supported {{citation needed|date=October 2011}}, and even some software which does support them (such as some versions of Internet Explorer) only displays the image once it has been completely downloaded. There are also many medical imaging and traffic systems that create and process 12-bit JPEG images, normally grayscale images. The 12-bit JPEG format has been part of the JPEG specification for some time, but again, this format is not as widely supported.

Lossless editing

{{See also|jpegtran}} A number of alterations to a JPEG image can be performed losslessly (that is, without recompression and the associated quality loss) as long as the image size is a multiple of 1 MCU block (Minimum Coded Unit) (usually 16 pixels in both directions, for 4:2:0 chroma subsampling

Chroma subsampling

Chroma subsampling is the practice of encoding images by implementing less resolution for chroma information than for luma information, taking advantage of the human visual system's lower acuity for color differences than for luminance....

). Utilities that implement this include jpegtran, with user interface Jpegcrop, and the JPG_TRANSFORM plugin to IrfanView

IrfanView

IrfanView is a freeware/shareware image viewer for Microsoft Windows that can view, edit, and convert image files and play video/audio files. It is noted for its small size, speed, ease of use, and ability to handle a wide variety of graphic file formats, and has some image creation and painting...

. Blocks can be rotated in 90 degree increments, flipped in the horizontal, vertical and diagonal axes and moved about in the image. Not all blocks from the original image need to be used in the modified one. The top and left edge of a JPEG image must lie on a block boundary, but the bottom and right edge need not do so. This limits the possible lossless crop operations, and also prevents flips and rotations of an image whose bottom or right edge does not lie on a block boundary for all channels (because the edge would end up on top or left, where - as aforementioned - a block boundary is obligatory). When using lossless cropping, if the bottom or right side of the crop region is not on a block boundary then the rest of the data from the partially used blocks will still be present in the cropped file and can be recovered. It is also possible to transform between baseline and progressive formats without any loss of quality, since the only difference is the order in which the coefficients are placed in the file.

JPEG files

The file format

File format

A file format is a particular way that information is encoded for storage in a computer file.Since a disk drive, or indeed any computer storage, can store only bits, the computer must have some way of converting information to 0s and 1s and vice-versa. There are different kinds of formats for...

known as "JPEG Interchange Format" (JIF) is specified in Annex B of the standard. However, this "pure" file format is rarely used, primarily because of the difficulty of programming encoders and decoders that fully implement all aspects of the standard and because of certain shortcomings of the standard: NEWLINE

Color space definition
Component sub-sampling registration
Pixel aspect ratio definition.

NEWLINE Several additional standards have evolved to address these issues. The first of these, released in 1992, was JPEG File Interchange Format

JPEG File Interchange Format

The JPEG File Interchange Format is an image file format standard. It is a format for exchanging JPEG encoded files compliant with the JPEG Interchange Format standard. It solves some of JIFs limitations in regard to simple JPEG encoded file interchange...

(or JFIF), followed in recent years by Exchangeable image file format

Exchangeable image file format

Exchangeable image file format is a standard that specifies the formats for images, sound, and ancillary tags used by digital cameras , scanners and other systems handling image and sound files recorded by digital cameras...

(Exif) and ICC

International Color Consortium

The International Color Consortium was formed in 1993 by eight industry vendors in order to create a universal color management system that would function transparently across all operating systems and software packages....

color profiles

ICC profile

In color management, an ICC profile is a set of data that characterizes a color input or output device, or a color space, according to standards promulgated by the International Color Consortium...

. Both of these formats use the actual JIF byte layout, consisting of different markers, but in addition employ one of the JIF standard's extension points, namely the application markers: JFIF use APP0, while Exif use APP1. Within these segments of the file, that were left for future use in the JIF standard and aren't read by it, these standards add specific metadata. Thus, in some ways JFIF is a cutdown version of the JIF standard in that it specifies certain constraints (such as not allowing all the different encoding modes), while in other ways it is an extension of JIF due to the added metadata. The documentation for the original JFIF standard states: NEWLINE

NEWLINE

JPEG File Interchange Format is a minimal file format which enables JPEG bitstreams to be exchanged between a wide variety of platforms and applications. This minimal format does not include any of the advanced features found in the TIFF JPEG specification or any application specific file format. Nor should it, for the only purpose of this simplified format is to allow the exchange of JPEG compressed images.

NEWLINE Image files that employ JPEG compression are commonly called "JPEG files", and are stored in variants of the JIF image format. Most image capture devices (such as digital cameras) that output JPEG are actually creating files in the Exif format, the format that the camera industry has standardized on for metadata interchange. On the other hand, since the Exif standard does not allow color profiles, most image editing software stores JPEG in JFIF format, and also include the APP1 segment from the Exif file to include the metadata in an almost-compliant way; the JFIF standard is interpreted somewhat flexibly. Strictly speaking, the JFIF and Exif standards are incompatible because they each specify that their marker segment (APP0 or APP1, respectively) appears first. In practice, most JPEG files contain a JFIF marker segment that precedes the Exif header. This allows older readers to correctly handle the older format JFIF segment, while newer readers also decode the following Exif segment, being less strict about requiring it to appear first.

JPEG filename extensions

The most common filename extension

Filename extension

A filename extension is a suffix to the name of a computer file applied to indicate the encoding of its contents or usage....

s for files employing JPEG compression are .jpg and .jpeg, though .jpe, .jfif and .jif are also used. It is also possible for JPEG data to be embedded in other file types – TIFF

Tagged Image File Format

TIFF is a file format for storing images, popular among graphic artists, the publishing industry, and both amateur and professional photographers in general. As of 2009, it is under the control of Adobe Systems...

encoded files often embed a JPEG image as a thumbnail

Thumbnail

Thumbnails are reduced-size versions of pictures, used to help in recognizing and organizing them, serving the same role for images as a normal text index does for words...

of the main image; and MP3

MP3

MPEG-1 or MPEG-2 Audio Layer III, more commonly referred to as MP3, is a patented digital audio encoding format using a form of lossy data compression...

files can contain a JPEG of cover art

Cover art

Cover art is the illustration or photograph on the outside of a published product such as a book , magazine, comic book, video game , DVD, CD, videotape, or music album. The art has a primarily commercial function, i.e...

, in the ID3v2 tag.

Color profile

Many JPEG files embed an ICC color profile

ICC profile

In color management, an ICC profile is a set of data that characterizes a color input or output device, or a color space, according to standards promulgated by the International Color Consortium...

(color space

Color space

A color model is an abstract mathematical model describing the way colors can be represented as tuples of numbers, typically as three or four values or color components...

). Commonly used color profiles include sRGB

SRGB color space

sRGB is a standard RGB color space created cooperatively by HP and Microsoft in 1996 for use on monitors, printers, and the Internet.sRGB uses the ITU-R BT.709 primaries, the same as are used in studio monitors and HDTV, and a transfer function typical of CRTs...

and Adobe RGB

Adobe RGB color space

The Adobe RGB color space is an RGB color space developed by Adobe Systems in 1998. It was designed to encompass most of the colors achievable on CMYK color printers, but by using RGB primary colors on a device such as the computer display...

. Because these color spaces use a non-linear transformation, the dynamic range

Dynamic range

Dynamic range, abbreviated DR or DNR, is the ratio between the largest and smallest possible values of a changeable quantity, such as in sound and light. It is measured as a ratio, or as a base-10 or base-2 logarithmic value.-Dynamic range and human perception:The human senses of sight and...

of an 8-bit JPEG file is about 11 stops

F-number

In optics, the f-number of an optical system expresses the diameter of the entrance pupil in terms of the focal length of the lens; in simpler terms, the f-number is the focal length divided by the "effective" aperture diameter...

