An Image Denoising Method Based on Non-local Two-side Random Projection and Low Rank Approximation
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摘要: 该文提出一种基于非局部双边随机投影的低秩逼近图像去噪新方法。首先,对每个图像块通过非局部搜索寻找相似匹配块簇,然后对相似匹配块簇进行双边随机投影,用投影后的低秩结构恢复原图像。实验结果表明,所提方法比奇异值分解方法有较低的计算复杂度,比单边随机投影方法有较小的重构误差。特别是和3维块匹配方法相比,所提方法能保持相近的信噪比和较好的视觉质量。Abstract: A novel image denoising method is proposed by using non-local approximation of low-rank based on random projection. The cluster of similar patch for each pixel point is found by using methods of non-local searching, and then compute low-rank approximation of matrix corresponding to the cluster of similar patches using two-side random projection. Finally, the image noise is suppressed by using the Low rank structure. Results show that the proposed method have the low computation cost. Comparing with one-side random projection method, the proposed algorithm ensure lower reconstruction error, and comparing with the Block Method of 3-Dimension (BM3D) method, proposed method have appealing visual quality of images.
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