Image registration based on genetic algorithm and weighted feature correspondences

Zhi Yuan, Alireza Ahrary, Peimin Yan, Sei Ichiro Kamata

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

4 Citations (Scopus)

Abstract

Super resolution is a technique of enhancing image resolution by combining information from multiple images. It is widely applied in fields like camera surveillance, satellite imaging, pattern recognition, etc. One challenging problem of super resolution is its high demand on image registration accuracy. This paper introduces a high accuracy registration approach for the purpose of super resolution. It is invariant to translation, scaling, rotation, and noise, and can be used to automatically obtain the Maximize a Likelihood Estimation (MLE) of image homography (registration result) using information only contained within the images themselves. An effective Genetic Algorithm based approach is used to filter out all the mismatches. Comparison with RANSAC and Keren's method will be given to prove the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2009 IEEE 13th International Symposium on Consumer Electronics, ISCE 2009
Pages42-46
Number of pages5
DOIs
Publication statusPublished - 2009 Oct 27
Event2009 IEEE 13th International Symposium on Consumer Electronics, ISCE 2009 - Kyoto, Japan
Duration: 2009 May 252009 May 28

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN (Print)0747-668X

Conference

Conference2009 IEEE 13th International Symposium on Consumer Electronics, ISCE 2009
CountryJapan
CityKyoto
Period09/5/2509/5/28

Keywords

  • Backward projection
  • Genetic Algorithm
  • Image registration
  • RANSAC (Random Sampling Consensus)
  • SIFT (Scale Invairant Feature Transform)
  • Super resolution

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Yuan, Z., Ahrary, A., Yan, P., & Kamata, S. I. (2009). Image registration based on genetic algorithm and weighted feature correspondences. In 2009 IEEE 13th International Symposium on Consumer Electronics, ISCE 2009 (pp. 42-46). [5157002] (Digest of Technical Papers - IEEE International Conference on Consumer Electronics). https://doi.org/10.1109/ISCE.2009.5157002