一种抑制合成孔径雷达图像相干斑的各向异性扩散滤波方法

朱磊; 韩天琪; 水鹏朗; 卫建华; 顾梅花

doi:10.7498/aps.63.179502

摘要

本文提出了一种抑制合成孔径雷达图像乘性相干斑噪声的各向异性扩散滤波新方法. 该方法将受自适应耦合函数控制的平均曲率运动嵌入到传统相干斑抑制的各向异性扩散方程中，形成了一种可有效抑制边缘区域相干斑与同质区块效应现象的各向异性扩散新方程，同时在新建的扩散方程中，引入了由改进Frost滤波与局部方向比率联合构建的一种带方向约束的新扩散函数，进一步削弱了块效应现象且明显改善了抑斑图像的边缘抖动扭曲问题. 实验结果表明该方法在有效保护图像边缘的同时，能充分平滑同质区与边缘区域的相干斑，明显削弱块效应现象，有效改善抑斑图像边缘抖动扭曲问题，而抑斑图像无论视觉效果还是参数指标均比多种传统抑斑方法更具优势.

关键词:

Abstract

An anisotropic diffusion filtering method is proposed to reduce multiplicative speckle noise in synthetic aperture radar images. A new anisotropic diffusion equation, which can effectively smooth speckles near the edges and reduce blocking artifacts in homogeneous regions, is established by embedding the mean curvature motion controlled by an adaptive coupling function into a traditional speckle reducing anisotropic diffusion equation. Moreover, a new direction-constrained diffusion function formed by combining the local directional ratios with the improved Frost filtering is introduced into the new anisotropic diffusion equation, so that it can further reduce blocking artifacts and obviously improve the edge distortion problem in the despeckled synthetic aperture radar images. Experimental results show that the proposed method can obviously reduce blocking artifacts, sufficiently smooth speckle noise in homogeneous regions and near the edges while preserving edges, and effectively improve the edge distortion problem. Visual quality and performance indexes of the despeckled images show that the proposed method outperforms several despeckling methods.

Keywords:

作者及机构信息

1.
西安工程大学电子信息学院, 西安 710048;

2.
西安电子科技大学雷达信号处理国家重点实验室, 西安 710071

基金项目: 国家自然科学基金（批准号：61271295）和陕西省教育厅自然科学基金（批准号：14JK1303）资助的课题.

Authors and contacts

1.
Electronics and Information College, Xi'an Polytechnic University, Xi'an 710048, China;

2.
National Lab of Radar Signal Processing, Xidian University, Xi'an 710071, China

Funds: Project supported by the National Natural Science Foundation of China(Grant No. 61271295), and the Natural Science Foundation of Shaanxi Province Department of Education (Grand No. 14JK1303).

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施引文献

[1]	Wang C, Mao Y X, Tang Z, Fang C, Yu Y J, Qi B 2011 Chin. Phys. B 20 332
[2]
[3]	Yuan Y, Yang S H 2012 Chin. Phys. B 21 287
[4]
[5]	Ji W J, Tong C M 2013 Chin. Phys. B 22 68
[6]	Lee J S 1980 IEEE Trans. Pattern Anal. Mach. Intell. PAMI-2 165
[7]
[8]	Kuan D T, Sawchuk A A, Strand T C, Chavel P 1985 IEEE Trans. Pattern Anal. Mach. Intell. PAMI- 7 165
[9]
[10]
[11]	Frost V S, Stiles J A, Shanmugan K S, Holtzman J C 1982 IEEE Trans. Pattern Anal. Mach. Intell. PAMI-4 157
[12]
[13]	Touzi R 2002 IEEE Trans. Geosci. Remote Sensing 40 2392
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[15]
[16]	Zhu L, Shui P L, Zhang W C 2012 J. Xi'an Jiaotong Univ. 46 83 (in Chinese)[朱磊, 水鹏朗, 章为川 2012 西安交通大学学报 46 83]
[17]
[18]	Li J C, Huang S X, Peng Y H, Zhang W M 2012 Acta Phys. Sin. 61 119501 (in Chinese)[李金才, 黄思训, 彭宇行, 张卫民 2012 61 119501]
[19]
[20]	Li J C, Huang B, Peng Y H 2012 Acta Phys. Sin. 61 189501 (in Chinese)[李金才, 黄斌, 彭宇行 2012 61 189501]
[21]
[22]
[23]	Zhu L, Shui P L, Zhang W C 2014 J. Electron. Inf. Tech. 36 220 (in Chinese)[朱磊, 水鹏朗, 章为川 2014 电子与信息学报 36 220]
[24]
[25]	Xie H, Pierce L E, Ulaby F T 2002 IEEE Trans. Geosci. Remote Sensing 40 2196
[26]
[27]	Achim A, Tsakalides P, Bezerianos A 2003 IEEE Trans. Geosci. Remote Sensing 41 1773
[28]
[29]	Argenti F, Bianchi T, Alparone L 2006 IEEE Trans. Image Process 15 3385
[30]	Bhuiyanr M, Ahmad M, Swamy M 2007 IEEE Trans. Geosci. Remote Sensing 17 500
[31]
[32]
[33]	Bianchi T, Argenti F, Alparone L 2008 IEEE Trans. Geosci. Remote Sensing 46 2728
[34]
[35]	Argenti F, Bianchi T, Lapini A, Alparone L 2012 IEEE Geosci. Remote Sensing Lett. 9 13
[36]	Chang X, Jiao L C, Liu F, Sha Y H 2010 Acta Electron. Sin. 38 1 (in Chinese)[常霞, 焦李成, 刘芳, 沙宇恒 2010 电子学报 38 1]
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[42]
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