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Treffer: Scale Selection for Compact Scale-Space Representation of Vector-Valued Images

Title:
Scale Selection for Compact Scale-Space Representation of Vector-Valued Images
Source:
Scale Space and Variational Methods in Computer VisionInternational journal of computer vision. 84(2):194-204
Publisher Information:
Heidelberg: Springer, 2009.
Publication Year:
2009
Physical Description:
print, 3/4 p
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Vrije Universiteit Brussel, ETRO-IRIS, Pleinlaan 2, 1050 Brussels, Belgium
EEE Dep., Imperial College, CSP Group, Exhibition Road, SW7 2AZ London, United Kingdom
NCSR Demokritos, IIT, Computational Intelligence Laboratory, P.O. BOX 60228, Agia Paraskevi, Athens, 153 10, Greece
ISSN:
0920-5691
Rights:
Copyright 2009 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.21804593
Database:
PASCAL Archive

Weitere Informationen

This paper investigates the scale selection problem for nonlinear diffusion scale-spaces. This topic comprises the notions of localization scale selection and scale space discretization. For the former, we present a new approach. It aims at maximizing the image content's presence by finding the scale that has a maximum correlation with the noise-free image. For the latter, we propose to adapt the optimal diffusion stopping time criterion of Mrázek and Navara in such a way that it may identify multiple scales of importance.