Speckle reduction of polarimetric SAR imagery has been studied using several different approaches. All these approaches exploited the degree of independence between HH, HV and VV channels. The statistical characteristics, such as correlation between channels, and polarimetric property preservation, were not addressed. This paper proposes a new approach in polarimetric SAR filtering. The new approach emphasizes not introducing cross-talk, preserving polarimetric information and statistical correlation between channels, and not degrading the image quality. To avoid cross-talk, each element of the covariance matrix has to be filtered independently. This rules out current methods of polarimetric SAR filtering. To preserve the polarimetric signature, each element of the covariance matrix should be filtered in a way similar to multi-look processing by averaging the covariance matrix of neighboring pixels, but without the deficiency of smearing edges, or degrading image quality. The proposed polarimetric SAR filter uses edge- directed non-square windows and applies the local statistics filter. The impact of using this polarimetric speckle filtering on terrain classification is also studied. NASA/JPL Les Landes polarimetric P-Band and C-Band SAR data is used for illustration.
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