Infrared and visible image fusion method based on target enhancement and rat swarm optimization
| Autor: | HAO Shuai, SUN Xizi, MA Xu, AN Beiyi, HE Tian, LI Jiahao, SUN Siya |
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| Jazyk: | čínština |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Xibei Gongye Daxue Xuebao, Vol 42, Iss 4, Pp 735-743 (2024) |
| Druh dokumentu: | article |
| ISSN: | 1000-2758 2609-7125 |
| DOI: | 10.1051/jnwpu/20244240735 |
| Popis: | In order to solve the target ambiguity and information loss in the fusion results of traditional infrared and visible images, a fusion method of infrared and visible images based on the target enhancement and mouse swarm optimization, which is abbreviated as TERSFuse. Firstly, in order to reduce the loss of the original image details in the fusion results, the infrared contrast enhancement module and the visible image enhancement module based on the brightness perception are constructed respectively. Secondly, the infrared and visible enhanced images were decomposed by using the Laplace pyramid transform to obtain the corresponding high and low frequency images. In order to make the fusion result fully retain the original information, the "maximum absolute value" rule is used to fuse the infrared and visible high frequency images, and the low frequency images are fused by calculating the weight coefficient. Finally, the image reconstruction module based on the rat swarm optimization is designed to achieve the adaptive allocation of weight parameters of high frequency and low frequency image reconstruction, and then improve the visual effect of the fused image. In order to verify the advantages of the present algorithm, the experimental results show that the present algorithm not only obtains the good visual effects, but also can retains the rich edge texture and contrast information of the original image. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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