Sure-based motion blur estimation

Abstract

We propose a novel approach to estimate the parameters of motion blur (blur length and orientation) from an observed image. The estimation of the motion blur parameters is based on a novel criterion - the minimization of an unbiased estimate of a filtered MSE ("blur-SURE"). By finding the best Wiener filter for this criterion, we automatically find the blur parameters with high accuracy. We then use these parameters in a recent (non-blind) deblurring algorithm that we have proposed and that achieves the state-of-the art in deconvolution. The results obtained are quite competitive with other standard algorithms under various range of scenarios: high noise level, short blur length, etc.