Motion blur parameters estimation for image restoration

摘要

This paper deals with estimation of parameters for motion blurred images. The objectives are to estimatethe length (L) and the blur angle (θ) of the given degraded image as accurately as possible so that the restoration performance can be optimised. Gabor filter is utilized to estimate the blur angle whereas a trained radial basis function neural network (RBFNN) estimates the blur length. Once these parametersare estimated the conventional restoration is performed. To validate the proposed scheme, simulationhas been carried out on standard images as well as in real images subjected to different blur angles and lengths. The robustness of the scheme is also validated in noise situations of different strengths. In all situations, the results have been compared with standard schemes. It is in general observed that the proposed scheme outperforms its counterparts in terms of restoration parameters and visual quality.