; see gamma curve. However, many applications are not able to deal with JPEG color profiles and simply ignore them.

Syntax and structure

A JPEG image consists of a sequence of segments, each beginning with a marker, each of which begins with a 0xFF byte followed by a byte indicating what kind of marker it is. Some markers consist of just those two bytes; others are followed by two bytes indicating the length of marker-specific payload data that follows. (The length includes the two bytes for the length, but not the two bytes for the marker.) Some markers are followed by entropy-coded data; the length of such a marker does not include the entropy-coded data. Note that consecutive 0xFF bytes are used as fill bytes for padding purposes (see JPEG specification section B.1.1.2 for details). Within the entropy-coded data, after any 0xFF byte, a 0x00 byte is inserted by the encoder before the next byte, so that there does not appear to be a marker where none is intended, preventing framing errors. Decoders must skip this 0x00 byte. This technique, called byte stuffing (see JPEG specification section F.1.2.3), is only applied to the entropy-coded data, not to marker payload data. NEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINE

Common JPEG markers
Short name	Bytes	Payload	Name	Comments
SOI	0xFF, 0xD8	none	Start Of Image
SOF0	0xFF, 0xC0	variable size	Start Of Frame (Baseline DCT Discrete cosine transform A discrete cosine transform expresses a sequence of finitely many data points in terms of a sum of cosine functions oscillating at different frequencies. DCTs are important to numerous applications in science and engineering, from lossy compression of audio and images A discrete cosine transform... )	Indicates that this is a baseline DCT-based JPEG, and specifies the width, height, number of components, and component subsampling (e.g., 4:2:0).
SOF2	0xFF, 0xC2	variable size	Start Of Frame (Progressive DCT)	Indicates that this is a progressive DCT-based JPEG, and specifies the width, height, number of components, and component subsampling (e.g., 4:2:0).
DHT	0xFF, 0xC4	variable size	Define Huffman Table(s)	Specifies one or more Huffman tables.
DQT	0xFF, 0xDB	variable size	Define Quantization Table(s)	Specifies one or more quantization tables.
DRI	0xFF, 0xDD	2 bytes	Define Restart Interval	Specifies the interval between RSTn markers, in macroblocks. This marker is followed by two bytes indicating the fixed size so it can be treated like any other variable size segment.
SOS	0xFF, 0xDA	variable size	Start Of Scan	Begins a top-to-bottom scan of the image. In baseline DCT JPEG images, there is generally a single scan. Progressive DCT JPEG images usually contain multiple scans. This marker specifies which slice of data it will contain, and is immediately followed by entropy-coded data.
RSTn	0xFF, 0xD0 … 0xD7	none	Restart	Inserted every r macroblocks, where r is the restart interval set by a DRI marker. Not used if there was no DRI marker. The low 3 bits of the marker code cycle in value from 0 to 7.
APPn	0xFF, 0xEn	variable size	Application-specific	For example, an Exif JPEG file uses an APP1 marker to store metadata, laid out in a structure based closely on TIFF.
COM	0xFF, 0xFE	variable size	Comment	Contains a text comment.
EOI	0xFF, 0xD9	none	End Of Image

NEWLINENEWLINE There are other Start Of Frame markers that introduce other kinds of JPEG encodings. Since several vendors might use the same APPn marker type, application-specific markers often begin with a standard or vendor name (e.g., "Exif" or "Adobe") or some other identifying string. At a restart marker, block-to-block predictor variables are reset, and the bitstream is synchronized to a byte boundary. Restart markers provide means for recovery after bitstream error, such as transmission over an unreliable network or file corruption. Since the runs of macroblocks between restart markers may be independently decoded, these runs may be decoded in parallel.

JPEG codec example

Although a JPEG file can be encoded in various ways, most commonly it is done with JFIF encoding. The encoding process consists of several steps:NEWLINE

The representation of the colors in the image is converted from RGB
RGB color model
The RGB color model is an additive color model in which red, green, and blue light is added together in various ways to reproduce a broad array of colors...

to {{YCbCr}}
YCbCr
YCbCr or Y′CbCr, sometimes written or , is a family of color spaces used as a part of the color image pipeline in video and digital photography systems. Y′ is the luma component and CB and CR are the blue-difference and red-difference chroma components...

, consisting of one luma
Luma (video)
In video, luma, sometimes called luminance, represents the brightness in an image . Luma is typically paired with chrominance. Luma represents the achromatic image without any color, while the chroma components represent the color information...

component (Y'), representing brightness, and two chroma
Chrominance
Chrominance is the signal used in video systems to convey the color information of the picture, separately from the accompanying luma signal . Chrominance is usually represented as two color-difference components: U = B' − Y' and V = R' − Y'...

components, (C_B and C_R), representing color. This step is sometimes skipped.
The resolution of the chroma data is reduced, usually by a factor of 2. This reflects the fact that the eye is less sensitive to fine color details than to fine brightness details.
The image is split into blocks of 8×8 pixels, and for each block, each of the Y, C_B, and C_R data undergoes a discrete cosine transform
Discrete cosine transform
A discrete cosine transform expresses a sequence of finitely many data points in terms of a sum of cosine functions oscillating at different frequencies. DCTs are important to numerous applications in science and engineering, from lossy compression of audio and images A discrete cosine transform...

(DCT). A DCT is similar to a Fourier transform
Fourier transform
In mathematics, Fourier analysis is a subject area which grew from the study of Fourier series. The subject began with the study of the way general functions may be represented by sums of simpler trigonometric functions...

in the sense that it produces a kind of spatial frequency spectrum.
The amplitudes of the frequency components are quantized
Quantization (image processing)
Quantization, involved in image processing, is a lossy compression technique achieved by compressing a range of values to a single quantum value. When the number of discrete symbols in a given stream is reduced, the stream becomes more compressible. For example, reducing the number of colors...

. Human vision is much more sensitive to small variations in color or brightness over large areas than to the strength of high-frequency brightness variations. Therefore, the magnitudes of the high-frequency components are stored with a lower accuracy than the low-frequency components. The quality setting of the encoder (for example 50 or 95 on a scale of 0–100 in the Independent JPEG Group's library) affects to what extent the resolution of each frequency component is reduced. If an excessively low quality setting is used, the high-frequency components are discarded altogether.
The resulting data for all 8×8 blocks is further compressed with a lossless algorithm, a variant of Huffman encoding.

NEWLINE The decoding process reverses these steps, except the quantization because it is irreversible. In the remainder of this section, the encoding and decoding processes are described in more detail.

Encoding

Many of the options in the JPEG standard are not commonly used, and as mentioned above, most image software uses the simpler JFIF format when creating a JPEG file, which among other things specifies the encoding method. Here is a brief description of one of the more common methods of encoding when applied to an input that has 24 bits per pixel (eight each of red, green, and blue

RGB color model

The RGB color model is an additive color model in which red, green, and blue light is added together in various ways to reproduce a broad array of colors...

). This particular option is a lossy data compression

Lossy data compression

In information technology, "lossy" compression is a data encoding method that compresses data by discarding some of it. The procedure aims to minimize the amount of data that need to be held, handled, and/or transmitted by a computer...

method. {{Citation needed|date=May 2011}}

Color space transformation

First, the image should be converted from RGB

RGB color model

The RGB color model is an additive color model in which red, green, and blue light is added together in various ways to reproduce a broad array of colors...

into a different color space

Color space

A color model is an abstract mathematical model describing the way colors can be represented as tuples of numbers, typically as three or four values or color components...

called {{YCbCr}}

YCbCr

YCbCr or Y′CbCr, sometimes written or , is a family of color spaces used as a part of the color image pipeline in video and digital photography systems. Y′ is the luma component and CB and CR are the blue-difference and red-difference chroma components...

