基于对偶树复数小波变换的邻域自适应的图像降噪
doi: 10.3724/SP.J.1146.2008.00469
Neighborhood Adaptive Image Denoising Using Dual-Tree Complex Wavelet Transform
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摘要: 该文提出一种新的基于对偶树复数小波变换的邻域自适应的图像降噪方法，它是现存的NeighShrink降噪方法的改进。该文运用Stein的无偏风险估计，在小波域每一个子带为NeighShrink方法确定一个最优的阈值和邻域窗口，并将NeighShrink方法从正交的小波变换推广到对偶树复数小波变换。实验结果证实，该文方法比当前基于小波的最具竞争力的图像降噪方法取得了更好的降噪效果。Abstract: In this paper, a new neighborhood adaptive image denoising method is proposed using dual-tree complex wavelet transforms. It is an improvement of the existing denoising method NeighShrink. The optimal thresholds and neighboring window sizes are determined for every subband in the wavelet domain using Steins unbiased risk estimate, and NeighShrink is also extended from orthogonal wavelet transforms to dual-tree complex wavelet transforms in this paper. Experimental results show that the proposed method performs?better than some of the existing methods.
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