为了有效提取星图中星点小目标, 实现提高星图识别效率及姿态计算的精度, 本文在分析星点目标和小目标像共性的基础上, 采用了一种形态学星点提取方法。该方法根据数学形态学运算的特点, 得到估计的星图背景, 通过灰度形态学 Top-Hat变换对消背景, 得到含有目标和高频噪声的图像, 本文采用自适应阈值法确定实际图像的阈值。实验结果表明此方法能很好的滤除背景噪声, 有助于选取阈值及确定目标亮度, 确定的目标亮度比传统方法得到亮度效果要好, 且质心坐标与真值相差不超过 0.3个像素单元。

In order to extract the star effectively, and improve the star map identification efficiency and the attitude precision of star map, a method of star extraction based on the commonness between star and small target using morphological was proposed. Background was estimated by morphological and suppressed by gray-scale morphology Top-Hat transform, and the star image was comprised of star target and high frequency noise. Self-adaptive threshold value method was adopted to determine the actual image threshold. The results indicate that the method can well suppress the background noise, and redound to selecting threshold and confirming the brightness of target. Moreover, the brightness of target confirmed is more effective than conventional methods, and the coordinates of centroid compared with the true value does not exceed 0.3 pixels unit.