Mathematical morphology on directional data

被引：0

作者：

Hauch, Konstantin ^{[1
]}

Redenbach, Claudia ^{[1
]}

机构：

[1] Tech Univ Kaiserslautern, Dept Math, Kaiserslautern, Germany

来源：

2022 25TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION 2022) | 2022年

关键词：

depth function; mu CT imaging; image processing; filtering; glass foam; DATA DEPTH; OPERATORS;

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：

We define morphological operators and filters for directional images whose pixel values are vectors on the unit sphere. 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 example, we enhance the fault region in a compressed glass foam.

引用

页数：7

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