Review of infrared object detection algorithms for low-light background

Abstract

At present, object detection algorithm using artificial intelligence technology plays an increasingly important role in the field of computer vision, and plays an extremely important role in such practical application scenarios as automatic driving, urban monitoring, national defense, military and medical assistance. Different from visible light imaging, infrared imaging technology uses detectors to measure the infrared radiation difference between the object itself and the background, overcoming the difficulty of low light intensity and realizing infrared object detection in the low-light scene. In this paper, the traditional infrared object detection algorithm for low light background and infrared object detection algorithm based on deep learning are reviewed, and the current representative classical algorithms are compared, and the characteristics of the model combined with the actual application scenarios are analyzed. Finally, the difficulties and challenges that the current infrared object detection task facing are described, and the research direction of infrared object detection is prospected.