An Automatic Recognition and Positioning Method for Point Source Targets on Satellite Images

• Main Authors: Kai Li, Yongsheng Zhang, Zhenchao Zhang, Ying Yu
• Format: Article
• Language: English
• Published: MDPI AG 2018-11-01
• Series: ISPRS International Journal of Geo-Information
• Subjects: point source targets; automatic recognition and positioning; Point Spread Function; feature parameter; joint geometric and radiometric calibration
• Online Access: https://www.mdpi.com/2220-9964/7/11/434

Currently, the geometric and radiometric calibration of on-board satellite sensors utilizes different ground targets using some form of manual intervention. Point source targets provide high precision geometric and radiometric information and have the potential to become a new tool for joint geometric and radiometric calibration. In this paper, an automatic recognition and positioning method for point source target images is proposed. First, the template matching method was used to effectively reduce nonpoint source target image pixels in the satellite imagery. The point source target images were then identified using particular feature parameters. Using the template matching method, the weighted centroid method, and the Gaussian fitting method, the positions of the centroid of the point source target images were calculated. The maximum position detection error obtained using the three methods was 0.07 pixels, which is comparably better than artificial targets currently in use. The experimental results show point source targets provide high precision geometric information, which can become a suitable alternative for automatic joint geometric and radiometric calibration of spaceborne optical sensors.