基于Shearlet变换的SAR图像自适应去噪算法

›› 2012, Vol. 25 ›› Issue (6): 83-.

基于Shearlet变换的SAR图像自适应去噪算法

刘成皓,刘文波,张弓

(1.南京航空航天大学自动化学院,江苏南京 210016;2.南京航空航天大学信息科学与技术学院,江苏南京 210016)

出版日期:2012-06-15 发布日期:2012-08-23
作者简介:刘成皓(1985—),男,硕士研究生。研究方向:SAR雷达图像处理。

Self-adaptive Denoising for SAR Image Based on Shearlet Transform

LIU Cheng-Hao, LIU Wen-Bo, ZHANG Gong

(1.College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;
2.College of Information Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)

Online:2012-06-15 Published:2012-08-23

摘要/Abstract

摘要：

针对SAR图像相干斑噪声的特点,提出了一种基于Shearlet变换的自适应去噪算法。首先对图像进行Shearlet变换,在考虑噪声度量和各尺度空间相关性的基础上,对Shearlet系数进行自适应收缩,将修正后的系数通过Shearlet逆变换重构图像。实验结果表明,文中算法在SAR图像处理相干斑得到有效抑制的同时,具有较强的边缘保持能力。

关键词: SAR图像, 相干斑, Sheatlet变换, 自适应去噪

Abstract:

In view of the characteristics of relevant speckle noise of SAR images,this paper proposes a self-adaptive shrinkage method for denoising based on Shearlet transform.First,the image is processed with Shearlet transform.Then,the Shearlet coefficient is contracted by the self-adaptive shrinkage method considering the noise measurement and the relevance of multi-scale spaces.Finally,one image is reconstructed through the inverse Shearlet transform using the amended coefficient.The experiments indicate that the algorithm can wipe off the relevant speckle noise of SAR images and has strong capability of maintaining the edge.

Key words: SAR image;speckle noise;Shearlet transform;denoising based on self-adaptive shrinkage

中图分类号:

TP391.4

刘成皓, 刘文波, 张弓. 基于Shearlet变换的SAR图像自适应去噪算法[J]. , 2012, 25(6): 83-.

LIU Cheng-Hao, LIU Wen-Bo, ZHANG Gong. Self-adaptive Denoising for SAR Image Based on Shearlet Transform[J]. , 2012, 25(6): 83-.

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