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The Fusion of Unmatched Infrared and Visible Images Based on Generative Adversarial Networks
Joint Authors
Wang, Hongqiao
Fu, Guangyuan
Zhao, Yuqing
Zhang, Shaolei
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-20
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Visible images contain clear texture information and high spatial resolution but are unreliable under nighttime or ambient occlusion conditions.
Infrared images can display target thermal radiation information under day, night, alternative weather, and ambient occlusion conditions.
However, infrared images often lack good contour and texture information.
Therefore, an increasing number of researchers are fusing visible and infrared images to obtain more information from them, which requires two completely matched images.
However, it is difficult to obtain perfectly matched visible and infrared images in practice.
In view of the above issues, we propose a new network model based on generative adversarial networks (GANs) to fuse unmatched infrared and visible images.
Our method generates the corresponding infrared image from a visible image and fuses the two images together to obtain more information.
The effectiveness of the proposed method is verified qualitatively and quantitatively through experimentation on public datasets.
In addition, the generated fused images of the proposed method contain more abundant texture and thermal radiation information than other methods.
American Psychological Association (APA)
Zhao, Yuqing& Fu, Guangyuan& Wang, Hongqiao& Zhang, Shaolei. 2020. The Fusion of Unmatched Infrared and Visible Images Based on Generative Adversarial Networks. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1194633
Modern Language Association (MLA)
Zhao, Yuqing…[et al.]. The Fusion of Unmatched Infrared and Visible Images Based on Generative Adversarial Networks. Mathematical Problems in Engineering No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1194633
American Medical Association (AMA)
Zhao, Yuqing& Fu, Guangyuan& Wang, Hongqiao& Zhang, Shaolei. The Fusion of Unmatched Infrared and Visible Images Based on Generative Adversarial Networks. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1194633
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1194633