A Comparative Approach for Analysis of Image Restoration using Image Deblurring Techniques

Abstract

Image restoration is a very important factor in high level image processing which deals with recovering of an original, cleared sharp image using a various algorithms and techniques. Certain time during image capturing process degradation i.e image degradation occurs. Image restoration is used to get the original sharp image from the corrupted data. This research paper is aim to provide a comparative overview of most useful fast restoration of degraded image .Different types of image deblurring techniques are Wiener Filter, Neural Network Approach, Iterative Richardson-Lucy Algorithm, Laplacian Sharpening Filter described. The strength and weakness of each approach are identified and applications are also described so that the best fast image deblurring technique is comparatively sorted out.