A Fuzzy Approach to Detect and Reduce Impulse Noise -A Review.

Image restoration is an important branch of image processing, which deals with the reconstruction of images by removing noise and blurriness , and making them suitable for human perception.In this paper we describe a new algorithm that is especially developed for reducing all kinds of impulse noise: FIDRM (Fuzzy Impulse noise Detection and Reduction Method). It can also be applied to images having a mixture of impulse noise and other types of noise. The result is an image with very little or no impulse noise so that other filters can be used afterwards. Here nonlinear filtering technique is applied usingtwo steps: an impulse noise detection step and a reduction step that preserves edge sharpness. A fuzzy set impulse noise is constructed by our detection method based on the concept of fuzzy gradient values.After that the filtering method (which is a fuzzy averaging of neighbouring pixels ) will use this fuzzy set represented by a membership functions.Basedon the criteria of peak-signal-to-noise-ratio (PSNR) and subjective evaluations we have found experimentally, that the proposedmethod provides a significant improvement on other state-of-the-art methods. FIDRM is not only very fast but also very effective for reducing little as well as very high impulse noise.