基于稀疏表示的Shearlet域SAR图像去噪  

Shearlet Domain SAR Image De-noising via Sparse Representation

作　　者：刘帅奇[1] 胡绍海[1] 肖扬[1] 

机构地区：[1]北京交通大学信息所,北京100044

出　　处：《电子与信息学报》2012年第9期2110-2115,共6页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(60572093);北京市自然科学基金(4102050);教育部博士点基金(20050004016);航空科学基金(201120M5007)资助课题

摘　　要：该文通过分析SAR图像的噪声成因以及其斑点噪声模型,结合图像的稀疏表示理论提出一种基于稀疏表示的Shearlet域SAR图像去噪算法。算法从整体上对SAR图像进行去噪:首先对SAR图像进行Shearlet变换,然后利用稀疏表示模型构造出去噪的最优化模型,在此基础上进行迭代去噪,然后重构SAR图像得到去噪后的图像。实验结果表明:该文所提出的算法不仅可以显著去除相干斑噪声,提高去噪图像的峰值信噪比(Peak Signal toNoise Ratio,PSNR),还明显地改善了图像的视觉效果,更好地保留了图像纹理信息。After analyzing the causes of SAR image noise and speckle model, a SAR image de-noising method is presented in Shearlet domain from the theory of image sparse representation. The proposed algorithm is to de-noise SAR image from the entire image information： firstly, Shearlet transform is applied to the noise SAR image, then, the de-noised Shearlet coefficients are got based on iterative de-noising algorithm from noise optimization model which constructed by the model of sparse representation of the SAR image, finally, the clean SAR image is obtained from the de-nosing Shearlet coefficients. The experimental results show that the proposed algorithm can suppress speckle and improve the PSNR of de-noised image significantly, as well as improve visual effect of the image and retain the image texture information better.

关 键 词：合成孔径雷达 图像去噪 稀疏表示 Shearlet去噪 共轭梯度法 

分 类 号：TN957.52[电子电信—信号与信息处理]