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基于局部平移瑞利分布模型的SAR图像相干斑抑制
引用本文:凤宏晓,焦李成,侯彪.基于局部平移瑞利分布模型的SAR图像相干斑抑制[J].电子与信息学报,2010,32(4):925-931.
作者姓名:凤宏晓  焦李成  侯彪
作者单位:西安电子科技大学智能信息处理研究所及智能感知与图像理解教育部重点实验室,西安,710071
基金项目:国家自然科学基金(60672126,60673097,60702062);;国家863计划项目(2007AA12Z136,2009AA12Z210);;科技部“973计划”重点项目(2006CB705707)资助课题
摘    要:该文提出了一种基于平稳小波域统计模型的SAR图像抑斑算法。首先对SAR图像应用非对数加性模型,接着针对该模型中的噪声在空域提出一种统计分布模型局部平移瑞利分布模型。最后基于该分布,在平稳小波域应用最大后验(MAP)方法获得真实信号平稳小波系数的解。实验表明,该文提出的局部平移瑞利分布模型是有效的,同时也表明该文给出的一种基于此分布模型的抑斑算法有很强的鲁棒性,抑斑性能优于许多现存的算法。

关 键 词:SAR图像抑斑  局部平移瑞利分布  非对数加性模型  平稳小波变换  最大后验
收稿时间:2009-4-10
修稿时间:2009-9-28

SAR Image Despeckling Based on Local Translation-Rayleigh Distribution Model
Feng Hong-xiao,Jiao Li-cheng,Hou Biao.SAR Image Despeckling Based on Local Translation-Rayleigh Distribution Model[J].Journal of Electronics & Information Technology,2010,32(4):925-931.
Authors:Feng Hong-xiao  Jiao Li-cheng  Hou Biao
Affiliation:Institute of Intelligent Information Processing and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, Xidian University, Xi'an 710071, China
Abstract:Based on the statistical model in stationary wavelet domain, an algorithm of SAR image despeckling is developed. Firstly, nonlogarithmic additive model is applied to SAR image, and then a statistical distribution—Local Translation-Rayleigh Distribution Model (LTRDM) is proposed for the noise within nonlogarithmic additive model in the image domain. Finally, based on this model and in the stationary wavelet domain, the solution of real signal coefficients are given by using Maximum A Posteriori(MAP). Experiments show that local translation-Rayleigh distribution model is effective, and also indicate that a despeckling algorithm based on LTRDM proposed in this paper is robust, and possess high performance over many traditional algorithms.
Keywords:SAR image despeckling  Local translation-Rayleigh distribution model  Nonlogarithmic additive model  Stationary wavelet transform  Maximum A Posteriori (MAP)
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