Mathematical Morphology on Directional Data

被引：0
|
作者：
Hauch, Konstantin [1 ]
Redenbach, Claudia [1 ]
机构：
[1] RPTU Kaiserslautern Landau, Dept Math, Gottlieb-Daimler-Str, D-67663 Kaiserslautern, Germany
来源：
JOURNAL OF MATHEMATICAL IMAGING AND VISION | 2024年 / 66卷 / 06期
关键词：
Depth function; mu CT imaging; Image processing; Filtering; Glass foam; Glass fibre reinforced polymer; DATA DEPTH; OPERATORS;
D O I：
10.1007/s10851-024-01210-0
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We define morphological operators and filters for directional images whose pixel values are unit vectors. This requires an ordering relation for unit vectors which is obtained by using depth functions. They provide a centre-outward ordering with respect to a specified centre vector. We apply our operators on synthetic directional images and compare them with classical morphological operators for grey-scale images. As application examples, we enhance the fault region in a compressed glass foam and segment misaligned fibre regions of glass fibre-reinforced polymers.
引用
收藏
页码：1019 / 1032
页数：14
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