Characterization of Graph-Based Hierarchical Watersheds: Theory and Algorithms

Watershed is a well-established clustering and segmentation method. In this article, we aim to achieve a better theoretical understanding of the hierarchical version of the watershed operator. More precisely, we propose a characterization of hierarchical watersheds in the framework of edge-weighted...

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Bibliographic Details
Published inJournal of mathematical imaging and vision Vol. 62; no. 5; pp. 627 - 658
Main Authors Santana Maia, Deise, Cousty, Jean, Najman, Laurent, Perret, Benjamin
Format Journal Article
LanguageEnglish
Published New York Springer US 01.06.2020
Springer Nature B.V
Springer Verlag
SeriesSpecial Issue on Discrete Geometry for Computer Imagery 2019
Subjects
Algorithms
Applications of Mathematics
Clustering
Computer Science
Image Processing
Image Processing and Computer Vision
Mathematical Methods in Physics
Segmentation
Signal,Image and Speech Processing
Special Issue on Discrete Geometry for Computer Imagery 2019
Watersheds
Binary partition hierarchy
Hierarchical watersheds on edge-weighted graphs
Recognition of hierarchical watersheds
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Summary:Watershed is a well-established clustering and segmentation method. In this article, we aim to achieve a better theoretical understanding of the hierarchical version of the watershed operator. More precisely, we propose a characterization of hierarchical watersheds in the framework of edge-weighted graphs. The proposed characterization leads to an efficient algorithm to recognize hierarchical watersheds.
ISSN:0924-9907
1573-7683
DOI:10.1007/s10851-019-00936-6