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An Adaptive Pointwise P-norm Regularization for Image Deconvolution

We propose a pointwise P-Norm based nonparametric image deconvolution method. In our algorithm, a pointwise p-norm based regular term is used to deal with the different types of regions in a blurry image such as edges, texture and smooth areas. A new hyper-parameter updating method is also adopted to improve the effectiveness and robustness of the proposed algorithm. The experimental results show that the quality of our restored images can outperform the results derived by other algorithms. In addition, our algorithm has a wide adaptation to different blur kernels.