A zero-shot image denoising pipeline for space target detection

Sibei Li; Xin Song; Yuxuan Li

doi:10.1117/12.3055346

12 December 2024 A zero-shot image denoising pipeline for space target detection

Sibei Li, Xin Song, Yuxuan Li

Author Affiliations +

Proceedings Volume 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024); 134392O (2024) https://doi.org/10.1117/12.3055346
Event: Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 2024, Xiamen, China

Abstract

Optical imaging of space targets using ground-based or space-based telescopes is typically affected by complex noise. Due to the sparse features and limited data, the denoising performance of star images is often suboptimal. In this paper, we propose a lightweight zero-shot star image denoising framework featuring an improved 3-layer U-Net backbone, which can efficiently complete the denoising task without a complete dataset. This network extracts feature information through two pair of down-sampling and up-sampling layers, as well as several convolution modules. The spatial attention module is employed to focus on attention regions, enhancing the model efficiency and generalization ability. In the experiments conducted with real star images, the denoising pipeline primarily consists of three steps: image preprocessing, network training and inference. The results demonstrate that our method effectively removes noise from star images and outperforms existing techniques, facilitating the accurate detection and extraction of space targets in subsequent research.

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

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Sibei Li, Xin Song, and Yuxuan Li "A zero-shot image denoising pipeline for space target detection", Proc. SPIE 13439, Fourth International Conference on Testing Technology and Automation Engineering (TTAE 2024), 134392O (12 December 2024); https://doi.org/10.1117/12.3055346

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KEYWORDS

Stars

Image denoising

Denoising

Image processing

Telescopes

Visualization

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