基于自适应窗和形状自适应小波变换的SAR图像相干斑抑制
Received:January 09, 2009  Revised:January 09, 2009  点此下载全文
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Author NameAffiliationE-mail
fenghongxiao Institute of Intelligent Information Processing and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education fenghongxiao1008@yahoo.com.cn 
基金项目:国家重点基础研究发展计划(973计划),国家高技术研究发展计划(863计划),国家自然科学基金项目(面上项目,重点项目,重大项目)
中文摘要:结合SAR图像空域的先验知识和小波域系数的特性,本文提出了一种新的SAR图像相干斑抑制算法:使用最近提出的局部多项式近似-置信区间交叉(Local Polynomial Approximation-Intersection of Confidence Intervals: LPA-ICI)构造自适应窗,寻找到与SAR图像中每个像素点相对应的同质区域,在每个同质区域内利用本文给出的快速形状自适应小波变换进行硬阈值收缩抑斑,最后根据本文提出的稀疏加权方法融合多个估计样本获得最终抑斑图像。实验结果表明本文提出的算法有着很好的抑斑性能,尤其是重构图像无“振铃”效应并有效的保留了原始SAR图像中的点目标。
中文关键词:SAR图像相干斑抑制 自适应窗 形状自适应小波变换 局部多项式近似-置信区间交叉 基于稀疏性的权值
 
SAR IMAGE DESPECKLING BASED ON ADAPTIVE WINDOW AND SHAPE ADAPTIVE - DISCRETE WAVELET TRANSFORM
Abstract:Considering the prior knowledge of SAR image in spatial domain and the property of coefficients in wavelet domain, this paper presents a novel algorithm of SAR image despeckling: constructing an adaptive window and finding a uniform region for every pixel of SAR image by using Local Polynomial Approximation-Intersection of Confidence Intervals (LPA-ICI), implementing hard-threshold shrinkage with fast shape adaptive discrete wavelet transform proposed in this paper. At last, many despeckled samples are fused into a final despeckled SAR image according to the sparsity of regions, which is presented in this paper. Experiments show that the algorithm proposed in this paper has advanced despeckled performance. Especially, reconstructed image is absent from unpleasant ringing artifacts, and efficiently reserves point targets of original SAR image.
keywords:SAR image despeckling, adaptive window, SA-DWT, Local Polynomial Approximation- Intersection of Confidence Intervals, weighting according to sparsity
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Copyright:《Journal of Infrared And Millimeter Waves》