Coefficient-Tracking Speckle Reducing Anisotropic Diffusion

被引:0
|
作者
Ibrahim, Walid [1 ]
El-Sakka, Mahmoud R. [1 ]
机构
[1] Univ Western Ontario, Dept Comp Sci, London, ON N6H 5B7, Canada
关键词
Anisotropic diffusion; diffusion filtering; edge detection; features preservation; instantaneous coefficient of variation; noise reduction; speckle noise; EDGE-DETECTION; IMAGES;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Speckle reducing anisotropic diffusion (SRAD) filter is introduced to significantly reduce speckle noise from images. Yet, SRAD suffers from the problems of ordinary diffusion filters, e.g., objects boundaries broadening and edges dislocation. This paper provides a more robust diffusion-filtering scheme, which is based on tracking the image main features across SRAD wale-space images. Coefficient-tracking SRAD (CSRAD) controls the amount of allowed diffusion based on the edges original location. CSRAD is tested on Berkley segmentation dataset. CSRAD results are Subjectively compared with those of SRAD in terms of edge localization, smoothing enhancement, and features preserving. Experimental results show that CSRAD significantly reduced the features distortion and edges dislocation effects. Consequently, the entire diffusion process is enhanced.
引用
收藏
页码:136 / 145
页数:10
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