计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 183-187.doi: 10.11896/j.issn.1002-137X.2017.6A.042

• 模式识别与图像处理 • 上一篇    下一篇

基于非局部相似和低秩矩阵逼近的SAR图像去噪

赵杰,王配配,门国尊   

  1. 河北大学电子信息工程学院 保定071000;河北省机器视觉工程技术研究中心 保定071000,河北大学电子信息工程学院 保定071000;河北省机器视觉工程技术研究中心 保定071000,河北大学经济学院 保定071000
  • 出版日期:2017-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(61572063,61401308),河北省自然科学基金(F2016201187),河北大学自然科学研究计划项目(2014-303),河北大学研究生创新资助

SAR Image Denosing Based on Nonlocal Similarity and Low Rank Matrix Approximation

ZHAO Jie, WANG Pei-pei and MEN Guo-zun   

  • Online:2017-12-01 Published:2018-12-01

摘要: 针对合成孔径雷达图像(Synthetic Aperture Radar,SAR)受斑点噪声影响的问题,提出了一种改进的基于非局部相似和低秩矩阵逼近的SAR图像去噪方法。首先对SAR图像进行对数变换,将图像的相干乘性噪声转化为加性噪声,然后预估计图像的全局噪声方差,利用非局部相似性引入一种新的基于欧氏距离和判定系数的联合块匹配方式,在低秩模型下采用改进残余噪声方差估计的加权核范数最小化算法(Weighted Nuclear Norm Minimization,WNNM)逼近低秩矩阵,最终实现SAR图像的噪声抑制。实验结果表明,该方法不仅使得峰值信噪比等客观指标有了明显的改善,而且更好地保存了图像的局部结构,并实现了良好的主观视觉效果。

关键词: SAR图像去噪,联合块匹配,非局部相似性,加权核范数最小化

Abstract: The SAR image denoising based on nonlocal similarity and low rank matrix approximation was presented to minimize the effect of speckle noise in Synthetic aperture radar.Firstly,multiplicative speckle is changed into additive noise by logarithmic transformation.Secondly,the image’s global noise variance is estimated in advance.Thirdly,a new joint block matching method based on Euclidean distance and R-squared is developed,which makes the matching result more accurate.Finally,within the framework of the low rank model,the improved residual noise variance estimation is used to approximate the low rank matrix with the weighted nuclear norm minimization.The noise suppression of SAR image is achieved.The experimental results show that this method not only the peak signal to noise ratio objective indicators have significantly improved and preserved the local structure of the image better,and produces a good subjective visual effect.

Key words: SAR image denosing,Joint block matching,Non-local selfsimilarity,Weighted nuclear norm minimization

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