Algorithm of global mean and standard deviation for motion blur parameters identification

The estimation of parameters for motion blurred images is dealed with. The objectives are to estimate the length and the blur angle of the given degraded image as accurately as possible so that the restoration performance can be optimized. An algorithm of global mean and standard deviation for motion blur parameters identification is proposed. Radon transform is utilized to estimate the blur angle where as a trained the pixel coordinates estimates the blur length. Once these parameters are estimated the conventional restoration is performed. To validate the proposed scheme, simulation has been carried out on standard images as well as in real images subjected to different blur lengths. In all situations, the results have been compared with standard schemes. It is in general observed that the proposed scheme out performs its counterparts in terms of restoration parameters and visual quality.