Image restoration with group sparse representation and low‐rank group residual learning
Zhaoyuan Cai,
Xianghua Xie,
Jingjing Deng
et al.
Abstract:Image restoration, as a fundamental research topic of image processing, is to reconstruct the original image from degraded signal using the prior knowledge of image. Group sparse representation (GSR) is powerful for image restoration; it however often leads to undesirable sparse solutions in practice. In order to improve the quality of image restoration based on GSR, the sparsity residual model expects the representation learned from degraded images to be as close as possible to the true representation. In thi… Show more
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