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基于直方图规定化的图像去雾算法 被引量:16

Image Haze Removal Algorithm Based on Histogram Specification
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摘要 直方图规定化是图像增强领域一个常用的算法,文中提出一种通过高斯函数加权的直方图规定化的图像去雾算法。首先通过分析晴天与雾霾天气下图像的直方图的特点,提出一种通过对高斯函数中方差的改变和高斯函数的加权的方式,解决了原有的单纯高斯函数直方图规定化图像偏暗的问题。通过实验图像的对比可以看出,文中提出的算法可有效去除雾霾天气的影响,其处理效果明显优于直方图规定化算法,而且计算量小、处理速度快、不需要人工干预。 Histogram specification is a commonly used algorithm in image enhancement field. Propose an image haze removal algorithm of histogram specification based on the weighted Gaussian probability density function (Gaussian PDF) in this paper. Firsfly, analyzing the characteristics of image histogram that captured in sunny, fogging and haze weather. Then, solve the weak intensity problem of image specification of the single Ganssian function through changing the variance and weighted Gaussian PDF. The experimental results show the algorithm is able to remove the fog effectively, which is superior to the some existing algorithms of histogram specification about efficiency. It also has many advantages such as low computation ,fast processing speed, no manual intervention.
出处 《计算机技术与发展》 2014年第9期241-244,共4页 Computer Technology and Development
基金 国家电网科研基金项目(2012A-17)
关键词 高斯函数 直方图规定化 图像去雾 加权 Gaussian function histogram specification image haze removal weighted
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参考文献14

  • 1McCartney E J. Optics of the atmosphere : scattering by mole- cules and particles[ M]. [ s. 1. ] :John Wiley and Sons, 1975.
  • 2王萍,张春,罗颖昕.一种雾天图像低对比度增强的快速算法[J].计算机应用,2006,26(1):152-153. 被引量:62
  • 3詹翔,周焰.一种基于局部方差的雾天图像增强方法[J].计算机应用,2007,27(2):510-512. 被引量:45
  • 4Kim J Y, Kim L S, Hwang S H. An advanced contrast en- hancement using partially overlapped sub-block histogram e- qualization [ J ]. IEEE Transactions on Circuits and Systems for Video Technology ,2001,11 (4) :475-484.
  • 5王多超,王永国,董雪梅,胡晰远,彭思龙.贝叶斯框架下的单幅图像去雾算法[J].计算机辅助设计与图形学学报,2010,22(10):1756-1761. 被引量:18
  • 6Tan R T. Visibility in bad weather from a single image[ C]// Proceedings of IEEE conference on computer vision and pat- tern recognition. Anchorage, Alaska, USA : IEEE ,2008 : 1-8.
  • 7Fattal R. Single image debazing [ J ]. ACM Transactions on Graphics,2008,27 ( 3 ) : 1-9.
  • 8He K M, Sun J, Tang X O. Single image haze removal using dark channel prior [ C ]//Proceedings of IEEE conference on computer vision and pattern recognition. Miami: [ s. n. ], 2009 : 1956-1963.
  • 9张冰冰,戴声奎,孙万源.基于暗原色先验模型的快速去雾算法[J].中国图象图形学报,2013,18(2):184-188. 被引量:42
  • 10Gonzales R C,Woods R C. Digital image processing[ M]. 3rd ed. USA : Prentice Hall ,2008.

二级参考文献59

  • 1曹聚亮,吕海宝,谭晓波,楚兴春.可保留图像细节的直方图修正法[J].中国图象图形学报(A辑),2004,9(5):631-635. 被引量:14
  • 2曹聚亮,吕海宝,李冠章.基于自适应局部灰度修正的直方图均衡算法[J].红外与激光工程,2004,33(5):513-515. 被引量:25
  • 3王萍,张春,罗颖昕.一种雾天图像低对比度增强的快速算法[J].计算机应用,2006,26(1):152-153. 被引量:62
  • 4周宏潮,王正明,赵敏.基于全局信息的图像增强组合方法[J].数据采集与处理,2005,20(4):432-435. 被引量:1
  • 5Nayar S K, Narasimhan S G. Vision in bad weather [C] // Proceedings of the 7th IEEE International Conference on Computer Vision, Kerkyra, 1999, 2 : 820-827.
  • 6Schechner Y Y, Narasimhan S G, Nayar S K. Instant dehazing of images using polarization [C] //Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Hawaii, 2001, 1 :Ⅰ-325-Ⅰ-332.
  • 7Narasimhan S G, Nayar S K. Interactive (de) weathering of an image using physical models [OL]. [2009-11-10]. http://lik. imag. fr/membres/Bill. Triggs[events/iccvO3/edrom/cpmcv03/31_ narasimhan. pdf.
  • 8Fattal R. Single image dehazing [J]. ACM Transactions on Graphics, 2008, 27(3): Article No. 72.
  • 9Tan R T. Visibility in bad weather from a single image [C]// Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, 2008:1-8.
  • 10He K M, Sun J, Tang X O. Single image haze removal using dark channel prior [C] //Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Miami, 2009: 1956-1963.

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