Spatial and Transform Domain Filtering Method for Image De-noising: A Review

Abstract

Present investigation reveals the quantum of work carried in the filtering methods for image de-noising. An image is often gets corrupted by various noises that are visible or invisible while being gathered, coded, acquired and transmitted. Noise influences various process parameters that may cause a quality problem for further image processing. De-noising of natural images is appears to be very simp le however when considered under practical situations becomes complex. It has been cited by various author that parameter such as type and quantum of noise, image etc. through single algorith m or approach becomes cumbersome when results are optimized. In order to improve the quality of an image noise must be removed when the image is pre-p rocessed and the important signal features like edge details should be retained as much as possible. The search on efficient image de-noising methods is still a valid challenge at the crossing of functional analysis and statistics. This paper reviews significant de-noising methods (spatial and transform domain method) and their salient features and applications. One filter in each category has been taken in consideration to understand the characteristics of both spatial and transform do main filters.