期刊文献+

基于主分量分析和大气散射模型的彩色图像雾霾快速去除算法 被引量:3

Fast algorithm for color image haze removal using principle component analysis and atmospheric scattering mode
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摘要 为去除彩色图像中的雾霾,提出了一种基于主分量分析(PCA)和大气散射模型的快速去除彩色图像雾霾的算法。首先,提取彩色图像三个颜色通道的主分量,并用最大主分量重构三个颜色通道,并在重构后的三个颜色通道中取最小灰度值构成最小重构映射(MRM);然后,用中值滤波器对MRM滤波,以提高估计全局大气光的准确性,接着在MRM中估计全局大气光;最后,根据大气散射模型求解介质透过率和场景辐射度(去除雾霾后的图像)。实验结果表明,所提算法在视觉效果上取得了较好的复原结果,与暗原色去雾算法和对比度受限自适应直方图均衡算法相比,所提算法运算效率更高,同时该算法简单、易于实现,能较快去除彩色图像中的雾霾。 For haze removal in color image, a fast algorithm based on Principle Component Analysis (PCA) and atmospheric scattering model was proposed for color image haze removal. Firstly, the principal components of three color channels were extracted from original color image, and the three color channels were reconstructed by use of maximum principal component, and the Minimum Reconstruction Map (MRM) was obtained by taking the minimum gray value in three color channels. Then, the MRM was filtered by median filter to improve the accuracy of estimation of the global atmosphere light, then the global atmosphere light was estimated in MRM. Finally, according to the atmospheric scattering model to obtain media transmittance and the sence radiance of the haze removal image. The experimental results showed that the proposed algorithm achieved better visual recovery results, in comparison with dark channel prior haze removal algorithm and contrast limited adaptive histogram equalization algorithm. The results domonstrate that the proposed algorithm improves the operation efficiency, it is simple and easy to implement, and can quickly remove haze in color image.
出处 《计算机应用》 CSCD 北大核心 2015年第2期531-534,共4页 journal of Computer Applications
基金 科技部国际合作研究项目(2009DFR10530)
关键词 去除彩色图像雾霾 主分量分析 最大主分量重构 最小重构映射 大气散射模型 color image haze removal Principal Component Analysis (PCA) reconstruction of maximum principalcomponent minimum reconstruction map atmospheric scattering model
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参考文献14

  • 1SCHECHER Y Y, NARASIMHAN S G, NAYAR S K. Instant de- hazing of images using polarization [ C]//CVPR 2001: Proceedings of the 2001 IEEE Computer Society Conference on Computer Viion and Pattern Recognition. Washington, DC: IEEE Computer Socie- ty, 2001, 1:325-332. 被引量:1
  • 2NAYAR S K, NARASIMHAN S G. Vision in bad weather [ C I// Proceedings of the Seventh IEEE Inthernation Conference on C3m- puter Vision. Piscataway: IEEE, 1999, 2:820-827. 被引量:1
  • 3NARASIMHAN S G, NAYAR S K. Contrast restoration of weaher degraded images [ J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(6): 713-724. 被引量:1
  • 4NARASIMHAN S G, NAYAR S K. Interactive (De) weather of an image using physical models [ C]// Proceedings of the 2003 ICCV Vision Workshop on Color and Photometric Methods in Computer Vi- sion. Piscataway: IEEE, 2003: 1387- 1394. 被引量:1
  • 5FATYAL R. Single image dehazing [ C]// SIGGRAPH '08: Pro- ceedings of the 2008 Special Interest Group on Computer Graphics. New York: ACM, 2008: Article No. 72. 被引量:1
  • 6HE K, SUN J, TANG X. Single image haze removal using dark channel prior [ J]. IEEE Transactions on Pattern Analysis and Ma- chine Intelligence, 2011, 33(12): 2341-2353. 被引量:1
  • 7TAN R T. Visibility in bad weather from a single image [ C]//CVPR 2008: Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2008:1-8. 被引量:1
  • 8HU X, TAO L, WANG 14. A contrast enhancement method for fog- degraded images [ C]// Proceedings of 2011 International Confer- ence in Electrics, Communication and Automatic Control. Berlin: Springer, 2012:577-584. 被引量:1
  • 9CHENG L, LYU W. A fast algorithm for foggy image contrast en- hancement [ C] // Proceedings of the 2011 International Conference on Transportation, Mechanical and Electrical Engineering. Piscat- away: IEEE, 2011: 1705-1708. 被引量:1
  • 10FENG Y, HE M, LIU W. A new method for foggy image enhance- ment [ C]// ICIEA 2009: Proceedings of the 4th IEEE Conference on Industrial Electronics and Applications. Piscataway: IEEE, 2009:2416-2419. 被引量:1

同被引文献26

  • 1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
  • 2STARK J A.Adaptive image contrast enhancement using generalizations of histogram equlization[J].IEEE Transactions on Image Processing,2000,9(5):889-896. 被引量:1
  • 3TAN 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. 被引量:1
  • 4FATTAL R.Single image dehazing[J].ACM Transactions on Graphics,2008,27(3):1-9. 被引量:1
  • 5HE 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,FL,USA:IEEE Computer Society,2009:1956-1963. 被引量:1
  • 6HE K M,SUN J,TANG X O.Guide image filtering[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013,35(6):1-13. 被引量:1
  • 7KIM J H,JANG W D,SIM J Y,et al.Optimized contrast enhancement for real-time image and video dehazing[J].Visual Communication and Image Representation,2013,24(3):410-425. 被引量:1
  • 8NARASIMHAN S G,S,NAYAR K.Contrast restoration of weather degraded images[J].IEEE Transactions on Pattern Analysis&Machine Intelligence,2003,25(6):713-724. 被引量:1
  • 9TAREL J P,HAUTI N.Fast visibility restoration from a single color or gray level image[C]//Proceedings of IEEE Conference on Computer Vision.Kyoto,Japan:IEEE Computer Society,2009:2201-2208. 被引量:1
  • 10刘茜,卢心红,李象霖.基于多尺度Retinex的自适应图像增强方法[J].计算机应用,2009,29(8):2077-2079. 被引量:51

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