(or, informally, YCbCr). It has three components Y', C_B and C_R: the Y' component represents the brightness of a pixel, and the C_B and C_R components represent the chrominance

Chrominance

Chrominance is the signal used in video systems to convey the color information of the picture, separately from the accompanying luma signal . Chrominance is usually represented as two color-difference components: U = B' − Y' and V = R' − Y'...

(split into blue and red components). This is basically the same color space as used by digital color television

Digital television

Digital television is the transmission of audio and video by digital signals, in contrast to the analog signals used by analog TV...

as well as digital video including video DVDs, and is similar to the way color is represented in analog PAL

PAL

PAL, short for Phase Alternating Line, is an analogue television colour encoding system used in broadcast television systems in many countries. Other common analogue television systems are NTSC and SECAM. This page primarily discusses the PAL colour encoding system...

video and MAC

Multiplexed Analogue Components

Multiplexed Analogue Components was a satellite television transmission standard, originally proposed for use on a Europe-wide terrestrial HDTV system, although it was never used terrestrially.- Technical overview :...

(but not by analog NTSC

NTSC

NTSC, named for the National Television System Committee, is the analog television system that is used in most of North America, most of South America , Burma, South Korea, Taiwan, Japan, the Philippines, and some Pacific island nations and territories .Most countries using the NTSC standard, as...

, which uses the YIQ

YIQ

YIQ is the color space used by the NTSC color TV system, employed mainly in North and Central America, and Japan. It is currently in use only for low-power television stations, as full-power analog transmission was ended by the U.S. Federal Communications Commission on 12 June 2009...

color space). The {{YCbCr}} color space conversion allows greater compression without a significant effect on perceptual image quality (or greater perceptual image quality for the same compression). The compression is more efficient because the brightness information, which is more important to the eventual perceptual quality of the image, is confined to a single channel. This more closely corresponds to the perception of color in the human visual system. The color transformation also improves compression by statistical decorrelation

Decorrelation

Decorrelation is a general term for any process that is used to reduce autocorrelation within a signal, or cross-correlation within a set of signals, while preserving other aspects of the signal. A frequently used method of decorrelation is the use of a matched linear filter to reduce the...

. A particular conversion to {{YCbCr}} is specified in the JFIF standard, and should be performed for the resulting JPEG file to have maximum compatibility. However, some JPEG implementations in "highest quality" mode do not apply this step and instead keep the color information in the RGB color model

RGB color model

The RGB color model is an additive color model in which red, green, and blue light is added together in various ways to reproduce a broad array of colors...

{{Citation needed|date=February 2008}}, where the image is stored in separate channels for red, green and blue brightness components. This results in less efficient compression, and would not likely be used when file size is especially important.

Downsampling

Due to the densities of color- and brightness-sensitive receptors in the human eye, humans can see considerably more fine detail in the brightness of an image (the Y' component) than in the hue and color saturation of an image (the Cb and Cr components). Using this knowledge, encoders can be designed to compress images more efficiently. The transformation into the {{YCbCr}} color model

YCbCr

enables the next usual step, which is to reduce the spatial resolution of the Cb and Cr components (called "downsampling

Downsampling

In signal processing, downsampling is the process of reducing the sampling rate of a signal. This is usually done to reduce the data rate or the size of the data....

" or "chroma subsampling

Chroma subsampling

"). The ratios at which the downsampling is ordinarily done for JPEG images are 4:4:4 (no downsampling), 4:2:2 (reduction by a factor of 2 in the horizontal direction), or (most commonly) 4:2:0 (reduction by a factor of 2 in both the horizontal and vertical directions). For the rest of the compression process, Y', Cb and Cr are processed separately and in a very similar manner.

Block splitting

After subsampling

Chroma subsampling

, each channel

Channel (digital image)

Color digital images are made of pixels, and pixels are made of combinations of primary colors. A channel in this context is the grayscale image of the same size as a color image, made of just one of these primary colors. For instance, an image from a standard digital camera will have a red, green...

must be split into 8×8 blocks. Depending on chroma subsampling, this yields (Minimum Coded Unit) MCU blocks of size 8×8 (4:4:4 – no subsampling), 16×8 (4:2:2), or most commonly 16×16 (4:2:0). In video compression MCUs are called macroblock

Macroblock

Macroblock is an image compression component and technique based on discrete cosine transform used on still images and video frames. Macroblocks are usually composed of two or more blocks of pixels. In the JPEG standard macroblocks are called MCU blocks....

s. If the data for a channel does not represent an integer number of blocks then the encoder must fill the remaining area of the incomplete blocks with some form of dummy data. Filling the edges with a fixed color (for example, black) can create ringing artifacts along the visible part of the border; repeating the edge pixels is a common technique that reduces (but does not necessarily completely eliminate) such artifacts, and more sophisticated border filling techniques can also be applied.

Discrete cosine transform

Next, each 8×8 block of each component (Y, Cb, Cr) is converted to a frequency-domain representation, using a normalized, two-dimensional type-II discrete cosine transform

Discrete cosine transform

A discrete cosine transform expresses a sequence of finitely many data points in terms of a sum of cosine functions oscillating at different frequencies. DCTs are important to numerous applications in science and engineering, from lossy compression of audio and images A discrete cosine transform...

(DCT). As an example, one such 8×8 8-bit subimage might be:

\left[
\begin{array}{rrrrrrrr}
 52 & 55 & 61 & 66 & 70 & 61 & 64 & 73 \\
 63 & 59 & 55 & 90 & 109 & 85 & 69 & 72 \\
 62 & 59 & 68 & 113 & 144 & 104 & 66 & 73 \\
 63 & 58 & 71 & 122 & 154 & 106 & 70 & 69 \\
 67 & 61 & 68 & 104 & 126 & 88 & 68 & 70 \\
 79 & 65 & 60 & 70 & 77 & 68 & 58 & 75 \\
 85 & 71 & 64 & 59 & 55 & 61 & 65 & 83 \\
 87 & 79 & 69 & 68 & 65 & 76 & 78 & 94
\end{array}
\right].

Before computing the DCT of the 8×8 block, its values are shifted from a positive range to one centered around zero. For an 8-bit image, each entry in the original block falls in the range

[0, 255]

. The mid-point of the range (in this case, the value 128) is subtracted from each entry to produce a data range that is centered around zero, so that the modified range is

[-128, 127]

. This step reduces the dynamic range requirements in the DCT processing stage that follows. (Aside from the difference in dynamic range within the DCT stage, this step is mathematically equivalent to subtracting 1024 from the DC coefficient

DC coefficient

When describing a periodic function in the frequency domain, the DC bias, DC component, DC offset, or DC coefficient is the mean value of the waveform...

after performing the transform – which may be a better way to perform the operation on some architectures since it involves performing only one subtraction rather than 64 of them.) This step results in the following values:

g=
\begin{array}{c}
x \\
\longrightarrow \\
\left[
\begin{array}{rrrrrrrr}
 -76 & -73 & -67 & -62 & -58 & -67 & -64 & -55 \\
 -65 & -69 & -73 & -38 & -19 & -43 & -59 & -56 \\
 -66 & -69 & -60 & -15 & 16 & -24 & -62 & -55 \\
 -65 & -70 & -57 & -6 & 26 & -22 & -58 & -59 \\
 -61 & -67 & -60 & -24 & -2 & -40 & -60 & -58 \\
 -49 & -63 & -68 & -58 & -51 & -60 & -70 & -53 \\
 -43 & -57 & -64 & -69 & -73 & -67 & -63 & -45 \\
 -41 & -49 & -59 & -60 & -63 & -52 & -50 & -34
\end{array}
\right]
\end{array}
\Bigg\downarrow y.

