欢迎访问中国科学院大学学报,今天是
信息与电子科学

一种基于视觉特性和灰度补偿改进的LDR图像增强方法

  • 何保畅 ,
  • 耿修瑞 ,
  • 胡文龙
展开
  • 1 中国科学院电子学研究所, 北京 100190;
    2 中国科学院空间信息处理与应用系统技术重点实验室, 北京 100190;
    3 中国科学院大学, 北京 100049

收稿日期: 2017-02-14

  修回日期: 2017-04-12

  网络出版日期: 2018-05-15

基金资助

国家自然科学基金(61331017)资助

An improved LDR image enhancement algorithm based on visual characteristics and gray scale compensation

  • HE Baochang ,
  • GENG Xiurui ,
  • HU Wenlong
Expand
  • 1 Institute of Electronic, Chinese Academy of Sciences, Beijing 100190, China;
    2 Key Laboratory of Geo-spatial Information Processing and Application System Technology, Chinese Academy of Sciences, Beijing 100190, China;
    3 University of Chinese Academy of Sciences, Beijing 100049, China

Received date: 2017-02-14

  Revised date: 2017-04-12

  Online published: 2018-05-15

摘要

针对传统空域增强算法的不足,LDR (layered difference representation)算法构造一种二维直方图,该直方图包含像素间上下文信息。基于此,提出一种基于LDR的改进算法。该算法将视觉特性引入直方图,构造二维视觉差异直方图,再利用该直方图和LDR进行初步增强。最后采用灰度补偿方法改善过增强现象。实验结果显示该算法可产生更好的视觉效果,并适当提高整体亮度和对比度,消除人工伪影,且无需调整参数,满足实时处理的要求。

本文引用格式

何保畅 , 耿修瑞 , 胡文龙 . 一种基于视觉特性和灰度补偿改进的LDR图像增强方法[J]. 中国科学院大学学报, 2018 , 35(3) : 391 -401 . DOI: 10.7523/j.issn.2095-6134.2018.03.014

Abstract

In view of the drawbacks of traditional spatial image enhancement algorithms, this paper proposes an improved algorithm based on the layered difference representation (LDR) algorithm which constructs a two-dimensional histogram containing the spatial context information. The histogram exploits the visual characteristics to construct a two-dimensional visual difference histogram, which is consequently used in the enhancement of the input images with LDR. Finally, the grayscale compensation method is used to ameliorate the over-enhancement problem. Experimental results show that the proposed algorithm produces better visual effects (performance), improves the overall brightness and contrast, and eliminates the artifacts. The proposed method is free of parameter selection and meets the real-time processing requirement.

参考文献

[1] Land E H. Recent advances in retinex theory and some implications for cortical computations:color vision and the natural image[J]. Proceedings of the National Academy of Sciences of the United States of America, 1983, 80(16):5163-5169.
[2] McCann J. Lessons learned from mondrians applied to real images and color gamuts[C]//Colorand Imaging Conference. Society for Imaging Science and Technology, 1999(1):1-8.
[3] Jobson D J, Rahman Z, Woodell G A. Properties and performance of a center/surround retinex[J]. IEEE Transactions on Image Processing:A Publication of the IEEE Signal Processing Society, 1997, 6(3):451-462.
[4] Jobson D J, Rahman Z U, Woodell G A. A multiscale retinex for bridging the gap between color images and the human observation of scenes[J]. IEEE Transactions on Image Processing:A Publication of the IEEE Signal Processing Society, 1997, 6(7):965-976.
[5] Rahman Z, Jobson D J, Woodell G A. Multi-scale retinex for color image enhancement[C]//International Conference on Image Processing, IEEE, 1996(3):1003-1006.
[6] 李云, 刘学诚. 基于小波变换的图像对比度增强算法研究[J]. 计算机应用与软件, 2008, 25(8):100-103.
[7] Huang K Q, Wang Q, Wu Z Y. Natural color image enhancement and evaluation algorithm based on human visual system[C]//IEEE International Conference on Acoustics. 2006, 3:721-724.
[8] Yu Z, Bajaj C. A fast and adaptive method for image contrast enhancement[C]//International Conference on Image Processing, IEEE, 2004(2):1001-1004.
[9] Kim J Y, Kim L S, Hwang S H. An advanced contrast enhancement using partially overlapped sub-block histogram equalization[J]. IEEE Transactions on Circuits & Systems for Video Technology, 2001, 11(4):475-484.
[10] Kim Y T. Contrast enhancement using brightness preserving bi-histogram equalization[J]. IEEE Transactions on Consumer Electronics, 1997, 43(1):1-8.
[11] Wang Y, Chen Q, Zhang B. Image enhancement based on equal area dualistic sub-image histogram equalization method[J]. IEEE Transactions on Consumer Electronics, 1999, 45(1):68-75.
[12] Chen S D, Ramli A R. Minimum mean brightness error bi-histogram equalization in contrast enhancement[J]. IEEE Transactions on Consumer Electronics, 2003, 49(4):1310-1319.
[13] Celik T. Two-dimensional histogram equalization and contrast enhancement[J]. Pattern Recognition, 2012, 45(10):3810-3824.
[14] Lee C, Lee C, Kim C S. Contrast enhancement based on layered difference representation of 2D histograms[J]. Image Processing IEEE Transactions on, 2013, 22(12):5372-5384.
[15] 许欣, 陈强, 孙怀江,等. 结合视觉感知特性的梯度域图像增强方法[J]. 计算机辅助设计与图形学学报, 2009, 21(1):130-135.
[16] 单建华, 何金洪. 基于人类视觉系统的动态直方图均衡算法[J]. 计算机科学与应用, 2013, 3(2):110-116.
文章导航

/