Texture Enhancement for Medical Images Based on Fractional Differential Masks

Texture enhancement for medical images is the most important technique in medical image diagnosis. This paper introduces a texture enhancement technique for medical images by using fractional differential (FD) masks based on Srivastava-Owa fractional operators. We also construct a 2D isotropic gradient mask based on generalized fractional operators. Texture enhancement performance is measured by applying experiments according to visual perception and by using Sobel/Canny edge filters and gray-level co-occurrence matrix. We discuss the capability of the FD mask for texture enhancement. The experiments and analysis show that the operator can extract subtle information and make the edges prominent