Automatic threshold selection for profiles of attribute filters based on granulometric characteristic functions

Gabriele Cavallaro*, Nicola Falco, Mauro Dalla Mura, Lorenzo Bruzzone, Jón Atli Benediktsson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

Morphological attribute filters have been widely exploited for characterizing the spatial structures in remote sensing images. They have proven their effectiveness especially when computed in multi-scale architectures, such as for Attribute Profiles. However, the question how to choose a proper set of filter thresholds in order to build a representative profile remains one of the main issues. In this paper, a novel methodology for the selection of the filters’ parameters is presented. A set of thresholds is selected by analysing granulometric characteristic functions, which provide information on the image decomposition according to a given measure. The method exploits a tree (i. e., min-, max-or inclusion-tree) representation of an image, which allows us to avoid the filtering steps usually required prior the threshold selection, making the process computationally effective. The experimental analysis performed on two real remote sensing images shows the effectiveness of the proposed approach in providing representative and non-redundant multi-level image decompositions.

Original languageEnglish
Title of host publicationMathematical Morphology and its Applications to Signal and Image Processing - 12th International Symposium, ISMM 2015, Proceedings
EditorsLaurent Najman, Hugues Talbot, Jon Atli Benediktsson, Jocelyn Chanussot
PublisherSpringer Verlag
Pages169-181
Number of pages13
ISBN (Print)9783319187198
DOIs
Publication statusPublished - 2015
Event12th International Symposium on Mathematical Morphology, ISMM 2015 - Reykjavik, Iceland
Duration: 27 May 201529 May 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9082
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Symposium on Mathematical Morphology, ISMM 2015
Country/TerritoryIceland
CityReykjavik
Period27/05/1529/05/15

Bibliographical note

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

Other keywords

  • Connected filters
  • Mathematical morphology
  • Threshold selection
  • Tree representations

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