Spatial and Spectral Morphological Template Matching

Jonathan Weber 1, * Sébastien Lefèvre 2
* Auteur correspondant
1 QGAR - Querying Graphics through Analysis and Recognition
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
2 SEASIDE - SEarch, Analyze, Synthesize and Interact with Data Ecosystems
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, UBS - Université de Bretagne Sud
Abstract : Template matching is a very topical issue in a wide range of imaging applica- tions. Mathematical morphology offers the hit-or-miss transform, an operator which has been successfully applied for template matching in binary images. More recently, it has been extended to greyscale images and even to multi- variate images. Nevertheless, these extensions, despite being relevant from a theoretical point-of-view, might lack practical interest due to the inherent diffi- culty to set up correctly the transform and its parameters (e.g. the structuring functions). In this paper, we propose a new and more intuitive operator which allows for morphological template matching in multivariate images from both a spatial and spectral point of view. We illustrate the potential of this operator in the context of remote sensing.
Type de document :
Article dans une revue
Image and Vision Computing, Elsevier, 2012, 30 (12), pp.934-945. 〈10.1016/j.imavis.2012.07.002〉
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Soumis le : mercredi 5 décembre 2012 - 11:15:12
Dernière modification le : mardi 18 décembre 2018 - 16:38:34



Jonathan Weber, Sébastien Lefèvre. Spatial and Spectral Morphological Template Matching. Image and Vision Computing, Elsevier, 2012, 30 (12), pp.934-945. 〈10.1016/j.imavis.2012.07.002〉. 〈hal-00761281〉



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