Adaptive fractional differential approach and its application to medical image enhancement

This paper presents a new medical image enhancement method that adjusts the fractional order according to the dynamic gradient feature of the entire image. The presented method can extract the edges of an image accurately and enhance them while preserving smooth areas and weak textures; these improvements can be particularly helpful to doctors' diagnoses. The primary contribution of this paper is the Adaptive Fractional Differential Algorithm (AFDA), which uses the improved Otsu algorithm to segment the edges, textures and smooth areas of images. This algorithm allows the optimal fractional order of each pixel to be obtained using an adaptive fractional differential function constructed based on the area feature of image. As a result, the image can be enhanced adaptively. Experimental results show that for medical images, AFDA shows better image enhancement than other methods by making edges clearer and textures richer. (C) 2015 Elsevier Ltd. All rights reserved.