The next step is to take the two-dimensional DCT, which is given by:

\ G_{u,v} =
 \sum_{x=0}^7
 \sum_{y=0}^7
 \alpha(u)
 \alpha(v)
 g_{x,y}
 \cos \left[\frac{\pi}{8} \left(x+\frac{1}{2}\right) u \right]
 \cos \left[\frac{\pi}{8} \left(y+\frac{1}{2}\right) v \right]

whereNEWLINE

$\ u$ is the horizontal spatial frequency
Spatial frequency
In mathematics, physics, and engineering, spatial frequency is a characteristic of any structure that is periodic across position in space. The spatial frequency is a measure of how often sinusoidal components of the structure repeat per unit of distance. The SI unit of spatial frequency is...

, for the integers $\ 0 \leq u < 8$ .
$\ v$ is the vertical spatial frequency, for the integers $\ 0 \leq v < 8$ .

NEWLINE \alpha(u) = \begin{cases} \sqrt{ \frac{1}{8} }, & \mbox{if }u=0 \\ \sqrt{ \frac{2}{8} }, & \mbox{otherwise} \end{cases} is a normalizing scale factor to make the transformation orthonormalNEWLINE

$\ g_{x,y}$ is the pixel value at coordinates $\ (x,y)$
$\ G_{u,v}$ is the DCT coefficient at coordinates $\ (u,v).$

NEWLINE If we perform this transformation on our matrix above, we get the following (rounded to the nearest two digits beyond the decimal point):

G=
\begin{array}{c}
u \\
\longrightarrow \\
\left[
\begin{array}{rrrrrrrr}
 -415.38 & -30.19 & -61.20 &  27.24 &  56.13 & -20.10 & -2.39 &  0.46 \\
    4.47 & -21.86 & -60.76 &  10.25 &  13.15 &  -7.09 & -8.54 &  4.88 \\
  -46.83 &   7.37 &  77.13 & -24.56 & -28.91 &   9.93 &  5.42 & -5.65 \\
  -48.53 &  12.07 &  34.10 & -14.76 & -10.24 &   6.30 &  1.83 &  1.95 \\
   12.12 &  -6.55 & -13.20 &  -3.95 &  -1.88 &   1.75 & -2.79 &  3.14 \\
   -7.73 &   2.91 &   2.38 &  -5.94 &  -2.38 &   0.94 &  4.30 &  1.85 \\
   -1.03 &   0.18 &   0.42 &  -2.42 &  -0.88 &  -3.02 &  4.12 & -0.66 \\
   -0.17 &   0.14 &  -1.07 &  -4.19 &  -1.17 &  -0.10 &  0.50 &  1.68
\end{array}
\right]
\end{array}
\Bigg\downarrow v.

Note the top-left corner entry with the rather large magnitude. This is the DC coefficient. The remaining 63 coefficients are called the AC coefficients. The advantage of the DCT is its tendency to aggregate most of the signal in one corner of the result, as may be seen above. The quantization step to follow accentuates this effect while simultaneously reducing the overall size of the DCT coefficients, resulting in a signal that is easy to compress efficiently in the entropy stage. The DCT temporarily increases the bit-depth of the data, since the DCT coefficients of an 8-bit/component image take up to 11 or more bits (depending on fidelity of the DCT calculation) to store. This may force the codec to temporarily use 16-bit bins to hold these coefficients, doubling the size of the image representation at this point; they are typically reduced back to 8-bit values by the quantization step. The temporary increase in size at this stage is not a performance concern for most JPEG implementations, because typically only a very small part of the image is stored in full DCT form at any given time during the image encoding or decoding process.

Quantization

The human eye is good at seeing small differences in brightness

Brightness

Brightness is an attribute of visual perception in which a source appears to be radiating or reflecting light. In other words, brightness is the perception elicited by the luminance of a visual target...

over a relatively large area, but not so good at distinguishing the exact strength of a high frequency brightness variation. This allows one to greatly reduce the amount of information in the high frequency components. This is done by simply dividing each component in the frequency domain by a constant for that component, and then rounding to the nearest integer. This rounding operation is the only lossy operation in the whole process if the DCT computation is performed with sufficiently high precision. As a result of this, it is typically the case that many of the higher frequency components are rounded to zero, and many of the rest become small positive or negative numbers, which take many fewer bits to represent. A typical quantization matrix, as specified in the original JPEG Standard, is as follows:

Q=
\begin{bmatrix}
 16 & 11 & 10 & 16 & 24 & 40 & 51 & 61 \\
 12 & 12 & 14 & 19 & 26 & 58 & 60 & 55 \\
 14 & 13 & 16 & 24 & 40 & 57 & 69 & 56 \\
 14 & 17 & 22 & 29 & 51 & 87 & 80 & 62 \\
 18 & 22 & 37 & 56 & 68 & 109 & 103 & 77 \\
 24 & 35 & 55 & 64 & 81 & 104 & 113 & 92 \\
 49 & 64 & 78 & 87 & 103 & 121 & 120 & 101 \\
 72 & 92 & 95 & 98 & 112 & 100 & 103 & 99
\end{bmatrix}.

The quantized DCT coefficients are computed with

B_{j,k} = \mathrm{round} \left( \frac{G_{j,k}}{Q_{j,k}} \right) \mbox{ for } j=0,1,2,\ldots,7; k=0,1,2,\ldots,7

where

G

is the unquantized DCT coefficients;

Q

is the quantization matrix above; and

B

is the quantized DCT coefficients. Using this quantization matrix with the DCT coefficient matrix from above results in:

B=
\left[
\begin{array}{rrrrrrrr}
 -26 & -3 & -6 & 2 & 2 & -1 & 0 & 0 \\
 0 & -2 & -4 & 1 & 1 & 0 & 0 & 0 \\
 -3 & 1 & 5 & -1 & -1 & 0 & 0 & 0 \\
 -3 & 1 & 2 & -1 & 0 & 0 & 0 & 0 \\
 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0
\end{array}
\right].

For example, using −415 (the DC coefficient) and rounding to the nearest integer

\mathrm{round}
\left(
 \frac{-415.38}{16}
\right)

Entropy coding

Entropy coding is a special form of lossless data compression

Lossless data compression

Lossless data compression is a class of data compression algorithms that allows the exact original data to be reconstructed from the compressed data. The term lossless is in contrast to lossy data compression, which only allows an approximation of the original data to be reconstructed, in exchange...

. It involves arranging the image components in a "zigzag

Zigzag

A zigzag is a pattern made up of small corners at variable angles, though constant within the zigzag, tracing a path between two parallel lines; it can be described as both jagged and fairly regular....

" order employing run-length encoding

Run-length encoding

Run-length encoding is a very simple form of data compression in which runs of data are stored as a single data value and count, rather than as the original run...

(RLE) algorithm that groups similar frequencies together, inserting length coding zeros, and then using Huffman coding

Huffman coding

In computer science and information theory, Huffman coding is an entropy encoding algorithm used for lossless data compression. The term refers to the use of a variable-length code table for encoding a source symbol where the variable-length code table has been derived in a particular way based on...

on what is left. The JPEG standard also allows, but does not require, decoders to support the use of arithmetic coding

Arithmetic coding

Arithmetic coding is a form of variable-length entropy encoding used in lossless data compression. Normally, a string of characters such as the words "hello there" is represented using a fixed number of bits per character, as in the ASCII code...

