INFRARED AND VISIBLE IMAGE FUSION USING BIMODAL TRANSFORMERS

Seonghyun Park, An Gia Vien, Chul Lee

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

13 Scopus citations

Abstract

We propose an infrared and visible image fusion algorithm using bimodal transformers. First, the proposed algorithm extracts multiscale features of the input infrared and visible images. Then, we develop the bimodal transformers that refine the extracted features by estimating their irrelevance maps to exploit the complementary information of the source images. Finally, we develop a reconstruction block that generates the fusion result by merging the refined features in the frequency domain to exploit the global information of the source images. Experimental results show that the proposed algorithm outperforms state-of-the-art infrared and visible image fusion algorithms on several datasets.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Image Processing, ICIP 2022 - Proceedings
PublisherIEEE Computer Society
Pages1741-1745
Number of pages5
ISBN (Electronic)9781665496209
DOIs
StatePublished - 2022
Event29th IEEE International Conference on Image Processing, ICIP 2022 - Bordeaux, France
Duration: 16 Oct 202219 Oct 2022

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference29th IEEE International Conference on Image Processing, ICIP 2022
Country/TerritoryFrance
CityBordeaux
Period16/10/2219/10/22

Keywords

  • multiscale network
  • transformer
  • Visible and infrared image fusion

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