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Proceedings Paper

SAR image speckle noise reduction based on second generation bandelets and a kernel-based possibilistic C-means clustering
Author(s): Shuang Liu; Licheng Jiao; Guofeng Zhang
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Paper Abstract

Synthetic Aperture Radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of the scattering phenomenon. Speckle noise of SAR affects image quality and image interpretation seriously. To alleviate deleterious effects of speckle, various ways have been devised to suppress it. An ideal algorithm should smooth the speckle without blurring edges and fine details. But most classical algorithms cannot satisfy these two demands very well. Due to the property of SAR images speckles is multiplicative noise, it difficult to estimate the variance of the high-frequency subband coefficients. Most classical approaches such as wavelet thresholding or shrinkage scheme of Donoho and Johnstone are not suitable for SAR images speckle noise removal. In this paper, a novel approach to SAR image speckle reduction is presented, which is based on second generation bandelets and a kernel-based possibilistic C-means clustering algorithm (BKPCM).

Paper Details

Date Published: 15 November 2007
PDF: 6 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67872L (15 November 2007); doi: 10.1117/12.750722
Show Author Affiliations
Shuang Liu, Xidian Univ. (China)
Licheng Jiao, Xidian Univ. (China)
Guofeng Zhang, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 6787:
MIPPR 2007: Multispectral Image Processing

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