, which is mathematically superior to Huffman coding. However, this feature has rarely been used as it was historically covered by patent

Patent

A patent is a form of intellectual property. It consists of a set of exclusive rights granted by a sovereign state to an inventor or their assignee for a limited period of time in exchange for the public disclosure of an invention....

s requiring royalty-bearing licenses, and because it is slower to encode and decode compared to Huffman coding. Arithmetic coding typically makes files about 5–7% smaller. The previous quantized DC coefficient is used to predict the current quantized DC coefficient. The difference between the two is encoded rather than the actual value. The encoding of the 63 quantized AC coefficients does not use such prediction differencing. The zigzag sequence for the above quantized coefficients are shown below. (The format shown is just for ease of understanding/viewing.) NEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINE

−26
−3	0
−3	−2	−6
2	−4	1	−3
1	1	5	1	2
−1	1	−1	2	0	0
0	0	0	−1	−1	0	0
0	0	0	0	0	0	0	0
0	0	0	0	0	0	0
0	0	0	0	0	0
0	0	0	0	0
0	0	0	0
0	0	0
0	0
0

NEWLINENEWLINE If the i-th block is represented by Bi and positions within each block are represented by (p,q) where p = 0, 1, ..., 7 and q = 0, 1, ..., 7, then any coefficient in the DCT image can be represented as Bi(p,q). Thus, in the above scheme, the order of encoding pixels (for the i-th block) is Bi(0,0), Bi(0,1), Bi(1,0), Bi(2,0), Bi(1,1), Bi(0,2), Bi(0,3), Bi(1,2) and so on.

This encoding mode is called baseline sequential encoding. Baseline JPEG also supports progressive encoding. While sequential encoding encodes coefficients of a single block at a time (in a zigzag manner), progressive encoding encodes similar-positioned coefficients of all blocks in one go, followed by the next positioned coefficients of all blocks, and so on. So, if the image is divided into N 8×8 blocks {B0,B1,B2, ..., Bn-1}, then progressive encoding encodes Bi(0,0) for all blocks, i.e., for all i = 0, 1, 2, ..., N-1. This is followed by encoding Bi(0,1) coefficient of all blocks, followed by Bi(1,0)-th coefficient of all blocks, then Bi(2,0)-th coefficient of all blocks, and so on. It should be noted here that once all similar-positioned coefficients have been encoded, the next position to be encoded is the one occurring next in the zigzag traversal as indicated in the figure above. It has been found that Baseline Progressive JPEG encoding usually gives better compression as compared to Baseline Sequential JPEG due to the ability to use different Huffman tables (see below) tailored for different frequencies on each "scan" or "pass" (which includes similar-positioned coefficients), though the difference is not too large. In the rest of the article, it is assumed that the coefficient pattern generated is due to sequential mode. In order to encode the above generated coefficient pattern, JPEG uses Huffman encoding. JPEG has a special Huffman code word for ending the sequence prematurely when the remaining coefficients are zero. Using this special code word: "EOB", the sequence becomes: NEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINE

−26
−3	0
−3	−2	−6
2	−4	1	−3
1	1	5	1	2
−1	1	−1	2	0	0
0	0	0	−1	−1	EOB

NEWLINENEWLINE JPEG's other code words represent combinations of (a) the number of significant bits of a coefficient, including sign, and (b) the number of consecutive zero coefficients that precede it. (Once you know how many bits to expect, it takes 1 bit to represent the choices {-1, +1}, 2 bits to represent the choices {-3, −2, +2, +3}, and so forth.) In our example block, most of the quantized coefficients are small numbers that are not preceded immediately by a zero coefficient. These more-frequent cases will be represented by shorter code words. The JPEG standard provides general-purpose Huffman tables; encoders may also choose to generate Huffman tables optimized for the actual frequency distributions in images being encoded.

Compression ratio and artifacts

The resulting compression ratio can be varied according to need by being more or less aggressive in the divisors used in the quantization phase. Ten to one compression usually results in an image that cannot be distinguished by eye from the original. 100 to one compression is usually possible, but will look distinctly artifacted

Compression artifact

A compression artifact is a noticeable distortion of media caused by the application of lossy data compression....

compared to the original. The appropriate level of compression depends on the use to which the image will be put. {{external media |image1=Illustration of edge busyness. }} Those who use the World Wide Web

World Wide Web

The World Wide Web is a system of interlinked hypertext documents accessed via the Internet...

may be familiar with the irregularities known as compression artifact

Compression artifact

A compression artifact is a noticeable distortion of media caused by the application of lossy data compression....

s that appear in JPEG images, which may take the form of noise around contrasting edges (especially curves and corners), or blocky images, commonly known as 'jaggies'. These are due to the quantization step of the JPEG algorithm. They are especially noticeable around sharp corners between contrasting colors (text is a good example as it contains many such corners). The analogous artifacts in MPEG video are referred to as mosquito noise, as the resulting "edge busyness" and spurious dots, which change over time, resemble mosquitoes swarming around the object. These artifacts can be reduced by choosing a lower level of compression

Image compression

The objective of image compression is to reduce irrelevance and redundancy of the image data in order to be able to store or transmit data in an efficient form.- Lossy and lossless compression :...

; they may be eliminated by saving an image using a lossless

Lossless data compression

file format, though for photographic images this will usually result in a larger file size. The images created with ray-tracing programs have noticeable blocky shapes on the terrain. Certain low-intensity compression artifacts might be acceptable when simply viewing the images, but can be emphasized if the image is subsequently processed, usually resulting in unacceptable quality. Consider the example below, demonstrating the effect of lossy compression on an edge detection

Edge detection

Edge detection is a fundamental tool in image processing and computer vision, particularly in the areas of feature detection and feature extraction, which aim at identifying points in a digital image at which the image brightness changes sharply or, more formally, has discontinuities...

processing step. NEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINENEWLINE

Image	Lossless compression	Lossy compression
Original
Processed byCanny edge detector

NEWLINENEWLINE Some programs allow the user to vary the amount by which individual blocks are compressed. Stronger compression is applied to areas of the image that show fewer artifacts. This way it is possible to manually reduce JPEG file size with less loss of quality. JPEG artifacts, like pixelation

Pixelation

In computer graphics, pixelation is an effect caused by displaying a bitmap or a section of a bitmap at such a large size that individual pixels, small single-colored square display elements that comprise the bitmap, are visible to the eye...

, are occasionally intentionally exploited for artistic purposes, as in Jpegs, by German photographer Thomas Ruff

Thomas Ruff

Thomas Ruff is an internationally renowned German photographer who lives and works in Düsseldorf.-Life:...

. Since the quantization stage always results in a loss of information, JPEG standard is always a lossy compression codec. (Information is lost both in quantizing and rounding of the floating-point numbers.) Even if the quantization matrix is a matrix of ones, information will still be lost in the rounding step.

