Nighttime low-light image enhancement and object detection based on knowledge distillation

In order to enhance the quality of nighttime low-light image, improve the accuracy of the object detection model under the nighttime low-light condition and reduce the calculation cost of the model, a multi-task model for nighttime low-light image enhancement and object detection based on knowledge distillation and data enhancement was proposed. Knowledge distillation was performed based on the high-quality image model, and the feature information of the high-quality image was used to guide the model training, so that the model could extract the feature information similar to that of the high-quality image in the nighttime low-light images. These feature information could be used to achieve enhancement of image contrast, denoising and objects detection. The experimental results show that the proposed distillation method can improve the object detection accuracy of nighttime low-light by 16.58%, and the image enhanced by this method can achieve the effect of mainstream image enhancement based on deep learning.