All-day astronomical measurement system daytime star point extraction method

Under daylight conditions, infrared star maps taken by all-day astronomical measurement systems are characterized by high background noise and low signal-to-noise (SNR) ratios. Notably, the accuracy of infrared star point centroid extraction directly affects astronomical measurement system indicators. Traditional infrared star map processing methods focus on SNR enhancement and star point detection but do not fully consider star point irregularities. Notably, SNR ratio enhancements easily alter star point energy distributions, seriously limiting the accuracy of centroid extraction. This study provides a novel method for meeting the high-precision requirements of centroid star point extraction from all-day astronomical measurement systems. First, we extract suspected star point boundaries using the background prediction method. Then, we expand the suspected boundaries using an expansion algorithm for improved accuracy. Finally, we superimpose the multi-frame star map extracted by the expanded boundaries to avoid the SNR increase inherent in traditional superimposed infrared star maps. The superimposition also solves the problem of irregular single-frame star point imaging. Experiments show that the extraction accuracy of our method is 69.2, 73.9, and 33.3% higher than contemporary adaptive threshold segmentation, background prediction, and multi-frame superposition methods, respectively. There are also clear improvements in the success rate of star point extraction.