Unmanned aerial vehicle system (UAVs) imaging has become a challenging area of research due to the dynamic atmospheric environment. The images captured by UAVs are often deteriorated by factors such as clouds occlusion, poor atmospheric illumination, and limited capability of the imaging system. To tackle problems, this paper presents a novel visibility restoration scheme for UAVs images by considering the following two assumptions: (1) The actual scene radiance of a UAVs image is bounded. (2) Pixels sharing the same appearance must have the same transmission value in a local neighborhood. Inspired by above assumptions, an image boundary constraint utilizing the median filter has been imposed on the RGB channel for the rough estimation of transmission-map in aerial images. Furthermore, a graph-model based optimization technique has been used for the transmission-map refinement. The experimental results demonstrate the efficiency of the proposed method in terms of metrics correspond to the human-visual-system (HVS).

由于动态大气环境，无人飞行器系统（UAV）成像已成为研究的挑战领域。UAV捕获的图像通常会因云团遮挡，恶劣的大气照度和成像系统功能受限等因素而劣化。针对这些问题，本文提出了一种新颖的无人机图像能见度恢复方案，其中考虑了以下两个假设：（1）限制了无人机图像的实际场景辐射度。（2）具有相同外观的像素在本地附近必须具有相同的透射值。受以上假设的启发，利用中值滤波器的图像边界约束已施加到RGB通道上，以粗略估计航空图像中的透射图。此外，基于图模型的优化技术已用于透射图的优化。实验结果证明了该方法在度量标准方面的有效性，该度量对应于人类视觉系统（HVS）。