基于改进分布估计的算法在井下监控系统中的应用研究  

Application research of algorithm based on improved distribution estimation in underground monitoring system

作　　者：梁燕华 芦君珂 田训鹏 LIANG Yanhua;LU Junke;TIAN Xunpeng(School of Electrical and Control Engineering,Heilongjiang University of Science and Technology,Harbin 150022,China)

机构地区：[1]黑龙江科技大学电气与控制工程学院,黑龙江 哈尔滨 150022

出　　处：《中国矿业》2023年第12期92-99,共8页China Mining Magazine

基　　金：黑龙江省自然科学基金项目资助(编号:LH2019E084)。

摘　　要：视频监控系统在煤矿井下综采工作中应用广泛,而视频监控采集图像质量的高低直接决定工作人员安全和生产工作效率。目前,受井下粉尘、水汽和光源分布不均等因素的影响,采集的图像信息存在雾气较大、图像过曝光和对比度低的问题。传统的暗通道先验去雾算法具有计算速度快、修复效果好的优点,广泛应用于井下去雾,但在处理煤矿井下尘雾大、光源分布不均的图像时会导致图像信息大量丢失和光源区域纹理受损等问题。针对这些问题,提出了一种改进透射率分布估计的井下去雾算法。通过利用暗态点光源模型,结合暗通道可信度权值因子和最优暗通道去雾图像,对透射率分布进行改进,对井下有雾图像进行去雾处理。试验结果表明,改进的透射率分布估计去雾算法相较于Retinex算法,峰值信噪比、信息熵、标准差和平均梯度分别提高了16.25%、31.39%、17.17%、48.47%,相较于传统暗通道先验去雾算法分别提高了47.24%、35.24%、21.64%、51.79%。实验数据表明改进的透射率分布估计去雾算法处理后的井下图像纹理细节损失小,对比度和清晰度都得到了有效提升。The video surveillance system is widely used in the comprehensive mining work of coal mines,and the quality of the images captured by video surveillance directly determines the safety and production efficiency of workers.Currently,it is affected by the uneven distribution of dust,water vapor,and light sources in the underground,and the collected image information is prone to problems such as large fog,overexposure,and low contrast,the traditional dark channel prior defogging algorithm has the advantages of fast calculation speed and good repair effect,so it is widely used in underground fog. However, when processing images with large dust and uneven distribution of light sources in coal mines, it can lead to a large amount of image information loss and damage to the texture of the light source area. To address this issue, an improved downhole fog algorithm for estimating the transmittance distribution is proposed. By utilizing a dark point light source model, combining the credibility weight factor of the dark channel with the optimal dark channel defogging image, the transmittance distribution is improved and the underground foggy image is defogged. The experimental results show that the peak signal to noise ratio, information entropy, standard deviation and average gradient of the improved transmission distribution estimation defogging algorithm are 16.25%, 31.39%, 17.17% and 48.47% higher than those of Retinex algorithm, respectively, and 47.24%, 35.24%, 21.64% and 51.79% higher than those of the traditional dark channel prior defogging algorithm. The experimental data shows that the improved transmittance distribution estimation and defogging algorithm reduces the loss of texture details in underground images, and effectively improves the contrast and clarity.

关 键 词：煤矿视频监控图像 尘雾图像去雾 暗通道先验 暗态点光源模型 透射率分布估计 

分 类 号：TD67[矿业工程—矿山机电]