Image Restoration by Iterative Denoising and Backward Projections
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Inverse problems appear in many applications such as image deblurring and inpainting. The common approach to address them is to design a specific algorithm for each problem. The Plug-and-Play (P&P) framework, which has been recently introduced, allows solving general inverse problems by leveraging the impressive capabilities of existing denoising algorithms. While this fresh strategy has found many applications, a burdensome parameter tuning is often required in order to obtain high-quality results. In this work, we propose an alternative method for solving inverse problems using denoising algorithms, that requires less parameter tuning. We provide theoretical analysis of the method, and empirically demonstrate that it is competitive with task-specific techniques and the P&P approach for image inpainting and deblurring.
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