Single-pixel noise commonly appearing in a star sensor can cause an unexpected error in centroid extraction. To overcome this problem, this paper proposes a star image denoising algorithm, named Improved Gaussian Side Window Filtering (IGSWF). Firstly, the IGSWF algorithm uses four special triangular Gaussian subtemplates for edge protection. Secondly, it exploits a reconstruction function based on the characteristic of stars and noise. The proposed IGSWF algorithm was successfully verified through simulations and evaluated in a star sensor. The experimental results indicated that the IGSWF algorithm performed better in preserving the shape of stars and eliminating the single-pixel noise and the centroid estimation error (CEE) value after using the IGSWF algorithm was eight times smaller than the original value, six times smaller than that after traditional window filtering, and three times smaller than that after the side window filtering.

中文翻译：

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基于边缘保护的焦油传感器降噪算法

星敏感器中常见的单像素噪声会导致质心提取出现意外错误。针对这一问题，本文提出了一种星形图像去噪算法，称为改进高斯边窗滤波（IGSWF）。首先，IGSWF 算法使用四个特殊的三角形高斯子模板进行边缘保护。其次，它利用了基于恒星和噪声特性的重建函数。所提出的IGSWF算法通过仿真成功验证，并在星敏感器中进行了评估。实验结果表明，IGSWF算法在保留恒星形状和消除单像素噪声方面表现更好，使用IGSWF算法后的质心估计误差（CEE）值比原值小8倍，