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| Shearlet Domain SAR Image De-noising via Sparse Representation |
| Liu Shuai-qi Hu Shao-hai Xiao Yang |
| Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China |
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Abstract 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.
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Received: 29 February 2012
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Corresponding Authors:
Liu Shuai-qi
E-mail: shdkj-1918@163.com
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2012, Vol. 34 
