Difference based median filter for removal of random value impulse noise in images

Random value impulse noise of images has many sources, such as image sensor, electronic components, etc. How to removal of noise and restore degraded image is always an interesting problem. The decision based algorithms as efficient methods to suppress noise have been extensively studied for a long time. In this type of algorithms, the first step is to classify the corrupted pixels from the surroundings, but it is not an easy thing since each image is different. The efficiency of the classification has great influence on the overall performances of the algorithms. A difference based median filter which can efficiently locate the random value impulse noise is proposed in this paper. Based on this filter, a new algorithm for removal of impulse noise in images is designed. A comparison of the performances is made among several existing algorithms in term of Image Enhancement Factor, Peak Signal-to-Noise Ratio and Structure Similarity Index. Finally, the proposed method is used for underwater image processing to suppress the random value impulse noise modified by Histogram Equalization operation. Visual and quantitative results indicate that the proposed method outperforms most of algorithms for removal of impulse noise in literatures.