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An Eedge-Based Adaptive Morphology Algorithm for Image Nosie Reduction

In this paper an efficient morphologica algorithm for reducing gaussian and impulse noise in gray-scale image is presented. Based on the edge information the input image is partitioned into a flat region and an edge region, then different algorithms are selectively applied to each region. in case of impulse noise, MGR (morphologica grayscale reconstruction) algorithm with directional SE (structuring element) is applied to the flat region. For theedge region opening-closing (closing-opening) is used instead of dialation (erosion), so that the remaining noise around large objects can be removed. In case of gaussian noise, 5*5 OCCO(opening closing closing opening) and 3*3 DMF(directional morphological filter ) are used for the flat region and the edgeregion, respectively. In order to remove discontinuity at the edge boundary, the algorithm uses 3*3 OCCO around the edge region to reconstruct the final image. Experimetnal results have shown that the proposed algorithm achieves a high performance in terms of noise removal, detail preservation, and NMSE.