Decoding

Decoding to display the image consists of doing all the above in reverse. Taking the DCT coefficient matrix (after adding the difference of the DC coefficient back in)

\left[
\begin{array}{rrrrrrrr}
 -26 & -3 & -6 & 2 & 2 & -1 & 0 & 0 \\
 0 & -2 & -4 & 1 & 1 & 0 & 0 & 0 \\
 -3 & 1 & 5 & -1 & -1 & 0 & 0 & 0 \\
 -4 & 1 & 2 & -1 & 0 & 0 & 0 & 0 \\
 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0
\end{array}
\right]

and taking the entry-for-entry product with the quantization matrix from above results in

\left[
\begin{array}{rrrrrrrr}
 -416 & -33 & -60 & 32 & 48 & -40 & 0 & 0 \\
 0 & -24 & -56 & 19 & 26 & 0 & 0 & 0 \\
 -42 & 13 & 80 & -24 & -40 & 0 & 0 & 0 \\
 -42 & 17 & 44 & -29 & 0 & 0 & 0 & 0 \\
 18 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 \\
 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0
\end{array}
\right]

which closely resembles the original DCT coefficient matrix for the top-left portion. The next step is to take the two-dimensional inverse DCT (a 2D type-III DCT), which is given by:

f_{x,y} =
 \sum_{u=0}^7
 \sum_{v=0}^7
 \alpha(u) \alpha(v) F_{u,v}
 \cos \left[\frac{\pi}{8} \left(x+\frac{1}{2}\right) u \right]
 \cos \left[\frac{\pi}{8} \left(y+\frac{1}{2}\right) v \right]

whereNEWLINE

$\ x$ is the pixel row, for the integers $\ 0 \leq x < 8$ .
$\ y$ is the pixel column, for the integers $\ 0 \leq y < 8$ .
$\ \alpha(u)$ is defined as above, for the integers $\ 0 \leq u < 8$ .
$\ F_{u,v}$ is the reconstructed approximate coefficient at coordinates $\ (u,v).$
$\ f_{x,y}$ is the reconstructed pixel value at coordinates $\ (x,y)$

NEWLINE Rounding the output to integer values (since the original had integer values) results in an image with values (still shifted down by 128) {{Multiple image|align=right|direction=vertical|image1=JPEG example image.jpg|alt1=|image2=JPEG example image decompressed.jpg|alt2=|width=180|footer=Notice the slight differences between the original (top) and decompressed image (bottom), which is most readily seen in the bottom-left corner.}}

\left[
\begin{array}{rrrrrrrr}
 -66 & -63 & -71 & -68 & -56 & -65 & -68 & -46 \\
 -71 & -73 & -72 & -46 & -20 & -41 & -66 & -57 \\
 -70 & -78 & -68 & -17 &  20 & -14 & -61 & -63 \\
 -63 & -73 & -62 &  -8 &  27 & -14 & -60 & -58 \\
 -58 & -65 & -61 & -27 &  -6 & -40 & -68 & -50 \\
 -57 & -57 & -64 & -58 & -48 & -66 & -72 & -47 \\
 -53 & -46 & -61 & -74 & -65 & -63 & -61 & -45 \\
 -47 & -34 & -53 & -74 & -60 & -47 & -47 & -41
\end{array}
\right]

and adding 128 to each entry

\left[
\begin{array}{rrrrrrrr}
 62 & 65 & 57 &  60 &  72 &  63 & 60 & 82 \\
 57 & 55 & 56 &  82 & 108 &  87 & 62 & 71 \\
 58 & 50 & 60 & 111 & 148 & 114 & 67 & 64 \\
 65 & 55 & 66 & 120 & 155 & 114 & 68 & 70 \\
 70 & 63 & 67 & 101 & 122 &  88 & 60 & 78 \\
 71 & 71 & 64 &  70 &  80 &  62 & 56 & 81 \\
 75 & 82 & 67 &  54 &  63 &  65 & 66 & 83 \\
 81 & 95 & 75 &  54 &  68 &  81 & 81 & 87
\end{array}
\right].

This is the decompressed subimage. In general, the decompression process may produce values outside of the original input range of

[0, 255]

. If this occurs, the decoder needs to clip the output values keep them within that range to prevent overflow when storing the decompressed image with the original bit depth. The decompressed subimage can be compared to the original subimage (also see images to the right) by taking the difference (original − uncompressed) results in the following error values:

\left[
\begin{array}{rrrrrrrr}
 -10 & -10 &  4 &  6 &  2 &   2 &  4 & -9 \\
   6 &   4 & -1 &  8 &  1 &  -2 &  7 &  1 \\
   4 &   9 &  8 &  2 & -4 & -10 & -1 &  8 \\
  -2 &   3 &  5 &  2 & -1 &  -8 &  2 & -1 \\
  -3 &  -2 &  1 &  3 &  4 &   0 &  8 & -8 \\
   8 &  -6 & -4 &  0 & -3 &   6 &  2 & -6 \\
  10 & -11 & -3 &  5 & -8 &  -4 & -1 &  0 \\
   6 & -15 & -6 & 14 & -3 &  -5 & -3 &  7
\end{array}
\right]

with an average absolute error of about 5 values per pixels (i.e.,

\frac{1}{64} \sum_{x=0}^7 \sum_{y=0}^7 |e(x,y)| = 4.875

). The error is most noticeable in the bottom-left corner where the bottom-left pixel becomes darker than the pixel to its immediate right.

Required precision

The encoding description in the JPEG standard does not fix the precision needed for the output compressed image. However, the JPEG standard (and the similar MPEG standards) includes some precision requirements for the decoding, including all parts of the decoding process (variable length decoding, inverse DCT, dequantization, renormalization of outputs); the output from the reference algorithm must not exceed:NEWLINE

a maximum 1 bit of difference for each pixel component
low mean square error over each 8×8-pixel block
very low mean error over each 8×8-pixel block
very low mean square error over the whole image
extremely low mean error over the whole image

NEWLINE These assertions are tested on a large set of randomized input images, to handle the worst cases. The former IEEE 1180–1990 standard contained some similar precision requirements. The precision has a consequence on the implementation of decoders, and it is critical because some encoding processes (notably used for encoding sequences of images like MPEG) need to be able to construct, on the encoder side, a reference decoded image. In order to support 8-bit precision per pixel component output, dequantization and inverse DCT transforms are typically implemented with at least 14-bit precision in optimized decoders.

Effects of JPEG compression

JPEG compression artifacts blend well into photographs with detailed non-uniform textures, allowing higher compression ratios. Notice how a higher compression ratio first affects the high-frequency textures in the upper-left corner of the image, and how the contrasting lines become more fuzzy. The very high compression ratio severely affects the quality of the image, although the overall colors and image form are still recognizable. However, the precision of colors suffer less (for a human eye) than the precision of contours (based on luminance). This justifies the fact that images should be first transformed in a color model separating the luminance from the chromatic information, before subsampling the chromatic planes (which may also use lower quality quantization) in order to preserve the precision of the luminance plane with more information bits.

Sample photographs

For information, the uncompressed 24-bit RGB bitmap image below (73,242 pixels) would require 219,726 bytes (excluding all other information headers). The filesizes indicated below include the internal JPEG information headers and some meta-data. For full quality images (Q=100), about 8.25 bits per color pixel is required. On grayscale images, a minimum of 6.5 bits per pixel is enough (a comparable Q=100 quality color information requires about 25% more encoded bits). The full quality image below (Q=100) is encoded at 9 bits per color pixel, the medium quality image (Q=25) uses 1 bit per color pixel. For most applications, the quality factor should not go below 0.75 bit per pixel (Q=12.5), as demonstrated by the low quality image. The image at lowest quality uses only 0.13 bit per pixel, and displays very poor color, it could only be usable after subsampling to a much lower display size. NEWLINE

NEWLINE

{| class="wikitable"

NEWLINE

NEWLINE |+ align="bottom"| Note: The above images are not IEEE

Institute of Electrical and Electronics Engineers

The Institute of Electrical and Electronics Engineers is a non-profit professional association headquartered in New York City that is dedicated to advancing technological innovation and excellence...

