一种基于大气散射模型和Retinex的红外图像去雾算法
|
摘要
基于红外图像和可见光图像在有雾天气下退化过程中的相似性,可以使用大气散射模型对红外图像进行图像复原。但是图像在去雾复原处理后常常会有对比度低,细节不明显的特点,不利于人眼直接观察。针对这一情况,使用Retinex对去雾后的图像进行对比度增强。经过这两个算法处理后可以提高红外图像的对比度,突出其细节,提高其信噪比,并且具有良好的视觉效果。对算法的改进可以在计算处理速度和算法处理的效果上找到一个平衡点,为后期的嵌入式平台实现实时的视频去雾打下基础。
According to the similarities between the image degradation in infrared and visible light images in foggy weather, we can defog foggy infrared images by using an atmospheric scattering model. However,after the image is defogged, the image often has low contrast and inconspicuous details, which is not conducive to direct observation by humans. To combat this, the Retinex algorithm was used to enhance the contrast of the image after defogging. Processing the image with these two methods can improve its contrast, highlight its details, improve the signal to noise ratio, and have a good visual effect. Improvements to the algorithm can be aimed towards balancing the calculation speed and the processing effect, while laying the foundation for real-time video defogging in embedded platforms in the future.
According to the similarities between the image degradation in infrared and visible light images in foggy weather, we can defog foggy infrared images by using an atmospheric scattering model. However,after the image is defogged, the image often has low contrast and inconspicuous details, which is not conducive to direct observation by humans. To combat this, the Retinex algorithm was used to enhance the contrast of the image after defogging. Processing the image with these two methods can improve its contrast, highlight its details, improve the signal to noise ratio, and have a good visual effect. Improvements to the algorithm can be aimed towards balancing the calculation speed and the processing effect, while laying the foundation for real-time video defogging in embedded platforms in the future.
引文
[1]陈钱.红外图像处理技术现状及发展趋势[J].红外技术,2013,35(6):311-318.CHEN Qian.Status and development trend of infrared image processing technology[J].Infrared Technology,2013,35(6):311-318.
[2]金伟其,刘斌,范永杰,等.红外图像细节增强技术研究进展[J].红外与激光工程,2011,40(12):2521-2527.JIN Weiqi,LIU Bin,FAN Yongjie,et al.Research progress of infrared image detail enhancement technology[J].Infrared and Laser Engineering,2011,40(12):2521-2527.
[3]李毅,张云峰,张强,等.基于去雾模型的红外图像对比度增强[J].中国激光,2015,42(1):298-306.LI Yi,ZHANG Yunfeng,ZHANG Qiang,et al.Contrast enhancement of infrared image based on defogging model[J].Chinese Journal of Lasers,2015,42(1):298-306.
[4]Mccartney E J.Scattering phenomena(Book Reviews:Optics of the Atmosphere,Scattering by Molecules and Particles)[J].Science,1977,196:1084-1085.
[5]周国辉,刘湘伟,徐记伟.一种计算红外辐射大气透过率的数学模型[J].红外技术,2008,30(6):331-334.ZHOU Guohui,LIU Xiangwei,XU Jiwei.A mathematical model for calculating the atmospheric transmittance of infrared radiation[J].Infrared Technology,2008,30(6):331-334.
[6]曹慧,张宝辉,陈磊,等.基于伪暗原色的红外增强技术研究[J].红外技术,2016,38(6):476-480.CAO Hui,ZHANG Baohui,CHEN Lei,et al.Research on infrared enhancement technology based on pseudo dark primary color[J].Infrared Technology,2016,38(6):476-480.
[7]Narasimhan S G,Nayar S K.Removing weather affects from monochrome images[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2001:186-193.
[8]Tan K K,Oakley J P.Physics-based approach to color image enhancement in poor visibility conditions[J].Journal of the Optical Society of America A Optics Image Science&Vision,2001,18(10):2460-2467.
[9]Kim Jinhwan,JANG Wondong,Sim Jaeyoung.Optimized contrast enhancement for real-time image and video dehazing[J].Journal of Visual Communication and Image Representation,24(3):410-425.
[10]HE Kaiming,SUN Jian,TANG Xiaoou.Single image haze removal using dark channel prior[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition,2009:1956-1963.
[11]刘倩,陈茂银,周东华.基于单幅图像的快速去雾算法[C]//第25届中国控制与决策会议,2013:3780-3785.LIU Qian,CHEN Maoyin,ZHOU Donghua.Fast dehazing algorithm based on single image[C]//The 25th China Control and Decision Conference,2013:3780-3785.
[12]Land E,McCann J J.Lightness and retinex theory[J].Journal of the Optical Society of America,1971,61(1):1-11.
[13]Jobson D J,Rahman Z,Woodell G A.Properties and performance of a center/surround retinex[J].IEEE Trans.Image Process,1997(6):451-462.
[14]Barnard K,Funt B.Investigations into Multi-Scale Retinex[C]//Proc.of Colour Imaging in Multimedia,1998:9-17..
[15]嵇晓强.图像快速去雾与清晰度恢复技术研究[D].长春:长春光学精密机械与物理研究所,2012.YAN Xiaoqiang.Research on image fast dehazing and sharpness restoration technology[D].Changchun:Changchun Institute of Optics,Fine Mechanics and Physics,2012.
