Article
Engineering, Electrical & Electronic
Xiangbo Zhang, Gang Liu, Lei Huang, Qin Ren, Durga Prasad Bavirisetti
Summary: Due to the difference in structure between infrared and visible images, existing algorithms often use globally consistent strategies, which may compromise the contrast of target regions. To address this issue, we propose an infrared and visible image fusion method called IVOMFuse, which utilizes infrared-to-visible object mapping. Our method involves processing the infrared image using the PIIFCM algorithm to extract the target region. The target region is then mapped to the visible image, allowing for quick retrieval of the corresponding target region. Additionally, we employ a hybrid fusion strategy for different regions based on the EM algorithm and FPDE to optimize the probability model and decompose the source image into high-frequency and low-frequency approximation images. Finally, our algorithm achieves superior performance compared to 14 state-of-the-art fusion methods on three commonly used datasets.
DIGITAL SIGNAL PROCESSING
(2023)
Article
Optics
Yanling Chen, Lianglun Cheng, Heng Wu, Fei Mo, Ziyang Chen
Summary: The proposed method utilizes an iterative differential thermal information filter to fuse infrared and visible images, resulting in a fusion image with prominent thermal targets from the infrared image and detailed information from the visible image. Experimental results demonstrate the advantages and effectiveness of the method compared to deep learning and non deep learning-based methods.
OPTICS AND LASERS IN ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Xingchen Zhang, Yiannis Demiris
Summary: Visible and infrared image fusion (VIF) has gained considerable attention for its applications in various tasks, and there has been an increasing number of deep learning-based VIF methods proposed in recent years. This paper presents a comprehensive review of these methods, discussing motivation, taxonomy, recent developments, datasets, evaluation methods, and future prospects in detail. It serves as a valuable reference for VIF researchers and those interested in this rapidly developing field.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Huibin Yan, Shuoyao Wang
Summary: This study proposes a novel method for infrared-visible image fusion to better integrate thermal radiation information and appearance details. By utilizing contrast and gradient preservation, and employing a specific norm formulation, experimental results demonstrate the competitiveness of this method in both subjective and objective evaluations.
IEEE SIGNAL PROCESSING LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Jing Li, Bin Yang, Lu Bai, Hao Dou, Chang Li, Lingfei Ma
Summary: This study proposes a transformer-based fusion method for infrared and visible image fusion, reconstructing the fused image in token dimension and capturing both the long-range dependencies in intra-modal and the attentive correlation of inter-modal. The use of learnable attentive weights enhances and balances the interaction between modal tokens. Experimental results demonstrate the significant advantages of this method in infrared and visible image fusion.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Artificial Intelligence
Guofa Li, Yongjie Lin, Xingda Qu
Summary: This paper proposes a new infrared and visible image fusion method based on multi-scale transformation and norm optimization, which uses a new loss function and the split Bregman method for image fusion. Experimental results show that the method outperforms others in highlighting targets and retaining effective detail information.
INFORMATION FUSION
(2021)
Article
Engineering, Electrical & Electronic
Chen Cheng, Cheng Sun, Yongqi Sun, Jiahui Zhu
Summary: This paper proposes a position-unaware style fusion loss function, jointly trained with an unsupervised network to learn the style information of the input images. The introduction of attention-based network connections enables full utilization of information at different scales and enhances information transmission across these scales. Experimental results demonstrate that the proposed model outperforms existing methods in both qualitative and quantitative evaluations.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2022)
Article
Engineering, Electrical & Electronic
Yong Yang, Xiangkai Kong, Shuying Huang, Weiguo Wan, Zixiang Song, Wang Zhang
Summary: A novel infrared and visible image fusion method based on a modified side window filter (MSWF) and intensity transformation is proposed in this study. The method outperforms state-of-the-art fusion methods in both subjective evaluation and objective metrics, effectively fusing the information of the source images.