/ CCIR

ITU-R

The ITU Radiocommunication Sector is one of the three sectors of the International Telecommunication Union and is responsible for radio communication....

/ EBU

European Broadcasting Union

The European Broadcasting Union is a confederation of 74 broadcasting organisations from 56 countries, and 49 associate broadcasters from a further 25...

test images

Standard test image

A standard test image is a digital image file used across different institutions to test image processing and image compression algorithms. By using the same standard test images, different labs are able to compare results, both visually and quantitatively...

, and the encoder settings are not specified or available. |- ! Image !! Quality !! Size (bytes) !! Compression ratio !! Comment |- |

| Higher quality (Q = 100) | 83,261 | 2.6:1 | Extremely minor artifacts |- |

| High quality (Q = 50) | 15,138 | 15:1 | Initial signs of subimage artifacts |- |

| Medium quality (Q = 25) | 9,553 | 23:1 | Stronger artifacts; loss of high frequency information |- |

| Low quality (Q = 10) | 4,787 | 46:1 | Severe high frequency loss; artifacts on subimage boundaries ("macroblocking") are obvious |- |

| Lowest quality (Q = 1) | 1,523 | 144:1 | Extreme loss of color and detail; the leaves are nearly unrecognizable |} The medium quality photo uses only 4.3% of the storage space but has little noticeable loss of detail or visible artifacts. However, once a certain threshold of compression is passed, compressed images show increasingly visible defects. See the article on rate distortion theory

Rate distortion theory

Rate–distortion theory is a major branch of information theory which provides the theoretical foundations for lossy data compression; it addresses the problem of determining the minimal amount of entropy R that should be communicated over a channel, so that the source can be approximately...

for a mathematical explanation of this threshold effect. A particular limitation of JPEG in this regard is its non-overlapped 8×8 block transform structure. More modern designs such as JPEG 2000

JPEG 2000

JPEG 2000 is an image compression standard and coding system. It was created by the Joint Photographic Experts Group committee in 2000 with the intention of superseding their original discrete cosine transform-based JPEG standard with a newly designed, wavelet-based method...

and JPEG XR exhibit a more graceful degradation of quality as the bit usage decreases — by using transforms with a larger spatial extent for the lower frequency coefficients and by using overlapping transform basis functions.

Lossless further compression

From 2004 to 2008, new research has emerged on ways to further compress the data contained in JPEG images without modifying the represented image. This has applications in scenarios where the original image is only available in JPEG format, and its size needs to be reduced for archival or transmission. Standard general-purpose compression tools cannot significantly compress JPEG files. Typically, such schemes take advantage of improvements to the naive scheme for coding DCT coefficients, which fails to take into account: NEWLINE

Correlations between magnitudes of adjacent coefficients in the same block;
Correlations between magnitudes of the same coefficient in adjacent blocks;
Correlations between magnitudes of the same coefficient/block in different channels;
The DC coefficients when taken together resemble a downscale version of the original image multiplied by a scaling factor. Well-known schemes for lossless coding of continuous-tone images can be applied, achieving somewhat better compression than the Huffman coded DPCM
DPCM
Differential pulse-code modulation is a signal encoder that uses the baseline of pulse-code modulation but adds some functionalities based on the prediction of the samples of the signal...

used in JPEG.

NEWLINE Some standard but rarely-used options already exist in JPEG to improve the efficiency of coding DCT coefficients: the arithmetic coding

Arithmetic coding

option, and the progressive coding option (which produces lower bitrates because values for each coefficient are coded independently, and each coefficient has a significantly different distribution). Modern methods have improved on these techniques by reordering coefficients to group coefficients of larger magnitude together; using adjacent coefficients and blocks to predict new coefficient values; dividing blocks or coefficients up among a small number of independently coded models based on their statistics and adjacent values; and most recently, by decoding blocks, predicting subsequent blocks in the spatial domain, and then encoding these to generate predictions for DCT coefficients. Typically, such methods can compress existing JPEG files between 15 and 25 percent, and for JPEGs compressed at low-quality settings, can produce improvements of up to 65%. A freely-available tool called packJPG is based on the 2007 paper "Improved Redundancy Reduction for JPEG Files." There are also at least two companies selling proprietary tools with similar capabilities, Infima's JPACK and Smith Micro Software

Smith Micro Software

Smith Micro Software, Inc. , founded in 1983 by William W. Smith, Jr., is a diversified developer and marketer of both enterprise and consumer-level software solutions and services...

's StuffIt

StuffIt

StuffIt is a family of computer software utilities for archiving and compressing files on the Macintosh and Microsoft Windows platforms: it was originally produced for the Macintosh. An old version for Linux and Sun Solaris 2.7 or later is also available...

, both of which claim to have pending patents on their respective technologies.

JPEG Stereoscopic

{{main|JPEG Stereo}} JPEG Stereoscopic (JPS, extension .jps) is a JPEG-based format for stereoscopic

Stereoscopy

Stereoscopy refers to a technique for creating or enhancing the illusion of depth in an image by presenting two offset images separately to the left and right eye of the viewer. Both of these 2-D offset images are then combined in the brain to give the perception of 3-D depth...

images. It has a range of configurations stored in the JPEG APP3 marker field, but usually contains one image of double width, representing two images of identical size in cross-eyed (i.e. left frame on the right half of the image and vice versa) side-by-side arrangement. This file format can be viewed as a JPEG without any special software, or can be processed for rendering in other modes.

JPEG Multi-Picture Format

JPEG Multi-Picture Format (MPO, extension .mpo) is a JPEG-based format for multi-view images. It contains two or more JPEG files concatenated together. There are also special EXIF fields describing its purpose. This is used by the Fujifilm FinePix Real 3D W1

Fujifilm FinePix Real 3D W1

The Fujifilm FinePix W Series Real 3D is a line of consumer-grade digital cameras designed to capture stereoscopic images that recreate the perception of 3-D depth, having both still and video formats while retaining standard 2D still image and movie modes...

camera, Panasonic

Panasonic

Panasonic is an international brand name for Japanese electric products manufacturer Panasonic Corporation, which was formerly known as Matsushita Electric Industrial Co., Ltd...

Lumix

Lumix is Panasonic's brand of digital cameras, ranging from pocket point-and-shoot models to digital SLRs.Compact digital camera DMC-LC5 and DMC-F7 were the first products of the Lumix series released in 2001. They are equipped with Leica lenses....

DMC-TZ20, Sony

Sony

, commonly referred to as Sony, is a Japanese multinational conglomerate corporation headquartered in Minato, Tokyo, Japan and the world's fifth largest media conglomerate measured by revenues....

DSC-HX7V, HTC Evo 3D

HTC EVO 3D

The HTC Evo 3D is an Android 2.3 smartphone that allows for the creation and viewing of 3D content through the use of two 5 MP rear-facing cameras and a glasses-free 3D-capable 4.3" qHD touch screen. In the United States, the Evo 3D is available exclusively on the Sprint/Nextel network...

, the JVC GY-HMZ1U AVCHD/MVC extension camcorder and by the Nintendo 3DS

Nintendo 3DS

The is a portable game console produced by Nintendo. The autostereoscopic device is able to project stereoscopic 3D effects without the use of 3D glasses or any additional accessories. The Nintendo 3DS features backward compatibility with Nintendo DS series software, including Nintendo DSi software...

for its 3D Camera.

