基于Shearlets变换的SAR图像去噪

doi:10.3969/j.issn.0255-8297.2012.06.012

应用科学学报 ›› 2012, Vol. 30 ›› Issue (6): 629-634.doi: 10.3969/j.issn.0255-8297.2012.06.012

基于Shearlets变换的SAR图像去噪

刘帅奇，胡绍海，肖扬

北京交通大学信息科学研究所，北京100044

收稿日期:2011-06-10 修回日期:2011-12-31 出版日期:2012-11-27 发布日期:2011-12-31
通信作者: 刘帅奇，博士生，研究方向：合成孔径雷达、多维信号、小波信号处理，E-mail: shdkj-1918@163.com
作者简介:刘帅奇，博士生，研究方向：合成孔径雷达、多维信号、小波信号处理，E-mail: shdkj-1918@163.com；肖扬，教授，博导，研究方向：SAR信号处理、多维信号处理、空时信号处理，E-mail: yxiao@bjtu.edu.cn
基金资助:
国家自然科学基金(No.60572093)；北京市自然科学基金(No.4102050)；航空科学基金与航空电子系统射频综合仿真航空科技
重点实验室基金(No.201120M5007)资助

De-noising of SAR Images Based on Shearlets Transform

LIU Shuai-qi, HU Shao-hai, XIAO Yang

Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China

Received:2011-06-10 Revised:2011-12-31 Online:2012-11-27 Published:2011-12-31

摘要/Abstract

摘要： 在合成孔径雷达(SAR)相干噪声模型基础上提出了一种基于剪切波(Shearlets)变换的SAR图像去噪算法. Shearlets变换继承了Curvele变换和Contourlet 变换的优点，既有灵活的方向选择性又易于实现，并且对于包含C2 奇异曲线或曲面的高维信号具有最优逼近特性. 该文采用Shearlets逼近SAR图像，再用基于贝叶斯估计
理论的双变量阈值函数对Shearlets变换系数进行处理得到去噪图像. 仿真结果表明，相比使用同级Contourlet双变量阈值去噪，该算法峰值信噪比提高2 dB；相比使用非下采样Contourlet变换双变量阈值算法去噪，该算法去噪后图像不仅峰值信噪比有所提高，而且更平滑，计算时间也大大减少.

关键词: 去噪, 剪切波, 轮廓波, 合成孔径雷达

Abstract: This paper proposes a de-noising algorithm for SAR images based on Shearlets transform. Shearlets transformation is multi-scale geometric analysis which possesses the advantages of Contourlet transform and Curvelet transform. For a singular curve or surface containing C2 high-dimensional signals, it is an optimal approximation. We apply Shearlets to approach SAR images, and use a bivariate threshold according to the Bayesian estimation theory to perform image de-noising. The obtained results show an increase of 2 dB in PSNR as compared to the Contourlet-based method with a bivariate threshold. Compared with the nonsubsampled Contourlet method with a bivariate threshold, the proposed method gives a higher PSNR and smoother denoised images. In addition, computation complexity is reduced.

Key words: de-nosing, Shearlets, Contourlet, synthetic aperture radar (SAR)

中图分类号:

TN911.6

刘帅奇，胡绍海，肖扬. 基于Shearlets变换的SAR图像去噪[J]. 应用科学学报, 2012, 30(6): 629-634.

LIU Shuai-qi, HU Shao-hai, XIAO Yang. De-noising of SAR Images Based on Shearlets Transform[J]. Journal of Applied Sciences, 2012, 30(6): 629-634.

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基于Shearlets变换的SAR图像去噪

De-noising of SAR Images Based on Shearlets Transform

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