基于Python的夜间图像增强方法研究
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摘要
数字图像广泛应用于生活娱乐、医学、交通等领域,由于光照不均匀和光照强度不够等自然环境、拍摄技术和设备的限制,有些获取的夜间图像对比度低、色彩偏暗、细节缺失严重,且含有大量噪声,影响图像的辨识度和质量,极大的影响了视觉体验.针对该问题,本文分析了基于Retinex和去雾理论的夜间图像增强算法,提高夜间图像的亮度和对比度,提升图像的可视化效果;运用Python语言实现了MSRCR、MSRCP以及基于去雾理论的增强算法.研究结果表明,对夜间图像进行增强处理后,能极大地提高图像的可视化效果.
Digital images are widely used in the fields of life entertainment,medicine,transportation,etc.Due to the limitations of natural environment,shooting technology and equipment such as uneven illumination and insufficient light intensity,some acquired nighttime images have low contrast,dark colors and serious lack of details and contain a lot of noise,which affect the recognition and quality of the image and the visual experience.Aiming at this problem,this paper analyzes the nighttime image enhancement algorithm based on Retinex and dehazing theory,improves the brightness and contrast of nighttime images,and enhances the visualization of images.Python language is used to implement multi-scale Retinex with color recovery,multi-scale Retinex with chromaticity preservation and enhanced algorithms based on defogging theory.The research results show that the enhancement of the night image can greatly improve the visualization of the image.
Digital images are widely used in the fields of life entertainment,medicine,transportation,etc.Due to the limitations of natural environment,shooting technology and equipment such as uneven illumination and insufficient light intensity,some acquired nighttime images have low contrast,dark colors and serious lack of details and contain a lot of noise,which affect the recognition and quality of the image and the visual experience.Aiming at this problem,this paper analyzes the nighttime image enhancement algorithm based on Retinex and dehazing theory,improves the brightness and contrast of nighttime images,and enhances the visualization of images.Python language is used to implement multi-scale Retinex with color recovery,multi-scale Retinex with chromaticity preservation and enhanced algorithms based on defogging theory.The research results show that the enhancement of the night image can greatly improve the visualization of the image.
引文
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[2]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(4):141-147.
[3]PARK J S,CHO N I.Generation of high dynamic range illumination from a single image for the enhancement of undesirably illuminated Images[J].Multimedia Tools and Applications,2017,14(8):1-14.
[4]黄伟国,张永萍,毕威,等.梯度稀疏和最小平方约束下的低照度图像分解及细节增强[J].电子学报,2018,46(2):424-432.
[5]MCCANN J J.Retinex at 50:color theory and spatial algorithms,a review[J].Journal of Electronic Imaging,2017,26(3):031204.
[6]ALHARBI E M,WANG H,GE P.A novel Dark-Channel dehazing algorithm based on Adaptive-Filter enhanced SSR theory[J].Journal of Computer&Communications,2017,5(11):60-71.
[7]LAND E H.The retinex theory of color vision[J].Scientific American,1977,237(6):108-129.
[8]LAND E H.An alternative technique for the computation of the designator in the retinex theory of color vision[J].Proceedings of the National Academy of Sciences of the United States of America,1986,83(10):3078-3080.
[9]JOBSON D J,RAHMAN Z Z,WOODELL G A.Properties and performance of a center/surround Retinex[J].IEEE Transactions on Image Processing,1997,6(3):451-462.
[10]JOBSON D J,RAHMAN Z Z,WOODELL G A.A multiscale retinex for bridging the gap between color images and the human observation of scenes[J].IEEE Trans.on Image Processing,1997,6(7):965-976.
[11]RAHMAN Z Z,JOBSON D J,WOODEN G A.Multi-scale Retinex for color imageenhancement[C]//Proceedings of IEEE International Conference on Image Processing.Los Alamitos;IEEE Computer Society Press,1996,3:1003-1006.
[12]HE K M,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.
[13]宋瑞霞,李达,王小春.基于HSI色彩空间的低照度图像增强算法[J].图学学报,2017,38(2):217-223.
[14]PETRO A B,SBERT C,MOREL J M.Multiscale Retinex[J].Image Processing on Line,2014(4):71-88.
[15]嵩天,黄天羽,礼欣.Python语言:程序设计课程教学改革的理想选择[J].中国大学教学,2016(2):42-47.
[16]冯英华.基于Petri net with inhibitor arcs的Python多线程程序分析[J].赤峰学院学报(自然科学版),2012,28(12):43-44.
[17]JAM E S.Python计算机视觉[M].朱文涛,袁勇,译.北京:人民邮电出版社,2014.
[18]苏慧娟,于正林,张桂林.基于OpenCV的图像处理[J].科技资讯,2014,12(8):18-19.