EPM-Net: a better way for optical and infrared scene matching via edge point

Shixiang Huang; Longyun Chi; Wenxing Fu; Jinwen Tian

doi:10.1117/12.3009056

7 March 2024 EPM-Net: a better way for optical and infrared scene matching via edge point

Shixiang Huang, Longyun Chi, Wenxing Fu, Jinwen Tian

Proceedings Volume 13085, MIPPR 2023: Automatic Target Recognition and Navigation; 130850N (2024) https://doi.org/10.1117/12.3009056
Event: Twelfth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2023), 2023, Wuhan, China

Abstract

As a crucial auxiliary technique in inertial navigation, scene matching has been widely applied in aircraft navigation and guidance. To enhance the adaptability and efficiency of scene matching algorithms in complex environments, existing approaches have gradually shifted towards heterogeneous scene matching, such as optical/ infrared scene matching based on deep learning features, with a focus on point features. However, due to the complex and diverse nonlinear distortions between optical and infrared images, the matching accuracy often fails to meet the practical requirements of navigation and positioning. In view of this problem, an EPM-Net algorithm based on edge features is proposed to improve matching performance by extracting more stable and discriminative edge point descriptors. Experimental results on infrared datasets demonstrate that this method achieves an average matching accuracy improvement of more than four times compared to traditional and existing deep learning methods.

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

Citation Download Citation

Shixiang Huang, Longyun Chi, Wenxing Fu, and Jinwen Tian "EPM-Net: a better way for optical and infrared scene matching via edge point", Proc. SPIE 13085, MIPPR 2023: Automatic Target Recognition and Navigation, 130850N (7 March 2024); https://doi.org/10.1117/12.3009056

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