中北大学学报（自然科学版）2011，Vol.32Issue(4)：512-517,6.DOI:10.3969/j.issn.1673-3193.2011.04.024
基于分数阶导数的自适应各向异性扩散图像去噪模型
An Adaptive Image Denoising Model of Anisotropic Diffusion Based on Fractional Derivative
摘要
Abstract
As the traditional pure anisotropic diffusion model (1-order derivative used by the gradient) brings "staircase effect" by excessive diffusion in smooth regions, and the 4-order PDE (2-order derivative used by the Laplacian) model suffers poor denoising effect, an adaptive image denoising model of anisotropic diffusion based on fractional derivative was proposed. As a locally adaptive process, the proposed model adopts different regularization constraints in different parts of the image. Experimental results show that the new model not only efficiently remove noise, but also retain the edge and detail information. Better quality and visual effects of the image is achieved with this model.关键词
分数阶导数/偏微分方程/图像去噪/图像恢复Key words
fractional derivative/ partial differential equations / image denoising/ image restoration分类
信息技术与安全科学引用本文复制引用
杨迎春,桂志国,李化奇,李晓岩..基于分数阶导数的自适应各向异性扩散图像去噪模型[J].中北大学学报（自然科学版）,2011,32(4):512-517,6.基金项目
国家自然科学基金资助项目(61071192) （61071192）
