AN IMPROVED INFRARED AND VISIBLE IMAGE FUSION ALGORITHM BASED ON CURVELET TRANSFORM
The fusion of infrared images and visible images can combine complementary information in an image, so we can better describe a scene, and it is helpful for some tasks such as target detection, target localization and environment recognition. In this paper, we use the Second Generation Curvelet Tr...
Main Author: | |
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Format: | Article |
Language: | English |
Published: |
Zibeline International
2017-02-01
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Series: | Acta Informatica Malaysia |
Subjects: | |
Online Access: | https://actainformaticamalaysia.com/archives/AIM/1aim2017/1aim2017-36-38.pdf |
Summary: | The fusion of infrared images and visible images can combine complementary information in an image, so we can
better describe a scene, and it is helpful for some tasks such as target detection, target localization and environment
recognition. In this paper, we use the Second Generation Curvelet Transform (SGCT) to decompose infrared images
and grayscale visible images to propose a new image fusion algorithm. This algorithm uses a multi-resolution
decomposition of different tools and different fusion rules implementation. The simulation results show that,
compared with existing algorithms, this algorithm have improved to some extent in the evaluation of fused images. |
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ISSN: | 2521-0874 2521-0505 |