A Fusion-based Enhancement Method for Low-light UAV Images

This paper focuses on the enhancement of low-light UAV images. There are some differences between low-light UAV images and general low-light images. Specifically, low-light UAV images are underexposed as a whole but contain overexposed areas produced by lamplights. In addition, these images have a larger field of vision and therefore contain more information. Based on these characteristics, we propose an enhancement method for low-light UAV images. First, we adopt two different enhancing methods, one is to improve the global brightness, the other enhances the local contrast, and then we use appropriate weights to fuse them to retain their respective advantages. Second, a new detail enhancement strategy is designed to preserve more details of these images. Finally, a brightness and chrominance optimization operation based on linear stretching is used to further optimize the enhanced images. We test the proposed method with three different datasets, including a public UAV dataset, a self-made UAV dataset and a widely used image enhancement dataset. Besides, our enhancement method is compared with several state-of-the-art enhancing methods and evaluated with two image quality assessments. All the experiments demonstrate that the proposed enhancement method is superior to others in enhancing low-light UAV images.