基于暗原色先验的单幅图像去雾优化技术
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摘要
雾霾等粒子的大气散射作用会使得图像采集设备所获取的图像质量下降,影响后续工作。基于暗原色先验理论提出一种单幅图像的去雾优化技术。针对景深突变处出现的"白边"与"黑化"现象,提出结合最小值滤波与中值滤波的粗估计透射率优化方法。并提出自适应限定透射率下限值的方法改善天空区域的颜色失真问题。实验结果表明,该算法在去雾效果及自适应性方面优于对比算法。
The atmospheric scattering of particles such as fog will make the image quality of the image acquisition equipment decrease,which will affect the follow-up work. Based on the theory of dark channel prior,an image dehazing optimization technique for single image is proposed. According to the depth of mutation appear at the"white"and"black"phenomenon,combining with the minimum value of the transmittance optimization method of coarse estimation filtering and median filtering. A method of adaptively defining the lower limit of transmittance is proposed to improve the color distortion problem in the sky region. The experimental results show that the algorithm is superior to the contrast algorithm in haze removal and self-adaptation.
The atmospheric scattering of particles such as fog will make the image quality of the image acquisition equipment decrease,which will affect the follow-up work. Based on the theory of dark channel prior,an image dehazing optimization technique for single image is proposed. According to the depth of mutation appear at the"white"and"black"phenomenon,combining with the minimum value of the transmittance optimization method of coarse estimation filtering and median filtering. A method of adaptively defining the lower limit of transmittance is proposed to improve the color distortion problem in the sky region. The experimental results show that the algorithm is superior to the contrast algorithm in haze removal and self-adaptation.
引文
[1]赵宏宇.雾天图像清晰化技术的研究[D].北京:北京工业大学,2015.
[2]申怀波,王永康,张孝峥.基于暗原色先验的图像去雾优化技术[J].火力与指挥控制,2016,41(7):157-160.
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[5]GIBSON K B,VO D T,NGUYEN T Q.An investigation of dehazing effects on image and video coding[J].IEEE Transactions on Image Processing,2012,21(2):662-673.
[6]肖进胜,高威,邹白昱,等.基于天空约束暗通道先验的图像去雾[J].电子学报,2017,45(2):346-352.
[7]龚昌来,罗聪.一种改进的容差机制图像去雾算法[J].液晶与显示,2016,31(11):1098-1104.
[8]陈建鹏,毕笃彦,熊磊,等.基于双重域的图像去雾新算法[J].电光与控制,2015,22(6):17-20.
[2]申怀波,王永康,张孝峥.基于暗原色先验的图像去雾优化技术[J].火力与指挥控制,2016,41(7):157-160.
[3]HE K,SUN J,TANG X.Single image haze removal using dark channel prior[J].IEEE Transactions on Pattern Analysis&Machine Intelligence,2011,33(12):2341-2353.
[4]HE K,SUN J,TANG X.Guided image filtering[J].IEEETransactions on Pattern Analysis&Machine Intelligence,2013,35(6):1397-1409.
[5]GIBSON K B,VO D T,NGUYEN T Q.An investigation of dehazing effects on image and video coding[J].IEEE Transactions on Image Processing,2012,21(2):662-673.
[6]肖进胜,高威,邹白昱,等.基于天空约束暗通道先验的图像去雾[J].电子学报,2017,45(2):346-352.
[7]龚昌来,罗聪.一种改进的容差机制图像去雾算法[J].液晶与显示,2016,31(11):1098-1104.
[8]陈建鹏,毕笃彦,熊磊,等.基于双重域的图像去雾新算法[J].电光与控制,2015,22(6):17-20.