Patent issues

In 2002, Forgent Networks

Forgent Networks

Asure Software is a software company which has licensing as its primary revenue source. Prior to September 13, 2007, the company was known as Forgent Networks. Critics claim Asure profits primarily as a patent troll...

asserted that it owned and would enforce patent

Patent

rights on the JPEG technology, arising from a patent that had been filed on October 27, 1986, and granted on October 6, 1987 ({{US patent|4698672}}). The announcement created a furor reminiscent of Unisys

Unisys

Unisys Corporation , headquartered in Blue Bell, Pennsylvania, United States, and incorporated in Delaware, is a long established business whose core products now involves computing and networking.-History:...

' attempts to assert its rights over the GIF image compression standard. The JPEG committee investigated the patent claims in 2002 and were of the opinion that they were invalidated by prior art

Prior art

Prior art , in most systems of patent law, constitutes all information that has been made available to the public in any form before a given date that might be relevant to a patent's claims of originality...

. Others also concluded that Forgent did not have a patent that covered JPEG. Nevertheless, between 2002 and 2004 Forgent was able to obtain about US$105 million by licensing their patent to some 30 companies. In April 2004, Forgent sued 31 other companies to enforce further license payments. In July of the same year, a consortium of 21 large computer companies filed a countersuit, with the goal of invalidating the patent. In addition, Microsoft launched a separate lawsuit against Forgent in April 2005. In February 2006, the United States Patent and Trademark Office

United States Patent and Trademark Office

The United States Patent and Trademark Office is an agency in the United States Department of Commerce that issues patents to inventors and businesses for their inventions, and trademark registration for product and intellectual property identification.The USPTO is based in Alexandria, Virginia,...

agreed to re-examine Forgent's JPEG patent at the request of the Public Patent Foundation

Public Patent Foundation

Public Patent Foundation, or PUBPAT, is a nonprofit organization that seeks to limit perceived abuse of the United States patent system. It was founded in 2003 by Dan Ravicher. , there was growing concern by many technology professionals over the number of patents granted that are either too...

. On May 26, 2006 the USPTO found the patent invalid based on prior art

Prior art

. The USPTO also found that Forgent knew about the prior art

Prior art

, and did not tell the Patent Office, making any appeal to reinstate the patent highly unlikely to succeed. Forgent also possesses a similar patent granted by the European Patent Office in 1994, though it is unclear how enforceable it is. As of October 27, 2006, the U.S. patent's 20-year term appears to have expired, and in November 2006, Forgent agreed to abandon enforcement of patent claims against use of the JPEG standard. The JPEG committee has as one of its explicit goals that their standards (in particular their baseline methods) be implementable without payment of license fees, and they have secured appropriate license rights for their upcoming JPEG 2000

JPEG 2000

standard from over 20 large organizations. Beginning in August 2007, another company, Global Patent Holdings, LLC claimed that its patent ({{US patent|5,253,341}}) issued in 1993, is infringed by the downloading of JPEG images on either a website or through e-mail. If not invalidated, this patent could apply to any website that displays JPEG images. The patent emerged{{Clarify|date=February 2010|reason=how can it emerge in 2007 when a cite below has "In autumn 2000 ..."}} in July 2007 following a seven-year reexamination by the U.S. Patent and Trademark Office in which all of the original claims of the patent were revoked, but an additional claim (claim 17) was confirmed. In its first two lawsuits following the reexamination, both filed in Chicago, Illinois, Global Patent Holdings sued the Green Bay Packers, CDW, Motorola, Apple, Orbitz, Officemax, Caterpillar, Kraft and Peapod as defendants. A third lawsuit was filed on December 5, 2007 in South Florida against ADT Security Services, AutoNation, Florida Crystals Corp., HearUSA, MovieTickets.com, Ocwen Financial Corp. and Tire Kingdom, and a fourth lawsuit on January 8, 2008 in South Florida against the Boca Raton Resort & Club. A fifth lawsuit was filed against Global Patent Holdings in Nevada. That lawsuit was filed by Zappos.com, Inc., which was allegedly threatened by Global Patent Holdings, and seeks a judicial declaration that the '341 patent is invalid and not infringed. Global Patent Holdings had also used the '341 patent to sue or threaten outspoken critics of broad software patents, including Gregory Aharonian and the anonymous operator of a website blog known as the "Patent Troll Tracker." On December 21, 2007, patent lawyer Vernon Francissen of Chicago asked the U.S. Patent and Trademark Office to reexamine the sole remaining claim of the '341 patent on the basis of new prior art. On March 5, 2008, the U.S. Patent and Trademark Office agreed to reexamine the '341 patent, finding that the new prior art raised substantial new questions regarding the patent's validity. In light of the reexamination, the accused infringers in four of the five pending lawsuits have filed motions to suspend (stay) their cases until completion of the U.S. Patent and Trademark Office's review of the '341 patent. On April 23, 2008, a judge presiding over the two lawsuits in Chicago, Illinois granted the motions in those cases. On July 22, 2008, the Patent Office issued the first "Office Action" of the second reexamination, finding the claim invalid based on nineteen separate grounds. On Nov. 24, 2009, a Reexamination Certificate was issued cancelling all claims.

Standards

{{Main|Joint Photographic Experts Group#Published Standards}} {{Main|Joint Bi-level Image experts Group#Published Standards}} Here are some examples of standards created by ISO/IEC JTC1 SC29 Working Group 1 (WG 1), which includes the Joint Photographic Experts Group and Joint Bi-level Image experts Group:NEWLINE

JPEG (lossy and lossless): ITU-T T.81, ISO/IEC 10918-1
JPEG extensions: ITU-T T.84
JPEG-LS
JPEG-LS
Lossless JPEG refers to a 1993 addition to JPEG standard by the Joint Photographic Experts Group to enable lossless compression. However, it might be used as an umbrella term to refer to all lossless compression schemes developed by the Joint Photographic Expert group...

(lossless, improved): ITU-T T.87, ISO/IEC 14495-1
JBIG
JBIG
JBIG is a lossless image compression standard from the Joint Bi-level Image Experts Group, standardized as ISO/IEC standard 11544 and as ITU-T recommendation T.82. It is widely implemented in fax machines. Now that the newer bi-level image compression standard JBIG2 has been released, JBIG is also...

(lossless, bi-level pictures, fax): ITU-T T.82, ISO/IEC 11544
JBIG2
JBIG2
JBIG2 is an image compression standard for bi-level images, developed by the Joint Bi-level Image Experts Group. It is suitable for both lossless and lossy compression...

(bi-level pictures): ITU-T T.88, ISO/IEC 14492
JPEG 2000
JPEG 2000
JPEG 2000 is an image compression standard and coding system. It was created by the Joint Photographic Experts Group committee in 2000 with the intention of superseding their original discrete cosine transform-based JPEG standard with a newly designed, wavelet-based method...

: ITU-T T.800, ISO/IEC 15444-1
JPEG 2000 extensions: ITU-T T.801
JPEG XR (formerly called HD Photo prior to standardization) : ITU-T T.832, ISO/IEC 29199-2

NEWLINE

External links

{{Commons category|JPEG}}NEWLINE

JPEG Standard (JPEG ISO/IEC 10918-1 ITU-T Recommendation T.81) at W3.org
Official Joint Photographic Experts Group site
JFIF File Format at W3.org
JPEG File Size Calculator
Wotsit.org's entry on the JPEG format
Example images over the full range of quantization levels from 1 to 100 at visengi.com
Public domain JPEG compressor in a single C++ source file, along with a matching decompressor at code.google.com

NEWLINE {{Compression Formats}} {{Graphics file formats}} {{DEFAULTSORT:Jpeg}}