Infrared dim target detection algorithm based on low rank factorization and human visual system fusion

Siyi Wang; Shengda Pan

doi:10.1117/12.3031602

18 July 2024 Infrared dim target detection algorithm based on low rank factorization and human visual system fusion

Siyi Wang, Shengda Pan

Proceedings Volume 13179, International Conference on Optics and Machine Vision (ICOMV 2024); 1317915 (2024) https://doi.org/10.1117/12.3031602
Event: International Conference on Optics and Machine Vision (ICOMV 2024), 2024, Nanchang, China

Abstract

An infrared dim target detection method based on Human Visual System and Low Rank Matrix Factorization is proposed in this paper. Firstly, the sparse component of a small-target infrared image is obtained through fast matrix decomposition based on weighted scene priors, achieving preliminary screening of small target regions in the image. Then, utilizing prior knowledge of the shape and contrast distribution of small targets, a three-layer sliding window with oversampled sub-windows is applied to further suppress non-target areas in the sparse part image. Lastly, to accomplish accurate extraction of small targets, an adaptive threshold segmentation method is applied.The experimental results reveal that, while preservation of good real-time performance, the recommended approach outperforms traditional infrared small target identification procedures in terms of BSF and SCRG.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Siyi Wang and Shengda Pan "Infrared dim target detection algorithm based on low rank factorization and human visual system fusion", Proc. SPIE 13179, International Conference on Optics and Machine Vision (ICOMV 2024), 1317915 (18 July 2024); https://doi.org/10.1117/12.3031602

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