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基于暗原色理论和自适应双边滤波的煤矿尘雾图像增强算法
引用本文:杜明本,陈立潮,潘理虎.基于暗原色理论和自适应双边滤波的煤矿尘雾图像增强算法[J].计算机应用,2015,35(5):1435-1438.
作者姓名:杜明本  陈立潮  潘理虎
作者单位:太原科技大学 计算机科学与技术学院, 太原 030024
基金项目:山西省科技重大专项,山西省科技攻关项目,山西省留学人员科研资助项目
摘    要:针对煤矿井下存在大量煤尘、水雾导致获取的视频图像伴有大量的噪声、分辨率低、模糊的问题,提出了一种基于暗原色理论和自适应双边滤波的煤矿尘雾图像增强算法.基于暗原色先验理论,采用自适应双边滤波代替softmatting过程来求取精细透射率图,并根据煤矿井下特殊环境,从新的角度求取全球大气光值、粗略透射率图,并根据图像退化模型实现图像的去噪.实验结果表明,对于分辨率为1024×576的图像处理时间为1.9s,与He算法(HE K, SUN J, TANG X. Single image haze removal using dark channel prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011,33(12):1-13.)相比,运行效率提高了5倍.与直方图均衡法等算法相比,所提算法有效增强了图像细节、边缘,整体上更加适合人类视觉和视频监控的要求.

关 键 词:暗原色先验理论    自适应双边滤波    图像去雾    介质传播函数    大气物理散射模型
收稿时间:2014-12-15
修稿时间:2015-01-23

Enhancement algorithm for fog and dust images in coal mine based on dark channel prior theory and bilateral adaptive filter
DU Mingben,CHEN Lichao,PAN Lihu.Enhancement algorithm for fog and dust images in coal mine based on dark channel prior theory and bilateral adaptive filter[J].journal of Computer Applications,2015,35(5):1435-1438.
Authors:DU Mingben  CHEN Lichao  PAN Lihu
Affiliation:School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan Shanxi 030024, China
Abstract:Concerning the problem that videos images captured from coal mines filled with coal dust and mist are often with quality problems such as lots of noise, low resolution and blur. To solve this problem, an enhancement algorithm for fog and dust images in coal mine based on dark channel prior theory and bilateral adaptive filter was proposed. On the basis of dark channel prior, the softmatting process was replaced with the adaptive bilateral filtering to obtain fine transmittance map. Then according to the special circumstances of coal mines, the global atmosphere light and the rough transmittance map were got from new perspective and image denoising was realized on the basis of the image degradation model. The experiment results show that the image processing time for a resolution of 1024×576 is 1.9 s. Compared with He algorithm (HE K, SUN J, TANG X. Single image haze removal using dark channel prior. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011,33(12):1-13.), the efficiency increased 5 times.Compared with other algorithms such as histogram equalization method, the proposed algorithm is effective to enhance the image detail. In this way, images can be more suitable for human vision as a whole.
Keywords:dark channel prior theory  bilateral adaptive filtering  fog removing of image  medium transmission function  atmospheric scattering model
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