AIG Based Nonlinear Anisotropic Smoothing Strategy for Vector-Valued Images

The effects of the Rician noise on the calculated tensors are analyzed and an affine invariant gradient （AIG） based nonlinear anisotropic smoothing strategy is presented. The AIG based smoothing strategy is a development of the affine invariant nonlinear anisotropic diffusion （AINAD） restoration mod...

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Bibliographic Details
Published in:Shanghai jiao tong da xue xue bao 2009-04, Vol.14 (2), p.223-228
Main Author: 张相芬 田蔚风 陈武凡 叶宏
Format: Article
Language:English
Subjects:
Architecture
Computer Science
Electrical Engineering
Engineering
Life Sciences
Materials Science
仿射不变量
信号噪声比
各向异性扩散
向量值
国际
平滑
美国
非线性
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Summary:The effects of the Rician noise on the calculated tensors are analyzed and an affine invariant gradient （AIG） based nonlinear anisotropic smoothing strategy is presented. The AIG based smoothing strategy is a development of the affine invariant nonlinear anisotropic diffusion （AINAD） restoration model, introduced by Guillermo Sapiro, and adopted to restore vector-valued data. To evaluate the efficiency of the presented AINAD model in accounting for the Rician noise introduced into the vector-valued data, the peak-to-peak signal-to-noise ratio （PSNR）, signal-to-mean squared error ratio （SMSE） and Beta（parameter that stands for edge preservation） metrics are used. The experiment results acquired from the synthetic and real data prove the good performance of the presented filter.
ISSN:1007-1172
1995-8188
DOI:10.1007/s12204-009-0223-z