Speckle reduction of polarimetric SAR images based on neural ICA

Authors:
Jian Ji;Zheng Tian
Affiliations:
Department of Computer Science & Technology, Northwestern Polytechnical University, Xi'an, China;Department of Computer Science & Technology, Northwestern Polytechnical University, Xi'an, China
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Year:
2006

Citing 6
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Abstract

The polarimetric synthetic aperture radar (PSAR) images are modeled by a mixture model that results from the product of two independent models, one characterizes the target response and the other characterizes the speckle phenomenon. For the scene interpretation, it is desirable to separate between the target response and the speckle. For this purpose, we proposed a new speckle reduction approach using independent component analysis (ICA) based on statistical formulation of PSAR image. In addition, we apply four ICA algorithms on real PSAR images and compare their performances. The comparison reveals characteristic differences between the studied neural ICA algorithms, complementing the results obtained earlier.