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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 被引量：4

SAR Image Despeckling Based on Local Translation-Rayleigh Distribution Model
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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。 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.
作者 凤宏晓 焦李成 侯彪
机构地区 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
出处 《电子与信息学报》 EI CSCD 北大核心 2010年第4期925-931,共7页 Journal of Electronics & Information Technology
基金 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
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 SAR image despeckling Local translation-Rayleigh distribution model Nonlogarithmic additive model Stationary wavelet transform Maximum A Posteriori （MAP）
分类号 TN957.52 [电子电信—信号与信息处理]
  • 相关文献

参考文献12

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共引文献10

同被引文献27

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引证文献4

二级引证文献19

电子与信息学报
2010年 第4期

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