REMOVAL OF IMPULSE NOISE IN HIGHLY CORRUPTED DIGITAL IMAGES USING A RELAXATION ALGORITHM

A relaxation algorithm for removing impulse noise from highly corrupte d images is proposed, where a nonlinear probabilistic model is used to reduce the ambiguity of each pixel based on the contextual informatio n. Each pixel is given three labels which stand for ''positive corrupt ion,'' ''no corruption,'' and ''negative corruption.'' The initial pro babilities of a pixel whose gray level lies in the middle intensity ra nge of the whole image are simply given some fixed values. Those of a pixel whose gray level lies in the upper or lower part of the intensit y range are determined by its gray level and the difference with the m edian value in a 3x3 window. To display the image after each iteration , the gray level of a pixel with high no-corruption probability is set to its original value approximately, while the gray level of a pixel with high corruption probability will be replaced by the average value of its neighbor pixels with high no-corruption probabilities. Experim ental results show that this algorithm can effectively remove both pos itive and negative impulse noise with very high probability and is sup erior in performance to some other methods for highly corrupted images . (C) 1997 Society of Photo-Optical Instrumentation Engineers.