Estimation of Motion Blur Based on Combination of PSO and GA

Abstract: In Digital Image processing image restoration is the process of reconstructing or deblurring an image which has been affected of various unwanted factors or noise. In this paper, we propose a method for image deblurring technique based on combination of PSO and GA. The main drawbacks in a digital image is the presence of noise and degradation during the camera shake by human error, long exposure time, the movement of an object, and not focus the target. Image restoration is very important and necessary in digital image process avoiding the blur and get original Image. We derive a blurring function, namely point spread function (PSF) which deblur the captured image by reversing the motion effect. It aims to incorporate the advantages of the two methods, where the PSO is effective in localizing the global region, is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality and the Genetic algorithm is effective in converging optimization and search problems. Image restoration is a technique which is used to make picture sharp and useful by using mathematical models of different Algorithms.

Keywords: Image deblur, blur, PSF, degradation model, motion blur, blind deconvalution.