马尔科夫随机场模型下的Retinex夜间彩色图像增强

赵宏宇; 肖创柏; 禹晶; 白鹭

doi:10.3788/OPE.20142204.1048

您当前的位置：

首页 >

文章列表页 >

马尔科夫随机场模型下的Retinex夜间彩色图像增强

信息科学 | 更新时间：2020-08-13

- 马尔科夫随机场模型下的Retinex夜间彩色图像增强
- A Retinex algorithm for night color image enhancement by MRF
- 光学精密工程 2014年22卷第4期页码：1048-1055
- 作者机构：
  
  1. 清华大学电子工程系北京,100084
  2. 北京工业大学计算机学院北京,100124
- 作者简介：
- 基金信息：
  
  北京市教委科技发展重点项目（KZ01210005007）();北京市教育委员会科技发展计划资助项目（No：KM201010005011，KM201310005020）()
- DOI：10.3788/OPE.20142204.1048
  中图分类号： TP394.1
- 收稿日期：2013-10-17，
  
  修回日期：2013-11-04，
  
  纸质出版日期：2014-04-25
- 稿件说明：
移动端阅览
赵宏宇, 肖创柏, 禹晶等. 马尔科夫随机场模型下的Retinex夜间彩色图像增强[J]. 光学精密工程, 2014,22(4): 1048-1055

ZHAO Hong-yu, XIAO Chuang-bai, YU Jing etc. A Retinex algorithm for night color image enhancement by MRF[J]. Editorial Office of Optics and Precision Engineering, 2014,22(4): 1048-1055
赵宏宇, 肖创柏, 禹晶等. 马尔科夫随机场模型下的Retinex夜间彩色图像增强[J]. 光学精密工程, 2014,22(4): 1048-1055 DOI： 10.3788/OPE.20142204.1048.

ZHAO Hong-yu, XIAO Chuang-bai, YU Jing etc. A Retinex algorithm for night color image enhancement by MRF[J]. Editorial Office of Optics and Precision Engineering, 2014,22(4): 1048-1055 DOI： 10.3788/OPE.20142204.1048.

摘要

由于Retinex算法在处理夜间彩色图像时容易出现光晕、颜色失真、细节丢失与噪声干扰等问题，本文基于马尔科夫随机场（MRF）提出了一种针对单幅图像的Retinex图像增强算法。该算法在HSV颜色空间下采用线性引导滤波估计图像照度分量；在MRF模型下求解仅包含物体本身特性的反射分量，并通过颜色恢复函数与增益补偿方法进行颜色恢复与校正，最终实现了夜间彩色图像的增强。实验结果表明，利用本文算法处理后图像的均值（整体亮度）可以提高2倍以上，标准差、熵、峰值信噪比（PSNR）等参数均有5%以上的提升。与其它基于Retinex原理的算法相比，本文提出的算法增强效果显著，具有消除“光晕伪影”现象、抑制噪声、颜色保真和有效地凸显边缘细节信息等能力。

Abstract

As Retinex algorithm usually has the problems of halo artifacts

color distortion

high noises and poor details in a low-illumination night color image

this paper proposes a novel Retinex enhancement algorithm based on Markov Random Fields (MRF) to enhance the visibility of single image. This algorithm uses the linear guided filter to estimate image illumination component in HSV(Hue Saturation Value) color space. The reflection image can be obtained through MRF model

and the night color image can be enhanced after color restoration and brightness correction. Compared with the original images

the experimental results demonstrate that the mean value (luminance) of image restored by proposed method has increased more than 2 times

and the evaluation indexes such as standard deviation

entropy

the Peak Signal and Noise Ratio(PSNR) and so on have increased more than 5%. Compared with other Retinex algorithms

the effect of enhancement of this algorithm is more remarkable in halo effect elimination

noise suppression and detail preservation.

关键词

Keywords

references

葛微, 李桂菊, 程宇奇, 等. 利用改进的Retinex进行人脸图像光照处理[J]. 光学精密工程, 2010, 18(4), 1011-1020. GE W, LI G J, CHENG Y Q, et al. Face image illumination processing based on improved Retinex[J]. Opt. Precision Eng., 2010, 18(4), 1011-1020. (in Chinese)

JOBSON D J, RAHMAN Z, WOODELL G A. Properties and performance of a center/surround Retinex[J]. IEEE Transactions on Image Processing, 1997, 6(3): 451-462.

TAREL J, HAUTIERE N, CARAFFA L et al. Vision enhancement in homogeneous and heterogeneous fog[J]. IEEE Intelligent Transportation Systems Magazine, 2012, 4(2):6-20.

JOBSON D J, RAHMAN Z, WOODELL G A. A multi-scale Retinex for bridging the gap between color images and the human observation of scenes[J]. IEEE Transactions on Image Processing, 1997, 6(7): 965-976, 4121:6-20.

RAHMAN Z, JOBSON D J, WOODELL G A. Retinex processing for automatic image enhancement[J]. Journal of Electronic Imaging, 2004, 13(1):100-110.

ELAD M. Retinex by two bilateral filters[C]. Scale-Space and PDE Methods in Computer Vision Lecture Notes in Computer Science, 2005, 3459:217-229.

RAHMAN Z, JOBSON D J, WOODELL G A, et al. Image enhancement, image quality, and noise[C]. San Diego: Photonic Devices and Algorithms for Computing VⅡ, SPIE, 2005, 5907: 164-178.

NISHINO K, KRATZ L, LOMBARDI S. Bayesian defogging[J].International Journal of Computer Vision, 2012, 98:263-278.

FIX A, GRUBER A, BOROS E, et al.. A graph cut algorithm for higher-order Markov Random Fields[J]. 2011 IEEE International Conference on Computer Vision(ICCV), 2011, 1020-1027.

何莲, 张启衡. 应用弦切变换提取几何特征实现目标检测[J]. 光学精密工程, 2010, 18(8):1904-1913. HE L, ZHANG Q H. Object detection based on geometric feature extracted by chord-tangent transformation[J]. Opt. Precision Eng., 2010, 18(8):1904-1913. (in Chinese)

HE K, SUN J, TANG X. Guided image filtering[C].European Conference on Computer Vision (ECCV), Berlin: Springer-Verlag, 2010: 1-14.

陈洪财. 适于LCM应用的彩色图像全局不失真增强算法[J]. 液晶与显示, 2013, 28(3): 446-449. CHEN H C. Color image globally without distortion enhancement algorithms suitable for LCM application[J].Chinese Journal of Liquid Crystals and Displays, 2013, 28(3): 446-449. (in Chinese)

朱明, 孙继刚, 郭立强. 彩色图像四元数矩不变量的研究[J]. 中国光学, 2011, 4(5): 497-502. ZHU M, SUN J G, GUO L Q. Quaternion moment invariant for color image[J]. Chinese Journal of Optics, 2011, 4(5):497-502. (in Chinese)

陈勇, 李愿, 吕霞付, 等. 视觉感知的彩色图像质量积极评价[J]. 光学精密工程, 2013, 21(3):742-750. CHEN Y, LI Y, LV X F, et al.Active assessment of color image quality based on visual perception[J]. Opt. Precision Eng., 2013, 21(3):742-750. (in Chinese)

浏览量

324

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

小波变换及其在MEMS谐振器运动轨迹的特征提取中的应用