Signal-to-noise analysis of point target detection using image pixel binning for space-based infrared electro-optical systems

Abstract

It is well known that pixel binning is an effective method for improving the signal-to-noise ratio (SNR) of silicon detectors. It has found extensive use in the study of spectroscopy, astronomy, and in the development of numerous image processing algorithms. However, the positive impact of binning technique on SNR does not happen at any moment. In this paper, we model the scenario of the detection of the point target. Our study analyzes the effects of variables such as encircled energy (EE), target motion velocity, and integration time on the imaging process. For different detection scenarios, we quantitatively discussed the degree of improvement in SNR of image pixel binning technique for detecting point targets. Based on actual 3483 point target imaging data collected, the model was validated with an average error of 0.016. A wide range of detection scenarios is covered by the proposed model with high accuracy, providing a useful reference for the design of electro-optical systems.