A Scale-based Forward-and-Backward Diffusion Process for Adaptive Image Enhancement and Denoising
 
A Scale-based Forward-and-Backward Diffusion Process for Adaptive Image Enhancement and Denoising 
 
Yi Wang, Ruiqing Niu, Liangpei Zhang, Ke Wu, Hichem Sahli
 
Abstract 

This work presents a scale-based forward-and-backward diffusion (SFABD) scheme. The main idea of this scheme is to perform local adaptive diffusion using local scale information. To this end, we propose a diffusivity function based on the Minimum Reliable Scale (MRS) of Elder and Zucker [1] to detect the details of local structures. The magnitude of the diffusion coefficient at each pixel is determined by taking into account the local property of the image through the scales. A scale-based variable weight is incorporated into the diffusivity function for balancing the forward and backward diffusion. Furthermore, as numerical scheme, we propose a modification of the Perona-Malik scheme [2] by incorporating edge orientations. The paper describes the main principles of our method and illustrates image enhancement results on a set of standard images as well as simulated medical images, together with qualitative and quantitative comparisons with a variety of anisotropic diffusion schemes.