基于BayesShrink软阈值的Bandelet域SAR图像去噪

doi:10.3969/j.issn.1006-2475.2011.11.018

计算机与现代化 ›› 2011, Vol. 1 ›› Issue (11): 67-3.doi: 10.3969/j.issn.1006-2475.2011.11.018

基于BayesShrink软阈值的Bandelet域SAR图像去噪

许亚男，汪贤才

池州学院物理与机电工程系，安徽池州247000

收稿日期:2011-07-14 修回日期:1900-01-01 出版日期:2011-11-28 发布日期:2011-11-28

Bandelet Domain SAR Images Despeckling Based on BayesShrink Softthresholding

XU Ya-nan, WANG Xian-cai

Dept. of Physical and Mechanical and Electrical Engineering, Chizhou University, Chizhou 247000, China

Received:2011-07-14 Revised:1900-01-01 Online:2011-11-28 Published:2011-11-28

摘要/Abstract

摘要：

合成孔径雷达(SAR)图像产生的相干斑噪声是一种乘性噪声，严重影响SAR图像的质量。本文提出一种新的极化SAR图像的去噪方法，该方法对极化SAR图像进行自适应Bandelets阈值方法，阈值采用BayesShrink软阈值方法，将其应用于自适应Bandelets系数。通过实验对比，证实此法与小波阈值去噪相比，能够更好地保持图像纹理和边缘特征。

关键词: 自适应Bandelet变换, BayesShrink软阈值, 小波去噪, SAR图像

Abstract:

Synthetic Aperture Radar (SAR) images are inherently affected by multiplicative speckle noise, which seriously affects the quality of SAR images. This paper presents a despeckling method for SAR images based on adaptive Bandelets thresholding. This threshold is derived in a Bayesian framework named BayesShrink softthresholding, and it is applied to adaptive Bandelets coefficients to achieve more satisfying results. The performances of this proposed scheme and wavelet thresholding for despeckling SAR images are compared through experiment. Experiment results clearly demonstrate the proposed scheme is able to better keep texture and edge character.

Key words: adaptive Bandelet transform, BayesShrink softthresholding, wavelet denoising, SAR images

许亚男;汪贤才. 基于BayesShrink软阈值的Bandelet域SAR图像去噪[J]. 计算机与现代化, 2011, 1(11): 67-3.

XU Ya-nan;WANG Xian-cai. Bandelet Domain SAR Images Despeckling Based on BayesShrink Softthresholding[J]. Computer and Modernization, 2011, 1(11): 67-3.

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基于BayesShrink软阈值的Bandelet域SAR图像去噪

Bandelet Domain SAR Images Despeckling Based on BayesShrink Softthresholding

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