TL;DRAbstract
Synthetic Aperture Radar (SAR) systems can provide high-resolution, microwave brightness images of the earth's surface, typically in the 1GHz-10GHz frequency (1cm-60cm wavelength) range. These images are sensitive to the roughness, geometry and dielectric properties of targets, and thus provide geophysical measurements of the surface which are complementary to the spectral measurements captured by optical sensors, and to other sources of data such as geochemistry or rasterized colour maps. The fusion of SAR with other data sets is recognized as a useful approach for maximizing information extraction from remotely sensed data. This paper summarizes the rationale for SAR data fusion and will review image processing techniques to accomplish it. The advantages and limitations of techniques such as band combinations, band ratioing, statistical transforms and colour space transforms are discussed.
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Synthetic Aperture Radar (SAR) systems can provide high-resolution, microwave brightness images of the earth's surface, typically in the 1GHz-10GHz frequency (1cm-60cm wavelength) range. These images are sensitive to the roughness, geometry and dielectric properties of targets, and thus provide geophysical measurements of the surface which are complementary to the spectral measurements captured by optical sensors, and to other sources of data such as geochemistry or rasterized colour maps. The fusion of SAR with other data sets is recognized as a useful approach for maximizing information extraction from remotely sensed data. This paper summarizes the rationale for SAR data fusion and will review image processing techniques to accomplish it. The advantages and limitations of techniques such as band combinations, band ratioing, statistical transforms and colour space transforms are discussed.
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