基于三角形循环二分算法的图像去雾研究
|
摘要
为了提高图像去雾效果,采用三角形循环二分算法处理图像。首先分析基本暗通道算法图像去雾;接着基于三角形循环二分算法对大气光值精确计算,将图像沿对角线分成4个三角形区域,只对雾浓度最较高的区域进行二分图形划分,选取三角形最长边的中点,连接到对应三角形最长边的顶点,循环执行直到满足预先设定的面积阈值;然后自适应调节透射率,避免色彩失真;最后给出了算法流程。实验仿真显示,本文算法去雾后的图像在视觉上更加清晰,可见边集合数目比、平均梯度比值、直方图相似度系数、综合评价指标相比其他算法较好,能够满足图像去雾对清晰度、信息量的要求。
In order to improve the quality of image dehazing,the triangle loop dichotomy algorithm is presented.Firstly,the dark channel prior is used to analyze the image dehazing.Secondly,using triangle loop dichotomy algorithm,the atmospheric light value is calculated accurately,the hazing image is divided into four triangular areas along the diagonal line,and the supreme hazing area is dichotomized only,which is selected the midpoint and connected the vertex of the longest side.The cycle execution is ended until satisfying the preset threshold.Thirdly,the adaptive transmission is made to avoid the color distortion.Finally,the algorithm process was given.The simulation results show that the triangle loop dichotomy algorithm is more clear in visual perception after image dehazing,number of edge sets,average gradient,the histogram similarity coefficient and the comprehensive evaluation index are better than other algorithms.It can satisfy the requirements of image clearness and information.
In order to improve the quality of image dehazing,the triangle loop dichotomy algorithm is presented.Firstly,the dark channel prior is used to analyze the image dehazing.Secondly,using triangle loop dichotomy algorithm,the atmospheric light value is calculated accurately,the hazing image is divided into four triangular areas along the diagonal line,and the supreme hazing area is dichotomized only,which is selected the midpoint and connected the vertex of the longest side.The cycle execution is ended until satisfying the preset threshold.Thirdly,the adaptive transmission is made to avoid the color distortion.Finally,the algorithm process was given.The simulation results show that the triangle loop dichotomy algorithm is more clear in visual perception after image dehazing,number of edge sets,average gradient,the histogram similarity coefficient and the comprehensive evaluation index are better than other algorithms.It can satisfy the requirements of image clearness and information.
引文
[1]杨爱萍,白煌煌.基于Retinex理论和暗通道先验的夜间图像去雾算法[J].激光与光电子学进展,2017,54(4):041002.YANG A P,BAI H H.Nighttime image defogging based on the theory of retinex and dark channel prior[J].Laser&Optoelectronics Progress,2017,54(4):041002.(in Chinese)
[2]王凯,王延杰,樊博.基于暗通道先验的图像去雾算法改进[J].液晶与显示,2016,31(8):840-845.WANG K,WANG Y J,FAN B.Improved method for single image dehazing using dark channel prior[J].Chinese Journal of Liquid Crystals and Displays,2016,31(8):840-845.(in Chinese)
[3]LIU C J,CHENG I,ZHANG Y,et al.Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency[J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,128(7):16-26.
[4]GIBSON K B,VO D T,NGUYEN T Q.An investigation of dehazing effects on image and video coding[J].IEEETransactions on Image Processing,2012,21(2):662-73.
[5]TAREL J P,HAUTIERE N.Fast visibility restoration from a single color or gray level image[C]//Procesings of the IEEE12th International Conference on Computer Vision.Kyoto,Japan:IEEE,2009:2201-2208.
[6]张小刚,唐美玲,陈华,等.一种结合双区域滤波和图像融合的单幅图像去雾算法[J].自动化学报,2014,40(8):1733-1739.ZHANG X G,TANG M L,CHEN H,et al.A dehazing method in single image based on double-area filter and image fusion[J].Acta Automatic Sincia,2014,40(8):1733-1739.(in Chinese)
[7]HE K M,SUN J,TANG X O.Single image haze removal using dark channel prior[J].IEEE Transactions on attern Analysis and Machine Intelligence,2011,33(12):2341-2353.
