基于暗通道先验的无人机图像去雾算法研究  

An Method of Image Haze Removal by Dark Channel Prior for UAV

作　　者：纪红霞[1] 姚军[2] 潘延鹏 舒伟[2] 

机构地区：[1]北京航空航天大学 [2]中国人民解放军95894部队

出　　处：《光学与光电技术》2016年第5期53-56,共4页Optics & Optoelectronic Technology

基　　金：军内科研基金(2015040411××××××)资助项目

摘　　要：对于单幅图像去雾处理,暗通道先验算法具有较好的效果,但该算法处理时间长,对储存资源与计算资源要求很高,很难应用于无人机图像去雾。在暗通道先验算法的基础上进行改进,提出了一种快速的去雾算法,首先通过优化滤波器直接获得高精度的透射率,避免了原算法后续的抠图处理,显著降低了计算复杂度;然后针对去雾图像偏暗、灰度分布偏离原始图像的情况,以原始图为参考,采用直方图规定化方法进行增强处理,提高了亮度,改善了去雾图像的视觉效果,与He算法相比,该算法不仅极大地降低了计算复杂度,速度提高了近5倍,而且保持了原始算法的去雾能力。While the dark channel prior algorithm works well for single image haze removal,it has to take long time to process and require expensive computational overhead and huge memory resource.In this paper,a fast daze removal algorithm is proposed based on dark channel prior knowledge.In the proposed approach,the structure of dark channel filter is designed to estimate refined transmission rate instead of the original soft-matting operator,which will substantially reduce the computational complexity.To deal with the invalid case of the proposed method,the histogram specification is used based on original image to enhance brightness and optimize gray distribution of haze-free image,which improves the visual effect of defogging images.Compared with He＇s algorithm,the proposed approach is equaled to the original algorithm in daze removal effect,and has about five times shorter processing time.

关 键 词：无人机 图像去雾 暗通道先验 直方图规定化 

分 类 号：TN911.73[电子电信—通信与信息系统]