INFRARED AND VISIBLE IMAGE FUSION USING BIMODAL TRANSFORMERS

Citations

WEB OF SCIENCE

10
Citations

SCOPUS

14

초록

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. © 2022 IEEE.

키워드

multiscale network; transformer; Visible and infrared image fusion; INFORMATION; TRACKING; NETWORK
제목
INFRARED AND VISIBLE IMAGE FUSION USING BIMODAL TRANSFORMERS
저자
Park, Seonghyun; Vien, An Gia; Lee, Chul
DOI
10.1109/ICIP46576.2022.9897993
발행일
2022-12
유형
Proceedings Paper
저널명
2022 IEEE International Conference on Image Processing (ICIP)
페이지
1741 ~ 1745