Pansharpened image
Encyclopedia
Pansharpening is a process of merging high resolution panchromatic
and lower resolution multispectral imagery to create a single high resolution color image. Google Maps
and nearly every map creating company uses this technique to increase image quality. Pan sharpening produces a high-resolution color image from three, four or more low-resolution multispectral satellite bands plus a corresponding high-resolution panchromatic band:
Low Res Color Bands + High Res Grayscale Band = Hi Res Color Image
Such band combinations are commonly bundled in satellite data sets, for example Landsat 7, which includes six 30m resolution multispectral bands, a 60m thermal infrared band plus a 15m resolution panchromatic band. SPOT®, GeoEye® and Digital Globe® commercial data packages also commonly include both lower resolution multispectral bands and a single panchromatic band. One of the principle reasons for configuring satellite sensors this way is to keep satellite weight, cost, bandwidth and complexity down. Pan sharpening uses spatial information in the high-resolution grayscale band and color information in the multispectral bands to create a high-resolution color image, essentially increasing the resolution of the color information in the data set to match that of the panchromatic band. This is usually done by transforming the multispectral data from RGB (red-green-blue) color space to an alternative color space containing an intensity vector (for example HSI or hue-saturation-intensity color space). The color information (hue and saturation) channels are resampled to match the resolution of the panchromatic channel and then interpolated. The panchromatic channel is then substituted for the intensity channel and then the processed data is transformed back to RGB color space (at the higher resolution). Other classes of pan sharpening algorithms are based on transformation of the image data from the spatial domain to the frequency domain, processing the information and then transforming back to the spatial domain.
Pan sharpening techniques can result in spectral distortions when pan sharpening satellite images as a result of the nature of the panchromatic band. The Landsat panchromatic band for example is not sensitive to blue light. As a result, the spectral characteristics of the raw pan sharpened color image may not exactly match those of the corresponding low-resolution RGB image, resulting in altered color tones. This has resulted in the development of many algorithms that attempt to reduce this spectral distortion and to produce visually pleasing images. For additional information on pan sharpening see http://www.pancroma.com/whitePapers.html
Panchromatic
Panchromatic film is a type of black-and-white photographic film that is sensitive to all wavelengths of visible light. A panchromatic film therefore produces a realistic reproduction of a scene as it appears to the human eye. Almost all modern photographic film is panchromatic, but some types are...
and lower resolution multispectral imagery to create a single high resolution color image. Google Maps
Google Maps
Google Maps is a web mapping service application and technology provided by Google, free , that powers many map-based services, including the Google Maps website, Google Ride Finder, Google Transit, and maps embedded on third-party websites via the Google Maps API...
and nearly every map creating company uses this technique to increase image quality. Pan sharpening produces a high-resolution color image from three, four or more low-resolution multispectral satellite bands plus a corresponding high-resolution panchromatic band:
Low Res Color Bands + High Res Grayscale Band = Hi Res Color Image
Such band combinations are commonly bundled in satellite data sets, for example Landsat 7, which includes six 30m resolution multispectral bands, a 60m thermal infrared band plus a 15m resolution panchromatic band. SPOT®, GeoEye® and Digital Globe® commercial data packages also commonly include both lower resolution multispectral bands and a single panchromatic band. One of the principle reasons for configuring satellite sensors this way is to keep satellite weight, cost, bandwidth and complexity down. Pan sharpening uses spatial information in the high-resolution grayscale band and color information in the multispectral bands to create a high-resolution color image, essentially increasing the resolution of the color information in the data set to match that of the panchromatic band. This is usually done by transforming the multispectral data from RGB (red-green-blue) color space to an alternative color space containing an intensity vector (for example HSI or hue-saturation-intensity color space). The color information (hue and saturation) channels are resampled to match the resolution of the panchromatic channel and then interpolated. The panchromatic channel is then substituted for the intensity channel and then the processed data is transformed back to RGB color space (at the higher resolution). Other classes of pan sharpening algorithms are based on transformation of the image data from the spatial domain to the frequency domain, processing the information and then transforming back to the spatial domain.
Pan sharpening techniques can result in spectral distortions when pan sharpening satellite images as a result of the nature of the panchromatic band. The Landsat panchromatic band for example is not sensitive to blue light. As a result, the spectral characteristics of the raw pan sharpened color image may not exactly match those of the corresponding low-resolution RGB image, resulting in altered color tones. This has resulted in the development of many algorithms that attempt to reduce this spectral distortion and to produce visually pleasing images. For additional information on pan sharpening see http://www.pancroma.com/whitePapers.html