Coherence-enhancing diffusion of colour images

被引:180
作者
Weickert, J [1 ]
机构
[1] Univ Copenhagen, Dept Comp Sci, DK-2100 Copenhagen, Denmark
关键词
image processing; flow-like structures; structure tensor; nonlinear diffusion; scale-space; vector-valued images;
D O I
10.1016/S0262-8856(98)00102-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Many image processing problems require the enhancement of coherent flow-like structures. This can be accomplished in a natural way by combining anisotropic diffusion filtering and texture analysis by means of the structure tensor (second-moment matrix, interest operator). In this paper an extension of these ideas to vector-valued images is presented. A structure tensor for vector-valued images is constructed as the mean of the structure tensors of each channel. This idea generalizes Di Zenzo's gradient for colour images by introducing an additional integration scale. The common structure tensor is used for steering the diffusion processes in each channel. The additional integration scale turns out to be crucial for orientation smoothing and it leads to significantly improved filter results. After analysing the role of all filter parameters, examples from different application areas are presented, and it is demonstrated that this type of diffusion filtering is highly robust under additive Gaussian noise. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:201 / 212
页数:12
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