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We propose a new image denoising algorithm by incorporating the $L_1$-regularization technique and the least squares method. In order to improve the quality of the reconstructed images, we adopt a high order least squares method along with new iterative nonlocal weights. In particular, we devise a measurement to estimate the nonlocal similarities between patches by using both data values and their derivatives. Some experimental results are presented to demonstrate the capability of the proposed algorithm.
This presentation is part of Contributed Presentation “CP7 - Contributed session 7”