A haze removal method for unmanned aerial vehicle images based on robust estimation of atmospheric light

Aimed at the problem that the quality of the images acquired by unmanned aerial vehicle (UAV) is easily reduced due to the fog or haze weather, a haze removal algorithm for UAV images based on robust estimation of atmospheric light was proposed. The proposed algorithm selects image patches with different surface reflectance rate to obtain the pixel line of each patch. Using the properties that all the pixel lines are coplanar with the atmospheric light, the orientation of the atmospheric light vector was calculated. Based on the fact that scene depths of each pixel in the image are similar, the global transmittance is defined. The amplitude of the atmospheric light and the dehazed image are obtained using the global transmittance and projection of the pixel lines on the direction of the atmospheric light. In order to apply this method to different types of images, the measures of automatic adjustment of image block size and condition threshold were adopted to improve the robustness of the algorithm. The experimental results with the real UAV images show that the proposed algorithm has a great improvement in the visual effect and objective evaluation index compared with the existing methods.