AI RESEARCH
Framelet-Based Blind Image Restoration with Minimax Concave Regularization
arXiv CS.CV
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ArXi:2604.19314v1 Announce Type: new Recovering corrupted images is one of the most challenging problems in image processing. Among various restoration tasks, blind image deblurring has been extensively studied due to its practical importance and inherent difficulty. In this problem, both the point spread function (PSF) and the underlying latent sharp image must be estimated simultaneously. This problem cannot be solved directly due to its ill-posed nature. One powerful tool for solving such problems is total variation (TV) regularization.