白昼条件下,天空背景光散射强烈,星敏感器在近红外波段工作性能更优,但是由于近红外敏感器件本身特性,近红外星图存在着盐粒噪声、图像非均匀性引起的条纹噪声、背景不均匀性及背景过强等特性,导致难以实现对星图中星点进行有效的提取。为了提高星图星点提取能力,提出了一种结合逆谐波均值滤波、能量相关滤波和形态学滤波的多重滤波方法,先后解决星图盐粒噪声、条纹噪声、背景不均匀性及背景过强等问题,并且利用自适应阈值法和质心法实现近红外星图的星点提取。仿真实验结果表明:该方法能够有效地抑制噪声,改善近红外星图质量,星点提取的误差在0.5个像素以内。

Under daylight conditions, the intense scattering of sky background light,and the star tracker works better in the near-infrared band, but due to the inherent characteristics of near-infrared sensitive devices, there are features such as salt noise, streak noise due to imagenonuniformity, backgroundnonuniformity, and strong background in the near-infrared star image. It is difficult to achieve effectively extraction of stars in a star image. In order to improve the ability of starextraction,a multiple filtering method combining contraharmonic mean filtering, energy correlation filtering and morphological filtering is proposed in this paper. It solves problems such as salt noise, streak noise, background nonuniformity and strong background. The results of simulation and experiment show that this method can effectively suppress noise and improve the quality of near-infrared star images. The error of the star extraction is within 0.5 pixel.