Robust ICA neural network and application on synthetic aperture radar (SAR) image analysis

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

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Abstract

Independent component analysis (ICA) has shown success in the separation of sources in lots of applications. However, in synthenic aperture radar (SAR) images the noise is multiplicative, so the applicability of ICA is seriously reduced. This paper proposes a new robust independent component analysis neural network (RICANN) that improves the robustness of ICA by adding outlier rejection rule. Its application in synthetic aperture radar (SAR) is discussed. The results show the potential usage in SAR image processing problems.