Multi-scale unsupervised network for infrared and visible image fusion based on joint attention mechanism
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Multi-scale unsupervised network for infrared and visible image fusion based on joint attention mechanism
Authors
Keywords
-
Journal
INFRARED PHYSICS & TECHNOLOGY
Volume 125, Issue -, Pages 104242
Publisher
Elsevier BV
Online
2022-06-14
DOI
10.1016/j.infrared.2022.104242
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Image fusion in the loop of high-level vision tasks: A semantic-aware real-time infrared and visible image fusion network
- (2022) Linfeng Tang et al. Information Fusion
- SDNet: A Versatile Squeeze-and-Decomposition Network for Real-Time Image Fusion
- (2021) Hao Zhang et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Image fusion meets deep learning: A survey and perspective
- (2021) Hao Zhang et al. Information Fusion
- Infrared and visible image fusion using dual discriminators generative adversarial networks with Wasserstein distance
- (2020) Jing Li et al. INFORMATION SCIENCES
- Unsupervised densely attention network for infrared and visible image fusion
- (2020) Yang Li et al. MULTIMEDIA TOOLS AND APPLICATIONS
- NestFuse: An Infrared and Visible Image Fusion Architecture Based on Nest Connection and Spatial/Channel Attention Models
- (2020) Hui Li et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- SDPNet: A Deep Network for Pan-Sharpening With Enhanced Information Representation
- (2020) Han Xu et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- U2Fusion: A Unified Unsupervised Image Fusion Network
- (2020) Han Xu et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A Novel Infrared and Visible Image Information Fusion Method Based on Phase Congruency and Image Entropy
- (2019) Xinghua Huang et al. Entropy
- Infrared and visible image fusion via detail preserving adversarial learning
- (2019) Jiayi Ma et al. Information Fusion
- Infrared and visible image fusion with convolutional neural networks
- (2018) Yu Liu et al. International Journal of Wavelets Multiresolution and Information Processing
- DenseFuse: A Fusion Approach to Infrared and Visible Images
- (2018) Hui Li et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- FusionGAN: A generative adversarial network for infrared and visible image fusion
- (2018) Jiayi Ma et al. Information Fusion
- Pixel-level image fusion: A survey of the state of the art
- (2017) Shutao Li et al. Information Fusion
- Infrared and visible image fusion based on visual saliency map and weighted least square optimization
- (2017) Jinlei Ma et al. INFRARED PHYSICS & TECHNOLOGY
- A new image quality metric for image fusion: The sum of the correlations of differences
- (2015) V. Aslantas et al. AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS
- A general framework for image fusion based on multi-scale transform and sparse representation
- (2015) Yu Liu et al. Information Fusion
- Fusion method for infrared and visible images by using non-negative sparse representation
- (2014) Jun Wang et al. INFRARED PHYSICS & TECHNOLOGY
- Group-Sparse Representation With Dictionary Learning for Medical Image Denoising and Fusion
- (2012) Shutao Li et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- A new image fusion performance metric based on visual information fidelity
- (2011) Yu Han et al. Information Fusion
- An Adaptive IHS Pan-Sharpening Method
- (2010) Sheida Rahmani et al. IEEE Geoscience and Remote Sensing Letters
- Performance comparison of different multi-resolution transforms for image fusion
- (2010) Shutao Li et al. Information Fusion
- Assessment of image fusion procedures using entropy, image quality, and multispectral classification
- (2008) Jan Van Aardt Journal of Applied Remote Sensing
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now