Global-local optimizations by hierarchical cuts and climbing energies - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Pattern Recognition Letters Année : 2014

Global-local optimizations by hierarchical cuts and climbing energies

Résumé

Hierarchical segmentation is a multi-scale analysis of an image and provides a series of simplifying nested partitions. Such a hierarchy is rarely an end by itself and requires external criteria or heuristics to solve problems of image segmentation, texture extraction and semantic image labelling. In this theoretical paper we introduce a novel framework: hierarchical cuts, to formulate optimization problems on hierarchies of segmentations. Second we provide the three important notions of h-increasing, singular, and scale increasing energies, necessary to solve the global combinatorial optimization problem of partition selection and which results in linear time dynamic programs. Common families of such energies are summarized, and also a method to generate new ones is described. Finally we demonstrate the application of this framework on problems of image segmentation and texture enhancement.
Fichier principal
Vignette du fichier
GlobalLocal_Hcuts_PR2013.pdf (1.16 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00802978 , version 1 (20-03-2013)
hal-00802978 , version 2 (29-04-2013)

Identifiants

Citer

Bangalore Ravi Kiran, Jean Serra. Global-local optimizations by hierarchical cuts and climbing energies. Pattern Recognition Letters, 2014, 47 (1), pp.12-24. ⟨10.1016/j.patcog.2013.05.012⟩. ⟨hal-00802978v2⟩
371 Consultations
615 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More