Abstract
This work addresses the problem of blind image deblurring, having one or more observations of the original image obtained through unknown linear channels and corrupted by additive noise. We resort to an iterative algorithm, belonging to the class of Bussgang algorithms, based on alternating a linear and a nonlinear image estimation stage. Specifically a novel nonlinear processing is performed on the Radon Transform of the image edges. The effect of the nonlinear processing is to thin the blurred image edges, and to drive the overall blind restoration algorithm to a focused image. The performance of the algorithm are assessed by experimental results pertaining to restoration of blurred natural images.
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