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17 August 2023 Multi-source target detection based on pixel-level fusion and decision-level fusion
Ming Lei, Yanyan Liu, Kuaikuai Yu, Congang Chen, Fang Liu
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Proceedings Volume 12757, 3rd International Conference on Laser, Optics, and Optoelectronic Technology (LOPET 2023); 127572O (2023) https://doi.org/10.1117/12.2690419
Event: 3rd International Conference on Laser, Optics and Optoelectronic Technology (LOPET 2023), 2023, Kunming, China
Abstract
In this paper, we focus on the problem of the visible images and the infrared images fusion detection. Aiming at the incomplete target information obtained by the single wave band target detection algorithm, an improved DenseFuse pixel-level fusion detection model CLHE-DenseFuse-Mask R-CNN is designed to fuse the information of the visible images and the infrared images. In order to solve the problem of the information loss caused by a single fusion method, a multi-source target detection model Mask R-CNN based on the pixel-level fusion and the decision-level fusion MF-Mask R-CNN is proposed. The experimental results show that the multi-fusion target detection model MF-Mask R-CNN significantly improves the detection accuracy of the targets
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Ming Lei, Yanyan Liu, Kuaikuai Yu, Congang Chen, and Fang Liu "Multi-source target detection based on pixel-level fusion and decision-level fusion", Proc. SPIE 12757, 3rd International Conference on Laser, Optics, and Optoelectronic Technology (LOPET 2023), 127572O (17 August 2023); https://doi.org/10.1117/12.2690419
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KEYWORDS
Image fusion
Target detection
Detection and tracking algorithms
Infrared imaging
Infrared detectors
Feature fusion
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