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Robust feature based multisensor remote sensing image registration algorithm

  • Nanjing Research Institute of Electronics Technology
  • Harbin Institute of Technology
  • Nanjing University of Aeronautics and Astronautics

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

Abstract

The crucial problem of multisensor remote sensing image registration is how to establish the reliable correspondences between the features extracted from two images. The feature similarity based methods fail when similar local regions exist, and the spatial relationship methods fail to match small portion of pair wise correspondences out of the total number of features. In this paper, we proposed shape context as feature similarity and overlap error as spatial relationship to construct an objective function for the feature matching problem, and deterministic annealing (DA) is used to solve the optimization problem. Feature matching experiments with real remote sensing images demonstrate the superiority of our algorithm over the 5 classic feature matching algorithms, and registration results outperform the popular image registration algorithms.

Original languageEnglish
Title of host publicationProceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages319-322
Number of pages4
ISBN (Electronic)9781479970056
DOIs
StatePublished - 19 Mar 2015
Event7th International Symposium on Computational Intelligence and Design, ISCID 2014 - Hangzhou, China
Duration: 13 Dec 201414 Dec 2014

Publication series

NameProceedings - 2014 7th International Symposium on Computational Intelligence and Design, ISCID 2014
Volume1

Conference

Conference7th International Symposium on Computational Intelligence and Design, ISCID 2014
Country/TerritoryChina
CityHangzhou
Period13/12/1414/12/14

Keywords

  • Multisensor image registration
  • deterministic annealing (DA)
  • feature matching
  • overlap error
  • shape context

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