Hierarchical Fusion of Infrared and Visible Images Based on Channel Attention Mechanism and Generative Adversarial Networks
In order to solve the problem that existing visible and infrared image fusion methods rely only on the original local or global information representation, which has the problem of edge blurring and non-protrusion of salient targets, this paper proposes a layered fusion method based on channel atten...
Saved in:
| Main Authors: | Jie Wu, Shuai Yang, Xiaoming Wang, Yu Pei, Shuai Wang, Congcong Song |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-10-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/24/21/6916 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
PS-GAN: Pseudo Supervised Generative Adversarial Network With Single Scale Retinex Embedding for Infrared and Visible Image Fusion
by: Jin Qi, et al.
Published: (2025-01-01) -
Cross-domain lung opacity detection via adversarial learning and box fusion
by: Jun Yao, et al.
Published: (2024-12-01) -
Infrared and visible image fusion algorithm based on gradient attention residuals dense block
by: Yongyu Luo, et al.
Published: (2024-11-01) -
Low-Light Image Enhancement Using CycleGAN-Based Near-Infrared Image Generation and Fusion
by: Min-Han Lee, et al.
Published: (2024-12-01) -
Multi-channel neural audio decorrelation using generative adversarial networks
by: Carlotta Anemüller, et al.
Published: (2024-11-01)