基于照度调整的矿井非均匀照度视频图像增强算法
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摘要
由于煤矿井下空间环境受粉尘等因素的影响,视频监控系统获取的作业环境图像存在照度低、照度不均匀等问题,而且现有的算法在处理煤矿非均匀照度图像时会出现颜色失真或者过增强现象,这不利于对图像的判读和应用。结合煤矿的实际数据,提出了一种新的图像增强算法,克服了现有算法存在的问题:分析井下视频图像特点,采用具有边缘保持特性的多尺度引导滤波获取照度分量;基于Retinex理论,将图像分解为照度分量与反射分量;针对照度不均匀的特性,提出一种新的"S型"曲线函数对其进行调整;分析图像的特性,引入受限对比度自适应直方图对其对比度进行增强;提出新的图像增强模型,利用细节增强系数和照度增强系数实现对图像的综合增强。与其他4种算法的对比试验表明,本文算法在主观评价和客观评价方面都优于上述算法。实验证明,本算法具有有效提升图像整体亮度和对比度,同时避免光源附近亮区域的过增强现象的特点,能够满足矿山实际应用需求。
Due to the environment of coal mine space is affected by grime, the images obtained by video surveillance have low illumination, non-uniform illuminance problems, and the existing algorithms cause color distortion or excessive enhancement in dealing with non-uniform illumination mine image,which is not conducive to the interpretation and application of images. With the actual images data,this paper proposed a new non-uniform image enhancement algorithm based on illumination adjustment combining with Guided Filtering and "S Curve" function, which may overcome the problems of the existing algorithms. By analyzing the characteristics of the video images,a multi-scale guide filtering,which can preserve the edges and corners,is adopted to get the illumination component. Then based on Retinex theory,the image is decomposed into an illuminance component and a reflection component. Regarding the non-uniform illumination,a new S-shape curve function is proposed to adjust the illuminance component. Considering the image has a relative low contrast,the contrast limited adaptive histogram is further used to enhance the contrast. Finally,a new image enhancement method is proposed with the detail enhancement coefficient and the illumination enhancement coefficient achieve a better enhancement performance of non-uniform images. Compared with the other four algorithms,this paper shows that the proposed algorithm is superior to the above algorithms both in subjective evaluation and objective evaluation. Finally,this algorithm can effectively enhance the overall image brightness and contrast,while avoiding excessive enhancement phenomenon of the bright region generated near the light, showing the superiority of the algorithm.
Due to the environment of coal mine space is affected by grime, the images obtained by video surveillance have low illumination, non-uniform illuminance problems, and the existing algorithms cause color distortion or excessive enhancement in dealing with non-uniform illumination mine image,which is not conducive to the interpretation and application of images. With the actual images data,this paper proposed a new non-uniform image enhancement algorithm based on illumination adjustment combining with Guided Filtering and "S Curve" function, which may overcome the problems of the existing algorithms. By analyzing the characteristics of the video images,a multi-scale guide filtering,which can preserve the edges and corners,is adopted to get the illumination component. Then based on Retinex theory,the image is decomposed into an illuminance component and a reflection component. Regarding the non-uniform illumination,a new S-shape curve function is proposed to adjust the illuminance component. Considering the image has a relative low contrast,the contrast limited adaptive histogram is further used to enhance the contrast. Finally,a new image enhancement method is proposed with the detail enhancement coefficient and the illumination enhancement coefficient achieve a better enhancement performance of non-uniform images. Compared with the other four algorithms,this paper shows that the proposed algorithm is superior to the above algorithms both in subjective evaluation and objective evaluation. Finally,this algorithm can effectively enhance the overall image brightness and contrast,while avoiding excessive enhancement phenomenon of the bright region generated near the light, showing the superiority of the algorithm.
引文
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[19]王小明,黄昶,李全彬,等.改进的多尺度Retinex图像增强算法[J].计算机应用,2010,30(8):2091-2093.WANG Xiaoming,HUANG Chang,LI Quanbin,et al.Improved multi-scale retinex image enhancement algorithm[J].Journal of Computer Applications,2010,30(8):2091-2093.
[20]刘志成,王殿伟,刘颖,等.基于二维伽马函数的光照不均匀图像自适应校正算法[J].北京理工大学学报,2016,36(2):191-LIU Zhicheng,WANG Dianwei,LIU Ying,et al.Adaptive adjustment algorithm for non-uniform illumination images based on2d Gamma function[J].Transactions of Beijing Institute of Technology,2016,36(2):191-196.
[2]WANG Jinhua.Development and prospect on fully mechanized mining in Chinese coal mines[J].International Journal of Coal Science&Technology,2014,1(3):153-260.
