An Image Fusion Method Based on Curvelet Transform and Guided Filter Enhancement
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-27
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
In order to improve the clarity of image fusion and solve the problem that the image fusion effect is affected by the illumination and weather of visible light, a fusion method of infrared and visible images for night-vision context enhancement is proposed.
First, a guided filter is used to enhance the details of the visible image.
Then, the enhanced visible and infrared images are decomposed by the curvelet transform.
The improved sparse representation is used to fuse the low-frequency part, while the high-frequency part is fused with the parametric adaptation pulse-coupled neural networks.
Finally, the fusion result is obtained by inverse transformation of the curvelet transform.
The experimental results show that the proposed method has good performance in detail processing, edge protection, and source image information.
American Psychological Association (APA)
Zhang, Hui& Ma, Xu& Tian, Yanshan. 2020. An Image Fusion Method Based on Curvelet Transform and Guided Filter Enhancement. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1202502
Modern Language Association (MLA)
Zhang, Hui…[et al.]. An Image Fusion Method Based on Curvelet Transform and Guided Filter Enhancement. Mathematical Problems in Engineering No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1202502
American Medical Association (AMA)
Zhang, Hui& Ma, Xu& Tian, Yanshan. An Image Fusion Method Based on Curvelet Transform and Guided Filter Enhancement. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1202502
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202502