LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images-Reference-Cited by-同舟云学术

LRRNet: A Novel Representation Learning Guided Fusion Network for Infrared and Visible Images

Published:2023-09-01 Issue:9 Volume:45 Page:11040-11052
ISSN:0162-8828
Container-title:IEEE Transactions on Pattern Analysis and Machine Intelligence
language:
Short-container-title:IEEE Trans. Pattern Anal. Mach. Intell.

Author:

Li Hui¹^ORCID,Xu Tianyang¹^ORCID,Wu Xiao-Jun¹^ORCID,Lu Jiwen²^ORCID,Kittler Josef³^ORCID

Affiliation:

1. School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China

2. State Key Lab of Intelligent Technologies and Systems, Beijing National Research Center for Information Science and Technology (BNRist), Beijing, China

3. Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, U.K.

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

111 Project of Ministry of Education of China

Engineering and Physical Sciences Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

Link

http://xplorestaging.ieee.org/ielx7/34/10210213/10105495.pdf?arnumber=10105495

Reference48 articles.

1. Ringing artifacts in wavelet based image fusion: Analysis, measurement and remedies

2. YDTR: Infrared and Visible Image Fusion via Y-shape Dynamic Transformer

3. Exploring a unified low rank representation for multi-focus image fusion

4. SwinFusion: Cross-domain Long-range Learning for General Image Fusion via Swin Transformer

5. RFN-Nest: An end-to-end residual fusion network for infrared and visible images

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