[8]陆健强,王卫星,胡子昂,等.基于改进暗通道先验算法的农田视频实时去雾清晰化系统[J].农业工程学报,2016,32(10):143-148.LU J Q,WANG W X,HU Z A,et al.Real time defogging system used for video image of farmland based on modified dark channel prior algorithm[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(10):143-148.(in Chinese)
[9]杨爱萍,刘华平,何宇清,等.基于暗原色融合和维纳滤波的单幅图像去雾[J].天津大学学报,2016,49(6):574-580.YANG A P,LIU H P,HE Y Q,et al.Single image dehazing based on dark channel fusion and wiener filtering[J].Journal of Tianjin University,2016,49(6):574-580.(in Chinese)
[10]肖杰,李同亮,翟东海.基于局部维纳滤波的交通图像去雾霾算法[J].成都信息工程学院学报,2014,29(6):567-573.XIAO J,LI T L,ZHAI D H.The Traffic image De-haze algorithm based on locally wiener filtering[J].Journal of Chengdu University of Information Technology,2014,29(6):567-573.(in Chinese)
[11]方委,陈林.基于饱和度运算图像去雾算法[J].电视技术,2017,41(3):11-14.FANG W,CHEN L.Image defogging algorithm based on saturation operation[J].Video Engineering,2017,41(3):11-14.(in Chinese)
[2]王凯,王延杰,樊博.基于暗通道先验的图像去雾算法改进[J].液晶与显示,2016,31(8):840-845.WANG K,WANG Y J,FAN B.Improved method for single image dehazing using dark channel prior[J].Chinese Journal of Liquid Crystals and Displays,2016,31(8):840-845.(in Chinese)
[3]LIU C J,CHENG I,ZHANG Y,et al.Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency[J].ISPRS Journal of Photogrammetry and Remote Sensing,2017,128(7):16-26.
[4]GIBSON K B,VO D T,NGUYEN T Q.An investigation of dehazing effects on image and video coding[J].IEEETransactions on Image Processing,2012,21(2):662-73.
[5]TAREL J P,HAUTIERE N.Fast visibility restoration from a single color or gray level image[C]//Procesings of the IEEE12th International Conference on Computer Vision.Kyoto,Japan:IEEE,2009:2201-2208.
[6]张小刚,唐美玲,陈华,等.一种结合双区域滤波和图像融合的单幅图像去雾算法[J].自动化学报,2014,40(8):1733-1739.ZHANG X G,TANG M L,CHEN H,et al.A dehazing method in single image based on double-area filter and image fusion[J].Acta Automatic Sincia,2014,40(8):1733-1739.(in Chinese)
[7]HE K M,SUN J,TANG X O.Single image haze removal using dark channel prior[J].IEEE Transactions on attern Analysis and Machine Intelligence,2011,33(12):2341-2353.
[8]陆健强,王卫星,胡子昂,等.基于改进暗通道先验算法的农田视频实时去雾清晰化系统[J].农业工程学报,2016,32(10):143-148.LU J Q,WANG W X,HU Z A,et al.Real time defogging system used for video image of farmland based on modified dark channel prior algorithm[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(10):143-148.(in Chinese)
[9]杨爱萍,刘华平,何宇清,等.基于暗原色融合和维纳滤波的单幅图像去雾[J].天津大学学报,2016,49(6):574-580.YANG A P,LIU H P,HE Y Q,et al.Single image dehazing based on dark channel fusion and wiener filtering[J].Journal of Tianjin University,2016,49(6):574-580.(in Chinese)
[10]肖杰,李同亮,翟东海.基于局部维纳滤波的交通图像去雾霾算法[J].成都信息工程学院学报,2014,29(6):567-573.XIAO J,LI T L,ZHAI D H.The Traffic image De-haze algorithm based on locally wiener filtering[J].Journal of Chengdu University of Information Technology,2014,29(6):567-573.(in Chinese)
[11]方委,陈林.基于饱和度运算图像去雾算法[J].电视技术,2017,41(3):11-14.FANG W,CHEN L.Image defogging algorithm based on saturation operation[J].Video Engineering,2017,41(3):11-14.(in Chinese)