基于稀疏表示的Shearlet域SAR图像去噪
doi: 10.3724/SP.J.1146.2012.00200
Shearlet Domain SAR Image De-noising via Sparse Representation
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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 to Noise 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。
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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
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.-
Key words:
- SAR /
- Image de-nosing /
- Sparse representation /
- Shearlet de-nosing /
- Conjugate gradient method
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