Citation: | JI L N,GUO X M,YANG F B. Adaptive layered fusion algorithm for infrared and visible video based on possibility theory[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(10):3021-3031 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0765 |
The current infrared and visible video fusion model cannot dynamically adjust the fusion strategy according to the difference between videos, resulting in poor fusion effect or even failure. To address this issue,an adaptive layered fusion algorithm for infrared and visible video based on possibility theory was proposed. First, the magnitudes of various difference features of the region of interest in each frame of the video sequence were calculated, and the main difference features corresponding to each frame were obtained. Secondly, a layered fusion framework was built to determine the variables of each layer. The fusion effectiveness of different variables for each difference feature was calculated based on cosine similarity, and the possibility theory was used to construct the corresponding fusion effectiveness distribution.Then, the fusion effect of different variables for various difference features was analyzed layer by layer, and the optimal variable of each layer was selected. Finally, the adaptive layered fusion of infrared and visible video was realized through the optimal combination of variables. The experimental results show that the method in this paper has achieved remarkable fusion results in preserving typical infrared targets and visible structural details, and it is superior to other single fusion methods in quantitative analysis and qualitative evaluation.
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