基于负修正和对比度拉伸的快速去雾算法

doi:10.11772/j.issn.1001-9081.2016.04.1106

计算机应用 ›› 2016, Vol. 36 ›› Issue (4): 1106-1110.DOI: 10.11772/j.issn.1001-9081.2016.04.1106

基于负修正和对比度拉伸的快速去雾算法

王琳¹, 毕笃彦¹, 李晓辉², 何林远¹

1. 空军工程大学航空航天工程学院, 西安 710038;
2. 中国人民解放军济南空军航空修理厂, 济南 250021

收稿日期:2015-09-21 修回日期:2015-11-03 出版日期:2016-04-10 发布日期:2016-04-08
通讯作者: 王琳
作者简介:王琳(1991-),女,陕西铜川人,硕士研究生,主要研究方向:图像增强; 毕笃彦(1962-),男,陕西宝鸡人,教授,博士,主要研究方向:机器视觉、模式识别、目标检测与跟踪、图像增强; 李晓辉(1967-),男,河南洛阳人,工程师,主要研究方向:数字化仿真; 何林远(1983-),男,陕西西安人,讲师,硕士,主要研究方向:图像增强。
基金资助:
国家自然科学基金资助项目(61372167, 613791140)。

Fast image dehazing based on negative correction and contrast stretching transform

WANG Lin¹, BI Duyan¹, LI Xiaohui², HE Linyuan¹

1. Institute of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi'an Shaanxi 710038, China;
2. PLA Air Force Aviation Repair Shop in Jinan, Jinan Shandong 250021, China

Received:2015-09-21 Revised:2015-11-03 Online:2016-04-10 Published:2016-04-08
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61372167, 613791140).

摘要/Abstract

摘要： 针对目前主流去雾方法算法复杂度高而难以满足实时性需求的问题,提出一种提高雾天图像对比度、保持图像颜色的快速算法。对输入图像的负像进行对比度拉伸间接提升雾天图像的对比度,达到了节约运算时间的效果。针对由Lipschitz系数得到的图像结构信息设置自适应的参数,参数设置由关于Lipschitz系数的函数和关于局部像素块亮度平均值的函数两部分组成,最后利用Sigmoid函数自适应地拉伸图像,能够得到色彩自然、细节清晰的无雾图像,相对于He算法,所提算法在速度方面提升了约90%。实验结果表明,该算法在保证实时性的同时达到了较好的主观视觉愉悦性,更符合实际工程应用的要求。

关键词: 快速图像去雾, 负修正, 对比度拉伸, Lipschitz指数, Sigmoid函数

Abstract: It is hard for existing image dehazing method to meet the demand of real-time because of high complexity, thus a fast image dehazing method combined with negative correction and contrast stretching transform was proposed to enhance the contrast and saturation of haze images. Contrast stretching transform was employed to negative image of input image to enhance the contrast, which saved computing time. Adaptive parameter was set for structure information got via Lipschitz exponent, it was composed of Lipschitz exponent and mean average function of local pixel block. Finally, the corresponding haze removed image with nature color and clear details was obtained by using Sigmoid function to stretch the image adaptively. The experimental results demonstrate that the proposed method can achieve a good subjective visual effect while ensuring the real-time performance, and meet the requirements of practical engineering applications.

Key words: fast image dehazing, negative correction, contrast stretching transform, Lipschitz exponent, Sigmoid function

中图分类号:

TP391.9

王琳, 毕笃彦, 李晓辉, 何林远. 基于负修正和对比度拉伸的快速去雾算法[J]. 计算机应用, 2016, 36(4): 1106-1110.

WANG Lin, BI Duyan, LI Xiaohui, HE Linyuan. Fast image dehazing based on negative correction and contrast stretching transform[J]. Journal of Computer Applications, 2016, 36(4): 1106-1110.

