Abstract
Polarimetric scattering information provided by fully polarimetric synthetic aperture radar (SAR) is useful for discriminating between different terrain covers. Conventionally, eigenanalysis is used to synthesize a polarimetric matched filter (PMF) that maximizes the contrast between the features of interest, but this involves many algebraic operations, and only one contrast ratio for any two classes can be obtained at one time. This paper describes the application of a genetic algorithm to the contrast enhancement. When it is used, all the contrast ratios characterizing the best discrimination for any two of all possible classes can be obtained simultaneously, providing a new and more convenient way to solve the problem of the optimization of polarimetric contrast enhancement. Two independent sets of L-band fully polarimetric SAR images are used as test data; the results show that the proposed method is very effective and promising.
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