基于最大能量法的白天红外星目标检测

受多种因素的影响,白天获得的红外星图像的信噪比低,且背景通常不均匀。采用一般的滤波方法无法提取出恒星目标,目前常用的形态学方法对于星图像的处理也不甚理想。首先分析背景特性,采用多帧叠加的方法消弱随机噪声,增大信噪比;然后设定阈值,对叠加后的星图进行背景消除,得到只含有目标及噪声的图像;然后用与恒星大小相近的模板按一定的规则对星图进行滤波,分割出目标。实验证明,该方法能较好地分离出恒星目标。

Infrared Star Target Detection Based on Maximum Energy in Daytime

Because of many factors, the infrared star images acquired in the daytime have a low signal-to-noise ratio and a nonuniform background. The star targets in the images can not be extracted by using common filtering methods. Currently, the common morphological method is also not ideal for the processing of star images. Firstly, the background characteristics are analyzed and the multi-frame superimposition method is used to reduce the random noise, so as to improve the signal-to-noise ratio. Then, setting a threshold, the background in the superimposed star image is removed and the image only containing targets and noise is obtained. Finally, the star image is processed by using a template similar to the star in size according to certain rules so as to separate the targets. The experimental result shows that this method is more efficient in star target separation.