The picture quality is declined in the low illumination environment. Meanwhile, the fog and haze formed by smoke, dust and other substances suspended in the air will cause blurred image details, which have a great impact on outdoor photography and computer vision. Therefore, it has important application value for image processing and computer vision by defogging degraded images to improve image quality. We propose an image defogging algorithm based on the combination of bright and dark channel in fog and haze weather. A model of the air light scattering is proposed based on the physical model of degraded image. Air light value and transmissivity are estimated by using the combination of light channel prior and dark channel prior. The algorithm can solve color distortion problem of sky area when fog-free image is restored, recover the image details and color, and improve the vision effect of the image. Evaluation parameters are used to compare the image quality. Simulation results show that the algorithm proposed in this paper is better than multi-scale Retinex image defogging algorithm.