Texture enhancement for medical images based on fractional differential masks
HA Jalab, RW Ibrahim - Discrete dynamics in nature and …, 2013 - Wiley Online Library
HA Jalab, RW Ibrahim
Discrete dynamics in nature and society, 2013•Wiley Online LibraryTexture 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 …
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 …
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.
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