Review of Image Degradation and Restoration process (KEY IJP************624)

• Imran Syed

Abstract

Image restoration is the process of recovering an image that has been degraded by noise, blur, or other distortions. It is a crucial step in many image processing applications, such as medical imaging, remote sensing, security, and digital forensics. However, choosing the appropriate image restoration technique for different applications and domains is not a trivial task. It depends on several factors, such as the type and level of degradation, the prior knowledge about the image, the desired output quality, and the computational resources available. In this article, we will explore some of the common image restoration techniques and how to select them based on these factors. As in image enhancement, the principal goal of restoration techniques is to improve an image in some predefined sense. Although there are areas of overlap, image enhancement is largely a subjective process, while image restoration is for the most part an objective process. Restoration attempts to recover an image that has been degraded by using a priori knowledge of the degradation phenomenon. Thus restoration techniques are oriented toward modelling the degradation and applying the inverse process in order to recover the original image. This approach usually involves formulating a criterion of goodness that will yield an optimal estimate of the desired result. By contrast, enhancement techniques basically are heuristic procedures designed to manipulate an image in order to take advantage of the psychophysical aspects of the human visual system. For example, contrast stretching is considered an enhancement technique because it is based primarily on the pleasing aspects it might present to the viewer, whereas removal of image blur by applying a deblurring function is considered a restoration technique.