颜色一致性的无人机航拍低光照图像增强算法

To address the issue of low brightness and poor visual effect of unmanned aerial vehicles (UAVs) in low illumination conditions, this paper established a low illumination dataset of UAV aerial photography and proposed a low illumination image enhancement algorithm for UAV aerial photography with color consistency. Firstly, in the brightness enhancement stage, this paper constructed a brightness enhancement network (BENet) to enhance the brightness of images and used the color network (CNet) module and the pyramid color embedding (PCE) module to combine the color features and content features of the images, which avoided color distortion in the enhanced image. In the image correction stage, this paper constructed a correction network based on domain transmission, trained the network with the self-built dataset, corrected the enhanced image after the first stage with the help of well-illuminated images, reduced the effect of noise on the image, and finally obtained the enhanced image. The experimental results show that the algorithm effectively avoids the problems of color distortion and noise amplification while enhancing the image brightness, and it outperforms other advanced algorithms in terms of objective indicators and improves the detection performance of the target detection algorithm at night.