一种新的方法用于星敏感器近红外星图星点提取

A new method used for star distillation of near-infrared star image of star tracker

分析了近红外星图小波分解系数的特点。依据小波分析的边缘检测特性、解相关性和多分辨率特性结合星点的灰度分布特征设计了不同尺度下的检测模板。在恒虚警概率条件下,提出利用局部阈值克服红外星图本身的背景不均匀性。通过在星图第二次分解的近似系数上检测星点最大灰度值的位置,削弱了单点噪声和条纹噪声的影响。实验结果显示,算法能有效得出视场中的星点最大灰度值坐标,误差在1个像素位置左右,满足后续星点提取的需要。

The distillation of near-infrared star image of star tracker was analyzed in this paper. A new method for this problem was presented. Firstly, characters of near-infrared star image in wavelet domain were analyzed and mask used to detect stars in multi scales were designed according to the distribution of the gray of stars. Then, local threshold was applied to overcome the imbalance of the background under the constant false alarm rate. Lastly, positions of the heaviest gray values of stars in the secondly decomposed approximation coefficients were accessed, eliminating the effect of the single point noise and stripe noise. Experimental results indicate that the method could efficiently obtain the position of the heaviest gray value of detected stars with error around one pixel, which satisfies the requirement of estimation of centroid.