[16]李大鹏,禹晶,肖创柏.图像去雾的无参考客观质量评测方法[J].中国图象图形学报,2011,16(9):1753-1757.LI Dapeng,YU Jing,XIAO Chuangbai.Non-reference objective quality evaluation method for image dehazing[J].Journal of Image and Graphics,2011,16(9):1753-1757.
[17]吴迪,朱青松.图像去雾的最新研究进展[J].自动化学报,2015,41(2):221-239.WU Di,ZHU Qingsong.Recent progress in image dehazing[J].Acta Automatica Sinica,2015,41(2):221-239.
[18]WANG Z,Bovik A C,Sheikh H R,et al.Image quality assessment:from error visibility to structural similarity[J].IEEE Transactions on Image Processing,2004,13(4):600-612.
[19]Hautiere N,Tarel J-p,Aubert D,et al.Blind contrast enhancement assessment by gradient ratioing at visible edges[J].Image Analysis&Stereology Journal,2008,27(2):87-95.
[2]金伟其,刘斌,范永杰,等.红外图像细节增强技术研究进展[J].红外与激光工程,2011,40(12):2521-2527.JIN Weiqi,LIU Bin,FAN Yongjie,et al.Research progress of infrared image detail enhancement technology[J].Infrared and Laser Engineering,2011,40(12):2521-2527.
[3]李毅,张云峰,张强,等.基于去雾模型的红外图像对比度增强[J].中国激光,2015,42(1):298-306.LI Yi,ZHANG Yunfeng,ZHANG Qiang,et al.Contrast enhancement of infrared image based on defogging model[J].Chinese Journal of Lasers,2015,42(1):298-306.
[4]Mccartney E J.Scattering phenomena(Book Reviews:Optics of the Atmosphere,Scattering by Molecules and Particles)[J].Science,1977,196:1084-1085.
[5]周国辉,刘湘伟,徐记伟.一种计算红外辐射大气透过率的数学模型[J].红外技术,2008,30(6):331-334.ZHOU Guohui,LIU Xiangwei,XU Jiwei.A mathematical model for calculating the atmospheric transmittance of infrared radiation[J].Infrared Technology,2008,30(6):331-334.
[6]曹慧,张宝辉,陈磊,等.基于伪暗原色的红外增强技术研究[J].红外技术,2016,38(6):476-480.CAO Hui,ZHANG Baohui,CHEN Lei,et al.Research on infrared enhancement technology based on pseudo dark primary color[J].Infrared Technology,2016,38(6):476-480.
[7]Narasimhan S G,Nayar S K.Removing weather affects from monochrome images[C]//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2001:186-193.
[8]Tan K K,Oakley J P.Physics-based approach to color image enhancement in poor visibility conditions[J].Journal of the Optical Society of America A Optics Image Science&Vision,2001,18(10):2460-2467.
[9]Kim Jinhwan,JANG Wondong,Sim Jaeyoung.Optimized contrast enhancement for real-time image and video dehazing[J].Journal of Visual Communication and Image Representation,24(3):410-425.
[10]HE Kaiming,SUN Jian,TANG Xiaoou.Single image haze removal using dark channel prior[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition,2009:1956-1963.
[11]刘倩,陈茂银,周东华.基于单幅图像的快速去雾算法[C]//第25届中国控制与决策会议,2013:3780-3785.LIU Qian,CHEN Maoyin,ZHOU Donghua.Fast dehazing algorithm based on single image[C]//The 25th China Control and Decision Conference,2013:3780-3785.
[12]Land E,McCann J J.Lightness and retinex theory[J].Journal of the Optical Society of America,1971,61(1):1-11.
[13]Jobson D J,Rahman Z,Woodell G A.Properties and performance of a center/surround retinex[J].IEEE Trans.Image Process,1997(6):451-462.
[14]Barnard K,Funt B.Investigations into Multi-Scale Retinex[C]//Proc.of Colour Imaging in Multimedia,1998:9-17..
[15]嵇晓强.图像快速去雾与清晰度恢复技术研究[D].长春:长春光学精密机械与物理研究所,2012.YAN Xiaoqiang.Research on image fast dehazing and sharpness restoration technology[D].Changchun:Changchun Institute of Optics,Fine Mechanics and Physics,2012.
[16]李大鹏,禹晶,肖创柏.图像去雾的无参考客观质量评测方法[J].中国图象图形学报,2011,16(9):1753-1757.LI Dapeng,YU Jing,XIAO Chuangbai.Non-reference objective quality evaluation method for image dehazing[J].Journal of Image and Graphics,2011,16(9):1753-1757.
[17]吴迪,朱青松.图像去雾的最新研究进展[J].自动化学报,2015,41(2):221-239.WU Di,ZHU Qingsong.Recent progress in image dehazing[J].Acta Automatica Sinica,2015,41(2):221-239.
[18]WANG Z,Bovik A C,Sheikh H R,et al.Image quality assessment:from error visibility to structural similarity[J].IEEE Transactions on Image Processing,2004,13(4):600-612.
[19]Hautiere N,Tarel J-p,Aubert D,et al.Blind contrast enhancement assessment by gradient ratioing at visible edges[J].Image Analysis&Stereology Journal,2008,27(2):87-95.