2023
DOI: 10.3390/app13127184
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An Unsupervised Image Denoising Method Using a Nonconvex Low-Rank Model with TV Regularization

Abstract: In real-world scenarios, images may be affected by additional noise during compression and transmission, which interferes with postprocessing such as image segmentation and feature extraction. Image noise can also be induced by environmental variables and imperfections in the imaging equipment. Robust principal component analysis (RPCA), one of the traditional approaches for denoising images, suffers from a failure to efficiently use the background’s low-rank prior information, which lowers its effectiveness u… Show more

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