Geometrical and textural component separation with adaptive scale selection

T. Szirányi, Dániel Szolgay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The present paper addresses the cartoon/texture decomposition task, offering theoretically clear solutions for the main issues of adaptivity, structure enhancement and the quality criterion of the goal function. We apply Anisotropic Diffusion with a Total Variation based adaptive parameter estimation and automatic stopping condition. Our quality measure is based on an observation that the cartoon and the texture components of an image are orthogonal to each other. The visual and numerical comparison to the similar algorithms from the state-of-the-art showed the superiority of the proposed method.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages66-77
Number of pages12
Volume7252 LNCS
DOIs
Publication statusPublished - 2012
EventInternational Workshop on Multimedia Understanding Through Semantics, Computation, and Learning, MUSCLE 2011 - Pisa, Italy
Duration: Dec 13 2011Dec 15 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7252 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherInternational Workshop on Multimedia Understanding Through Semantics, Computation, and Learning, MUSCLE 2011
CountryItaly
CityPisa
Period12/13/1112/15/11

Fingerprint

Texture
Textures
Adaptive Estimation
Anisotropic Diffusion
Quality Measures
Adaptivity
Numerical Comparisons
Total Variation
Parameter estimation
Parameter Estimation
Enhancement
Decomposition
Decompose
Vision
Observation

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Szirányi, T., & Szolgay, D. (2012). Geometrical and textural component separation with adaptive scale selection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7252 LNCS, pp. 66-77). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7252 LNCS). https://doi.org/10.1007/978-3-642-32436-9_6

Geometrical and textural component separation with adaptive scale selection. / Szirányi, T.; Szolgay, Dániel.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7252 LNCS 2012. p. 66-77 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7252 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Szirányi, T & Szolgay, D 2012, Geometrical and textural component separation with adaptive scale selection. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7252 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7252 LNCS, pp. 66-77, International Workshop on Multimedia Understanding Through Semantics, Computation, and Learning, MUSCLE 2011, Pisa, Italy, 12/13/11. https://doi.org/10.1007/978-3-642-32436-9_6
Szirányi T, Szolgay D. Geometrical and textural component separation with adaptive scale selection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7252 LNCS. 2012. p. 66-77. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-32436-9_6
Szirányi, T. ; Szolgay, Dániel. / Geometrical and textural component separation with adaptive scale selection. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7252 LNCS 2012. pp. 66-77 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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