IMPULSE NOISE REMOVAL USING FCM ALGORITHM

Abstract

Image noise removal is an important aspect of image processing. Impulse noise is one such noise, which is frequently introduced into images while transmitting and acquiring them over an unsecure communication channel. Satellite or TV images can be corrupted by atmospheric disturbances. In other applications noise can be introduced by strong electromagnetic fields, transmission errors, etc. Human visual system is very sensitive to the high amplitude of noise signals, thus noise in an image can result in a subjective loss of information. Various techniques have been introduced for the removal of impulse noise based on the properties of their respective noise models. Performance of some recent filters is evaluated and compared to that of the proposed filter. This study introduces an iterative filter for images highly corrupted with impulse noise, typically in the range 30-80%. It is a novel technique for detecting high density impulse noise and preserves more image details in high noise environment. The application of Fuzzy C-means (FCM) algorithm in the detection phase provides optimal results. By extensive simulation results and comparison with other filters, it is observed that the proposed algorithm outperforms several methods.