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Double weighted Schatten-\(p\) norm minimization for real color image denoising. (Chinese. English summary) Zbl 1474.94019

Summary: Compared with gray image denoising, color image denoising is more difficult, which is one of the research hotspots. Aiming at the problem of color image denoising, a color image denoising algorithm based on double weighted Schatten-\(p\) norm minimization is proposed. Firstly, the \(R\), \(G\) and \(B\) channels are divided into blocks, and the block matrix is connected to make use of channel redundancy. Then, according to the different noise statistics in each channel, the weighted matrix is introduced to balance the data fidelity. Using the weighted Schatten-\(p\) norm as the low rank penalty term, an optimization problem with equality constraints is constructed. The alternating multiplier direction method is used to solve the problem. Each iteration update step has a closed form solution to ensure the convergence of the final result. Experimental results show that the proposed algorithm has better performance under the same conditions compared with the latest denoising algorithm.

MSC:

94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
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