HP-CRL: High-resolution preservation driven collaborative representation learning for infrared and visible image fusion-Reference-Cited by-同舟云学术

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HP-CRL: High-resolution preservation driven collaborative representation learning for infrared and visible image fusion

Published:2024-10 Issue: Volume:177 Page:111184
ISSN:0030-3992
Container-title:Optics & Laser Technology
language:en
Short-container-title:Optics & Laser Technology

Author:

Huang Jingyu^ORCID,Nie Rencan^ORCID,Cao Jinde,Zhang Ying^ORCID,Su Huaping

Publisher

Elsevier BV

Reference68 articles.

1. Infrared and visible image fusion methods and applications: A survey;Ma;Inf. Fusion,2019

2. Learning a deep multi-scale feature ensemble and an edge-attention guidance for image fusion;Liu;IEEE Trans. Circuits Syst. Video Technol.,2021

3. U2Fusion: A unified unsupervised image fusion network;Xu;IEEE Trans. Pattern Anal. Mach. Intell.,2020

4. DIDFuse: Deep image decomposition for infrared and visible image fusion;Zhao,2020

5. DDFM: denoising diffusion model for multi-modality image fusion;Zhao,2023

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