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Image deconvolution is still to be a challenging ill-posed problem forrecovering a clear image from a given blurry image, when the point spreadfunction is known. Although competitive deconvolution methods are numericallyimpressive and approach theoretical limits, they are becoming more complex,making analysis, and implementation difficult. Furthermore, accurate estimationof the regularization parameter is not easy for successfully solving imagedeconvolution problems. In this paper, we develop an effective approach forimage restoration based on one explicit image filter - guided filter. Byapplying the decouple of denoising and deblurring techniques to thedeconvolution model, we reduce the optimization complexity and achieve a simplebut effective algorithm to automatically compute the parameter in eachiteration, which is based on Morozov's discrepancy principle. Experimentalresults demonstrate that the proposed algorithm outperforms manystate-of-the-art deconvolution methods in terms of both ISNR and visualquality.

An Adaptive Parameter Estimation for Guided Filter based Image Deconvolution