[3]KHAN Mohammad Farhan,KHAN E,ABBASI Z A.Image contrast enhancement using normalized histogram equalization[J].Optik-International Journal for Light and Electron Optics,2015,126(24):4868-4875.
[4]COOPER,TED J,BAQAI F A.Analysis and extensions of the Frankle-Mc Cann Retinex algorithm[J].Journal of Electronic Imaging,2004,13:85-92.
[5]YIN Jingcao,LI H,DU J,et al.Low illumination image Retinex enhancement algorithm based on guided filtering[A].Cloud Compu-ting and Intelligence Systems(CCIS),2014 IEEE 3rd International Conference on[C].2014.
[6]DENG Guang.A generalized unsharp masking algorithm[J].IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society,2011,20(5):1249-1261.
[7]黄向东,邓莉洁.一种基于Relinex的矿井非均匀照度图像增强算法[J].科学技术与工程,2014,14(5):141-144.HUANG Xiangdong,DENG Lijie.Algorithm of mine non-uniform illumination image enhancement based on Retinex[J].Science Technology and Engineering,2014,14(5):141-144.
[8]程德强,郑珍,姜海龙.一种煤矿井下图像增强算法[J].工矿自动化,2015,41(12):31-34.CHENG Deqiang,ZHENG Zhen,JIANG Hailong.An image enhancement algorithm for coal mine underground[J].Industry and Mine Automation,2015,41(12):31-34.
[9]徐辉,贺耀宜.一种煤矿井下监控视频图像预处理方法[J].工矿自动化,2016,42(1):32-34.XU Hui,HE Yaoyi.An image preprocessing method for underground monitoring video[J].Industry and Mine Automation,2016,42(1):32-34.
[10]王焱,关南楠,刘海涛.改进的多尺度Retinex井下图像增强算法[J].辽宁工程技术大学学报:自然科学版,2016,35(4):440-443.WANG Yan,GUAN Nannan,LIU Haitao.An improved multi-scale Retinex algorithm for mine image enhancement[J].Journal of Liaoning Technical University(Natural Science),2016,35(4):440-443.
[11]RAHMAN Z U,JOBSON D J,WOODELL G A.Multi-scale retinex for color image enhancement[A].International Conference on IMAGE Processing IEEE[C].1996:1003-1006.
[12]JIANG B,WOODELL G A,JOBSON D J.Novel multi-scale retinex with color restoration on graphics processing unit[J].Journal of Real-Time Image Processing,2014,10(2):239-253.
[13]HE K,SUN J,TANG X.Guided image filtering[J].IEEE Transactions on Pattern Analysis&Machine Intelligence,2010,35(6):1397-1409.
[14]LI Y,GUO F,TAN R T,et al.A contrast enhancement framework with JPEG artifacts suppression[M].Computer VisionECCV,Springer International Publishing,2014:174-188.
[15]ZUIDERVELD K.Contrast limited adaptive histogram equalization[A].Academic Press Professional[C].1994:474-485.
[16]王红,何小海,杨晓敏.基于模糊理论和CLAHE的雾天图像自适应清晰化算法[J].微电子学与计算机,2012,29(1):32-34.WANG Hong,HE Xiaohai,YANG Xiaomin.An adaptive foggy image enhancement algorithm based on fuzzy theory and CLAHE[J].Microelectronics&Computer,2012,29(1):32-34.
[17]SHIN Y,JEONG S,LEE S.Efficient naturalness restoration for nonuniform illumination images[J].IET Image Processing,2015,9(8):662-671.
[18]WANG S,ZHENG J,HU H M,et al.Naturalness preserved enhancement algorithm for non-uniform illumination images[J].IEEE Transactions on Image Processing a Publication of the IEEE Signal Processing Society,2013,22(9):3538-3548.
[19]王小明,黄昶,李全彬,等.改进的多尺度Retinex图像增强算法[J].计算机应用,2010,30(8):2091-2093.WANG Xiaoming,HUANG Chang,LI Quanbin,et al.Improved multi-scale retinex image enhancement algorithm[J].Journal of Computer Applications,2010,30(8):2091-2093.
[20]刘志成,王殿伟,刘颖,等.基于二维伽马函数的光照不均匀图像自适应校正算法[J].北京理工大学学报,2016,36(2):191-LIU Zhicheng,WANG Dianwei,LIU Ying,et al.Adaptive adjustment algorithm for non-uniform illumination images based on2d Gamma function[J].Transactions of Beijing Institute of Technology,2016,36(2):191-196.