Scale-based image enhancement using modified anisotropic diffusion filter

We propose a scale-based image enhancement method using a modified anisotropic diffusion filter that employs sensor noise estimation and scale space methods based on a minimum reliable scale. Based on the relationship between the local gradient and the critical value function, an image is classified into various scales representing the region's complexity. The degree of enhancement is then adjusted according to each region's complexity. When compared to the existing linear unsharp masking, adaptive unsharp masking, and warping-based methods, the proposed algorithm produces negligible noise amplification in homogeneous regions and superior edge enhancement.