Image dehazing algorithm based on airport image quality evaluation

Heavy hazy weather blurs airport or target images obtained through visible light photoelectricity sensors, and hazy images reduce the efficiency of target recognition. With the deployment of panoramic systems and takeoff and landing monitoring systems in the test field, the research on image dehazing algorithms has increasingly crucial theoretical significance and practical application value. In this paper, we propose an image dehazing method based on the Double Discriminator Generative Adversarial Network (DDGAN-DF), which generates multi-layer semantic awareness and produces highquality, reliable haze-free images.