Deep-learning-based algorithm for local feature recognition of target infrared polarization

Zhihui Zou; Shuai Yang; Yingchao Li; Haodong Shi; Qiang Fu

doi:10.1117/12.2689150

31 July 2023 Deep-learning-based algorithm for local feature recognition of target infrared polarization

Zhihui Zou, Shuai Yang, Yingchao Li, Haodong Shi, Qiang Fu

Proceedings Volume 12747, Third International Conference on Optics and Image Processing (ICOIP 2023); 127471I (2023) https://doi.org/10.1117/12.2689150
Event: Third International Conference on Optics and Image Processing (ICOIP 2023), 2023, Hangzhou, China

Abstract

In response to the traditional detection methods of not detecting the target, not seeing it, blurring the outline and details of the image, etc., using a combination of infrared and polarization detection, the infrared image information and the polarization image information are decoded to solve the problem of not being detected or seen in various environments. For the target local feature extraction process of large amounts of data, slow extraction speed, and other problems, an improved SIFT algorithm for local feature extraction of polarized images with deep learning is proposed. Experimental results show that the modified algorithm combines the advantages of polarimetric imaging and deep learning to achieve fast feature extraction of targets in simple or complex backgrounds. The algorithm improves the speed of local feature extraction of polarized images by 3.6% and the accuracy of extraction by 2.8%. The algorithm provides the theoretical basis for target classification, identification, and tracking techniques.

Citation Download Citation

Zhihui Zou, Shuai Yang, Yingchao Li, Haodong Shi, and Qiang Fu "Deep-learning-based algorithm for local feature recognition of target infrared polarization", Proc. SPIE 12747, Third International Conference on Optics and Image Processing (ICOIP 2023), 127471I (31 July 2023); https://doi.org/10.1117/12.2689150

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