SAR image adaptive MAP filtering based on the generalized Gaussian model

Shaobo Chen; Jiangou Liu; Guoyou Wang; Qiaoliang Li

doi:10.1117/12.749035

15 November 2007 SAR image adaptive MAP filtering based on the generalized Gaussian model

Shaobo Chen, Jiangou Liu, Guoyou Wang, Qiaoliang Li

Proceedings Volume 6787, MIPPR 2007: Multispectral Image Processing; 678711 (2007) https://doi.org/10.1117/12.749035
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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.

Citation Download Citation

Shaobo Chen, Jiangou Liu, Guoyou Wang, and Qiaoliang Li "SAR image adaptive MAP filtering based on the generalized Gaussian model", Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678711 (15 November 2007); https://doi.org/10.1117/12.749035

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KEYWORDS

Image filtering

Speckle

Synthetic aperture radar

Gaussian filters

Digital filtering

Statistical analysis

Electronic filtering

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