New saliency point detection and evaluation methods for finding structural differences in remote sensing images of long time-span samples

Andrea Kovacs, Tamas Sziranyi

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

3 Citations (Scopus)

Abstract

The paper introduces a novel methodology to find changes in remote sensing image series. Some remotely sensed areas are scanned frequently to spot relevant changes, and several repositories contain multi-temporal image samples for the same area. The proposed method finds changes in images scanned by a long time-interval difference in very different lighting and surface conditions. The presented method is basically an exploitation of Harris saliency function and its derivatives for finding featuring points among image samples. To fit together the definition of keypoints and their active contour around them, we have introduced the Harris corner detection as an outline detector instead of the simple edge functions. We also demonstrate a new local descriptor by generating local active contours. Saliency points support the boundary hull definition of objects, constructing by graph based connectivity detection and neighborhood description. This graph based shape descriptor works on the saliency points of the difference and in-layer features. We prove the method in finding structural changes on remote sensing images.

Original languageEnglish
Title of host publicationAdvanced Concepts for Intelligent Vision Systems - 12th International Conference, ACIVS 2010, Proceedings
Pages272-283
Number of pages12
EditionPART 2
DOIs
Publication statusPublished - Dec 1 2010
Event12th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2010 - Sydney, NSW, Australia
Duration: Dec 13 2010Dec 16 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6475 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2010
CountryAustralia
CitySydney, NSW
Period12/13/1012/16/10

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Keywords

  • Harris function
  • change detection
  • remote sensing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kovacs, A., & Sziranyi, T. (2010). New saliency point detection and evaluation methods for finding structural differences in remote sensing images of long time-span samples. In Advanced Concepts for Intelligent Vision Systems - 12th International Conference, ACIVS 2010, Proceedings (PART 2 ed., pp. 272-283). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6475 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-17691-3_25