A sure approach for image deconvolution in an orthonormal wavelet basis
Amel Benazza‐Benyahia, Jean‐Christophe Pesquet · 2008
In this paper, we are interested in restoring blurred images corrupted by an additive Gaussian noise. The originality of the proposed approach is two-fold. Firstly, we formulate the restoration problem as the minimization of a criterion derived from Stein's unbiased risk estimate. Secondly, the deconvolution procedure is performed using any analysis and synthesis function families, that can be redundant or not. Simulations carried out on satellite images indicate the good performance of our method in the case of orthonormal wavelet decompositions.