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Proceedings Paper

SAR image adaptive MAP filtering based on the generalized Gaussian model
Author(s): Shaobo Chen; Jiangou Liu; Guoyou Wang; Qiaoliang Li
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Paper Abstract

Synthetic aperture radar (SAR) images are inherently affected by a signal dependent noise known as speckle, which is due to the radar wave coherence. In this paper, we propose a novel adaptive despeckling filter and derive a maximum a posteriori (MAP) estimator for the radar cross section (RCS). We first employ a logarithmic transformation to change the multiplicative speckle noise into additive noise. We model the RCS using the recently introduced Generalized Gaussian density function[1], Which was proved to be the best described for the SAR Amplitude. We estimate model parameters from noisy observations by means of second-kind statistics theory, which relies on the Mellin transform. Finally, we compare the proposed algorithm with several classical speckle filters applied on actual SAR images. Experimental results show that the MAP filter based on the Generalized Gaussian prior for the RCS is among the best for speckle removal.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678711 (15 November 2007); doi: 10.1117/12.749035
Show Author Affiliations
Shaobo Chen, Huazhong Univ. of Science and Technology (China)
Jiangou Liu, Huazhong Univ. of Science and Technology (China)
Guoyou Wang, Huazhong Univ. of Science and Technology (China)
Qiaoliang Li, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 6787:
MIPPR 2007: Multispectral Image Processing
Henri Maître; Hong Sun; Jianguo Liu; Enmin Song, Editor(s)

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