A comparative analysis of pixel-level image fusion based on sparse representation

Hang Tan*, Xianhe Huang, Huachun Tan*, Changtao He

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

Along with the development of wavelet transform (WT) technique, sparse representation as a new tool also gradually lead to the researchers' wide interests. In our study, a sparse representation based unified image fusion model is introduced. Under this fusion model, we compare several fusion results of combining different overcomplete dictionaries and sparse coefficients, and eventually find a best combination. Extensive experiment is implemented on two source images, and results illustrate the proposed fusion model is very effective. Furthermore, we also find an optimal combination of dictionary and sparse coefficient for pixel-level image fusion.

Original languageEnglish
Title of host publication2012 International Conference on Computational Problem-Solving, ICCP 2012
Pages332-334
Number of pages3
DOIs
Publication statusPublished - 2012
Event2012 International Conference on Computational Problem-Solving, ICCP 2012 - Leshan, China
Duration: 19 Oct 201221 Oct 2012

Publication series

Name2012 International Conference on Computational Problem-Solving, ICCP 2012

Conference

Conference2012 International Conference on Computational Problem-Solving, ICCP 2012
Country/TerritoryChina
CityLeshan
Period19/10/1221/10/12

Keywords

  • Sparse representation
  • image fusion
  • overcomplete dictionaries

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