A Scale-based Forward-and-Backward Diffusion Process for Adaptive Image Enhancement and Denoising This publication appears in: EURASIP Journal on Advances in Signal Processing Authors: Y. Wang, R. Niu, L. Zhang, K. Wu and H. Sahli Number of Pages: 12 Publication Year: 2011
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.
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