基于亮度先验的星图杂散光噪声去除方法

Stray light noise removal method of star maps based on intensity prior

  • 摘要: 针对地基可见光观测图像中存在的杂散光干扰问题,提出了一种基于星图亮度先验的杂散光噪声去除方法。首先,通过分析杂散光形成的原因及其在星图中的空间分布特征,建立星图在杂散光干扰下的退化模型;然后利用星图的亮度先验,估计大气的深度信息并去除分布不均的杂散光噪声;最后,在地基光学望远镜拍摄的实际星图上进行验证。与现有的算法相比,对于受不同程度杂散光干扰的目标,该方法在背景抑制和目标信杂比提升上均获得了更好的实验效果。其中,针对序列星图中信杂比为2.05以上的空间目标,处理后能够获得7.39以上的信杂比增益和1.92以上的背景抑制因子。

     

    Abstract: Aiming at the problem of stray light interference in ground-based visible light observation images, a stray light noise removal method of star maps based on intensity prior was proposed. First, by analyzing the causes of stray light and its spatial distribution characteristics in star maps, a degradation model of the star maps under stray light interference was established; then, the intensity prior of star maps was used to estimate the depth information of the atmosphere and remove the unevenly distributed stray light noise; finally, the method was verified on the actual star maps taken by the ground-based optical telescopes. Compared with the existing algorithms, the proposed method obtained better experimental results in terms of background suppression and target signal-to-clutter ratio (SCR) improvement for targets interfered by different degrees of stray light. Among them, for the space target with a SCR of 2.05 or more in the sequence star maps, the proposed method can obtain the SCR gain of 7.39 or more and the background suppression factor (BSF) of 1.92 or more after processing.

     

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