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commercial data packages also commonly include both lower-resolution multispectral bands and a single panchromatic band. One of the principal reasons for configuring satellite sensors this way is to keep satellite weight, cost, bandwidth and complexity down. Pan sharpening uses spatial information
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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 pansharpened color
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and nearly every map creating company use this technique to increase image quality. Pansharpening produces a high-resolution color image from three, four or more low-resolution multispectral satellite bands plus a corresponding high-resolution panchromatic band:
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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.
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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.
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Alignment: the up-sampled color bands and the panchromatic band are aligned to reduce artifacts due to mis-registration (generally, when the data comes from the same sensor, this step is usually not necessary);
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Reverse transform: the reverse transformation is performed using the substituted intensity component to transform back to the original color space.
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Forward transform: the up-sampled color bands are transformed to an alternate color space (where intensity is orthogonal to the color information);
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One common class of algorithms for pansharpening is called “component substitution,” which usually involves the following steps:
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Intensity matching: the intensity of the color bands is matched to the pan band intensity in the transformed space;
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Component substitution: the pan band is then directly substituted for the transformed intensity component;
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Up-sampling: the color bands are up-sampled to the same resolution as the panchromatic band;
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Such band combinations are commonly bundled in satellite data sets, for example
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Low-res color bands + High-res grayscale band = High-res color image
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237:"Smart pansharpening approach using kernel-based image filtering"
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Common color-space transformation used for pan sharpening are
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imagery to create a single high-resolution color image.
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and replacing the first component with the pan band.
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