MrFDDGAN: Multireceptive Field Feature Transfer and Dual Discriminator-Driven Generative Adversarial Network for Infrared and Color Visible Image Fusion-Reference-Cited by-同舟云学术

MrFDDGAN: Multireceptive Field Feature Transfer and Dual Discriminator-Driven Generative Adversarial Network for Infrared and Color Visible Image Fusion

Published:2023 Issue: Volume:72 Page:1-28
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Li Junwu¹^ORCID,Li Binhua¹^ORCID,Jiang Yaoxi¹^ORCID,Tian Longwei²^ORCID,Cai Weiwei³^ORCID

Affiliation:

1. Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China

2. Shanghai Key Laboratory of Navigation and Location-Based Services, Shanghai Jiao Tong University, Shanghai, China

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

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10035924.pdf?arnumber=10035924

Reference49 articles.

1. GANMcC: A Generative Adversarial Network With Multiclassification Constraints for Infrared and Visible Image Fusion

2. Investigating Task-Driven Latent Feasibility for Nonconvex Image Modeling

3. Deep learning for pixel-level image fusion: Recent advances and future prospects

4. Infrared and visible image fusion methods and applications: A survey

5. A fully convolutional two-stream fusion network for interactive image segmentation

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