基于粗糙集和属性直方图的医学图像增强

medical image edge detect method based on granular computing. Integrality and uncertainty may occur in many different levels in the process of medical image because of the complication of image information. It is a crucial problem to partition an image into different sub-images when rough sets theory is applied in image enhancement. The improved histogram，a histogram bound by some prior knowledge，is used for partitioning an image into different sub-images，Furthermore，all image enhancement method based on rough sets and bound histogram is proposed．There are three steps in the method．First, the gray-level threshold is determined by Otsu algorithm based on bound histogram．Second，based on the indiscernible relation，according to the threshold，an image is partitioned into sub-images for background，object and noise. Noise pixels can be removed by median filtering. Third，the denoised sub-images of background and object are enhanced respectively and they are combined to form a final enhanced image．Regard lung tissue in the chest CT picture as the target area, experimental results show that the image is remarkably enhanced and the boundaries of a region of interest keep unchanged in shape.