Infrared non-uniformity correction method based on binocular detection system without blindsight

The output image of an infrared detector often suffers from non-uniformity due to the inhomogeneity of the device material and limitations in the manufacturing process, which can reduce the detector's capability to detect and identify targets. It is therefore necessary to adequately correct the non-uniformity to fully utilize the high temperature sensitivity of the detector. Calibration-based non-uniformity correction technology is one of the earliest and most effective methods of correcting non-uniformity. Typically, a relatively uniform shutter is used to mask the field of view for calibration correction. However, this process interrupts the observation due to the need for masking, severely limiting its use in real-world projects. In order to maintain the performance superiority of the calibration-based method and eliminate the defect of target loss caused by masking, this paper takes the occlusion calibration as the theoretical basis, which consists of dual detectors to form a binocular detection system, and uses one of the occluded calibration auxiliary detector to assist the other occlusion-free primary detector, and takes advantage of the fact that the radiation is the same when observing the same target at the same time to make the correct response based on the steepest gradient descent learning algorithm, which removes the non-uniformity while achieving detail fidelity, no ghosting and continuous output.