参考文献

[1] 毕笃彦, 葛渊, 李权合, 等. 单幅图像去雾方法研究[J].空军工程大学学报(自然科学版), 2013, 14(6):46-53.(BI D Y, GE Y, LI Q H, et al. A research on defogging methods with single image[J]. Journal of Air Force Engineering University (Natural Science Edition), 2013, 14(6):46-53.)
[2] HE K, SUN J, TANG X. Single image haze removal using dark channel prior[C]//CVPR 2009:Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, NJ:IEEE, 2009:1956-1963.
[3] HE K, SUN J, TANG X. Guided image filtering[C]//ECCV 2010:Proceedings of the 11th European Conference on Computer Vision, LNCS 6311. Berlin:Springer, 2010:1-14.
[4] FATTAL R. Single image dehazing[J]. ACM Transactions on Graphics, 2008, 27(3):1-9.
[5] 张赛楠, 吴亚东, 张红英, 等. 改进的单尺度Retinex雾天图像增强算法[J].激光与红外, 2013, 43(6):698-702.(ZHANG S N, WU Y D, ZHANG H Y, et al. Haze image enhancement method based on improved single scale Retinex[J]. Laser & Infrared, 2013, 43(6):698-702.)
[6] 阚建霞.基于HSV颜色空间的改进的多尺度Retinex算法[J].电子设计工程, 2015, 23(7):148-150.(KAN J X. Improved multscale Retinex algorithm based on the HSV color space[J]. Electronic Design Engineering, 2015, 23(7):148-150.)
[7] 冯亚丽, 黄静. 一种新的基于MSRCR光照补偿算法[J].计算机系统应用, 2012, 21(9):187-191.(FENG Y L, HUANG J. Light compensation algorithm based on MSRCR[J]. Computer Systems & Applications, 2012, 21(9):187-191.)
[8] PROVENZI E, FIERRO M, RIZZI A, et al. Random spray Retinex:a new Retinex implementation to investigate the local properties of the model[J]. IEEE Transactions on Image Processing, 2007, 16(1):162-171.
[9] 孙李辉, 李俊山, 张仲敏, 等. 大气湍流退化图像过渡区域细化算法[J].电光与控制, 2013, 20(9):14-17.(SUN L H, LI J S, ZHANG Z M, et al. Refinement algorithm of edge transitional region for turbulence degraded image[J]. Electronics Optics & Control, 2013, 20(9):14-17.)
[10] GAO Y. A fast image dehazing algorithm based on negative correction[J]. Signal Processing, 2014, 103(10):380-398.
[11] LIU Q, CHEN M, ZHOU D. Single image haze removal via depth-based contrast stretching transform[J]. Science China:Information Science, 2015, 58(1):1-17.
[12] 王东, 丁宣浩, 陈利霞. 信号奇异性的Lipschitz意义[J].桂林电子工业学院学报, 2003, 23(5):9-12.(WANG D, DING X H, CHEN L X. Lipschitz significance of signal singularity[J]. Journal of Guilin University of Electronic Technology, 2003, 23(5):9-12.)
[13] 岑翼刚, 岑丽辉, 孙德宝. 信号Lipschitz奇异性的计算与分析[J].计算机工程与应用, 2004, 40(18):35-37.(CEN Y G, CEN L H, SUN D B. The calculation and analysis of signal's Lipschitz singularities[J]. Computer Engineering and Applications, 2004, 40(18):35-37.)
[14] 孙抗, 汪渤, 周志强, 等. 基于双边滤波的实时图像去雾技术研究[J].北京理工大学学报, 2011, 31(7):810-813.(SUN K, WANG B, ZHOU Z Q, et al. Real time image haze removal using bilateral filter[J]. Transactions of Beijing Institute of Technology, 2011, 31(7):810-813.)

基于负修正和对比度拉伸的快速去雾算法

Fast image dehazing based on negative correction and contrast stretching transform

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

编辑推荐

Metrics

[1]	李垚峰何小海吴小强. 改进的带色彩恢复的多尺度Retinex雾天图像增强算法[J]. 计算机应用, 2014, 34(10): 2996-2999.
[2]	张雨浓陈俊维刘锦荣曲璐黎卫兵. 基于权值与结构确定法的单极Sigmoid神经网络分类器[J]. 计算机应用, 2013, 33(03): 766-770.
[3]	许蓓蕾庄奕琪汤华莲张丽田进寿. 基于对象的多级图像增强法[J]. 计算机应用, 2011, 31(06): 1556-1559.
[4]	闫军何小海王海梅吴学宏. 天气雷达图像中对流云区识别算法[J]. 计算机应用, 2009, 29(12): 3366-3368.
[5]	田东平赵天绪. 基于Sigmoid惯性权值的自适应粒子群优化算法[J]. 计算机应用, 2008, 28(12): 3058-3061.