IEEE SENSORS JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Yan Mo, Xudong Kang, Puhong Duan, Bin Sun, Shutao Li
Summary: A novel infrared and visible image fusion method is proposed in this paper, which considers the attributes of objects in source images and utilizes edge-preserving filters and weight-based pyramid fusion strategy to achieve more natural fusion results. Experimental results demonstrate that the proposed method achieves state-of-the-art fusion performance in terms of both visual and objective evaluations. The algorithm is also implemented in an infrared-visible dual sensor system, showing the practicality of the fusion method.
INFORMATION FUSION
(2021)
Article
Computer Science, Information Systems
Zhuo Li, Hai-Miao Hu, Wei Zhang, Shiliang Pu, Bo Li
Summary: This paper proposes a new visible and near-infrared images fusion algorithm by fully considering their different reflection and scattering characteristics. The experimental results demonstrate that the proposed algorithm can preserve spectrum characteristics, avoid color distortion, and outperform the state-of-the-art techniques.
IEEE TRANSACTIONS ON MULTIMEDIA
(2021)
Article
Optics
Jinjuan Wang, Xiliang Zeng, Shan Duan, Qun Zhou, Hao Peng
Summary: We propose a fast and efficient method for fusing infrared and visible images based on median filter and intensity transfer. The method achieves superior fusion performance in terms of both subjective evaluation and objective metrics when compared with seven standard state-of-the-art methods, and is suitable for real-time fusion applications.
UKRAINIAN JOURNAL OF PHYSICAL OPTICS
(2022)
Article
Instruments & Instrumentation
Zhijian Li, Fengbao Yang, Yubin Gao, Linna Ji
Summary: Changes in illumination conditions affect the relative amount of complementary information between infrared and visible images. Existing fusion methods often ignore these changes, leading to the loss of detail information and low contrast in fused images. Our proposed IDA Fusion method addresses this issue by adaptively fusing source images and adjusting illumination-dependent rules.
INFRARED PHYSICS & TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Hui Li, Tianyang Xu, Xiao-Jun Wu, Jiwen Lu, Josef Kittler
Summary: Deep learning based fusion methods have achieved promising performance in image fusion tasks due to the importance of network architecture. However, designing fusion networks is still a challenging task. In this paper, the fusion task is mathematically formulated and a connection between the optimal solution and network architecture is established. This leads to the proposal of a lightweight fusion network based on a learnable representation approach.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Wei Tang, Fazhi He, Yu Liu, Yansong Duan, Tongzhen Si
Summary: In this paper, a novel end-to-end model called DATFuse is proposed for infrared and visible image fusion. It combines the thermal radiation information of an infrared image with the texture details of a visible image to detect targets under various weather conditions. The model uses a dual attention residual module and a Transformer module to accurately examine important areas of the source images and preserve global complementary information. With an unsupervised training approach, the model outperforms other state-of-the-art approaches in qualitative and quantitative assessments, demonstrating its good generalization ability.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Anyang Song, Huixian Duan, Haodong Pei, Lei Ding
Summary: This paper proposes a novel fusion model for infrared and visible image fusion using a triple-discriminator generative adversarial network, which achieves a balance between clear boundaries and rich details. The difference image obtained from image subtraction highlights the difference information, extracts image details, and retains the contrast of infrared targets and texture details in visible images during fusion.
Article
Instruments & Instrumentation
Zengrun Wen, Xiulin Fan, Kaile Wang, Weiming Wang, Song Gao, Wenjing Hao, Yuanmei Gao, Yangjian Cai, Liren Zheng
Summary: This study presents a transition from Q-switched state to continuous wave state in an erbium-doped fiber laser, accompanied by irregular mode-hopping. The results showed that the transition between these two states can be achieved by adjusting the pump power. Modulation peaks were observed on both the Q-switched pulse train and the continuous wave background, and the central wavelength fluctuated.
INFRARED PHYSICS & TECHNOLOGY
(2024)