A feature-dependent fuzzy bidirectional flow for adaptive image sharpening

被引:22
作者
Fu, Shujun [1 ]
Ruan, Qiuqi
Wang, Wenqia
Gao, Fuzheng
Cheng, Heng-Da
机构
[1] Shandong Univ, Sch Math & Syst Sci, Jinan 250100, Peoples R China
[2] Beijing Jiaotong Univ, Inst Sci Informat, Beijing 100044, Peoples R China
[3] Utah State Univ, Dept Comp Sci, Logan, UT 84322 USA
关键词
anisotropic diffusion; bidirectional flow; edge sharpening; fuzzy set; image sharpening; shock filter;
D O I
10.1016/j.neucom.2006.10.035
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a fuzzy bidirectional flow framework based on generalized fuzzy set is presented to sharpen image by reducing its edge width, which performs a fuzzy backward (inverse) diffusion along the gradient direction to the isophote line (edge), while does a certain forward diffusion along the tangent direction on the contrary. Gaussian smoothing to the second normal derivative of an image is used to decide its zero-crossing, which results in a robust sharpening process against noise. Controlled by the image gradient magnitude, the fuzzy membership function guarantees a natural transition across different areas. To preserve image features, the nonlinear diffusion coefficients are locally adjusted according to the directional derivatives of the image. Experiments on real images demonstrate that the algorithm substantially improves the visual quality of the enhanced image over some relevant equations. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:883 / 895
页数:13
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