A Fuzzy Based Approach for Image Restoration

Removing and reducing impulse noise is very active research area in image processing. Present day applications require various kinds of images and pictures as sources of information for interpretation and analysis. Whenever an image is converted from one form to another, some form of degradation occurs at the output. The output image has to undergo a process called image enhancement. An effective method for image enhancement was presented by Russo, which was controlled by tuning of one parameter. In this paper, a filter is introduced which will remove the noise and improve the contrast of the image. The objective of image restoration is to reconstruct the image from degraded one resulted from system errors and noises and so on. There are two ways to achieve such an objective. One is to model the corrupted image degraded by motion, system distortion, and additive noises, whose statistic models are known. And the inverse process may be applied to restore the degraded images. Another is called image enhancement, that is, constructing digital filters to remove noises to restore the corrupted images resulted from noises.