A Non-Local Algorithm for Image Denoising
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In this paper, we focus on the research of fast deconvolution algorithm based on the non-convex L"q(q=12,23) sparse regularization. Recently, we have deduced the closed-form thresholding formula for L"1"2 regularization model (Xu (2010) [1]). In this work, we further deduce the closed-form thresholding formula for the L"2"3 non-convex regularization problem. Based on the closed-form formulas for L"q(q=12,23) regularization, we propose a fast algorithm to solve the image deconvolution problem using half-quadratic splitting method. Extensive experiments for image deconvolution demonstrate that our algorithm has a significant acceleration over Krishnan et al.'s algorithm (Krishnan et al. (2009) [3]). Moreover, the simulated experiments further indicate that L"2"3 regularization is more effective than L"0,L"1"2 or L"1 regularization in image deconvolution, andL"1"2 regularization is competitive to L"1 regularization and better than L"0 regularization.