REVIEW PAPER ON IMAGE RESTORATION USING STATISTICAL MODELING

Abstract

There are various applications of image restoration in today’s world. Image restoration is an important process in the field of image processing. It is a process to recover original image from distorted image. Image restoration is a task to improve the quality of image via estimating the amount of noises and blur involved in the image. To restore image it’s too important to know a prior knowledge about an image i.e. the knowledge about how an image was degraded or distorted. It is must to find out that which type of noise is added in an image and how image gets blurred. So the prior knowledge about an image is a one of the important part in image restoration. Image gets degraded due to different conditions such as atmospheric conditions and environmental conditions, so it is required to restore the original image by using different image restoration algorithms. There are varieties of reasons that are responsible for noise generation in an image and different blur models are responsible for generation of blur image. So it’s necessary to remove such noise from an image and remove blur model by using different deblurring techniques to improve it’s quality for visual appearance. The restoration of degraded images can be applied in many application areas that are needed to restore it for further processing. Application area varies from restoration of old images in museum, image coding and decoding, medical imaging, photography, and image acquisition and restoration. So this paper proposes image restoration method by using joint statistical modeling. This paper gives a review of different image restoration techniques used.