计算机应用 ›› 2014, Vol. 34 ›› Issue (10): 2990-2995.DOI: 10.11772/j.issn.1001-9081.2014.10.2990

• 虚拟现实与数字媒体 • 上一篇    下一篇

基于HSI颜色空间的单幅图像去雾算法

王建新1,2,4,张有会1,2,4,王志巍1,2,4,张静3,李娟1,2,4   

  1. 1. 河北师范大学 数学与信息科学学院,石家庄 050024
    2. 计算数学与应用重点实验室(河北师范大学),石家庄 050024;
    3. 石家庄学院 计算机学院,石家庄 050035
    4. 河北师范大学 数学与信息科学学院,石家庄 050024
  • 收稿日期:2014-05-12 修回日期:2014-06-17 出版日期:2014-10-01 发布日期:2014-10-30
  • 通讯作者: 王建新
  • 作者简介:王建新(1988-),女,河北沧州人,硕士研究生,主要研究方向:图形图像处理;
    张有会(1955-) 男,河北承德人,教授,〖BP(〗硕士,〖BP)〗主要研究方向:计算几何、图形图像处理;
    王志巍(1960-),男,辽宁锦州人,副教授,硕士,主要研究方向:算法设计、图像处理;
    张静(1980-),女,河北邯郸人,讲师,硕士,主要研究方向:数字图像处理;
    李娟(1988-),女,山西忻州人,硕士研究生,主要研究方向:图形图像处理。
  • 基金资助:

    国家自然科学基金资助项目;河北省高校创新团队领军人才培育计划项目

Single image defogging algorithm based on HSI color space

WANG Jianxin1,2,ZHANG Youhui1,2,WANG Zhiwei1,2,ZHANG Jing3,LI Juan1,2   

  1. 1. Key Laboratory of Computational Mathematics and Applications (Hebei Normal University), Shijiazhuang Hebei 050024, China;
    2. Mathematics and Information Science College, Hebei Normal University, Shijiazhuang Hebei 050024, China;
    3. Department of Computer, Shijiazhuang College, Shijiazhuang Hebei 050035, China
  • Received:2014-05-12 Revised:2014-06-17 Online:2014-10-01 Published:2014-10-30
  • Contact: WANG Jianxin

摘要:

针对有雾图像对比度差、能见度低的情况,结合HSI颜色空间特点,提出一种单幅图像去雾算法。首先,将有雾图像从RGB颜色空间转换到HSI颜色空间;然后,依据HSI颜色空间中色度、饱和度和亮度各分量受雾影响程度的差异,建立相应的去雾模型;最后,通过分析图像饱和度,得到饱和度模型中权重的取值范围,再对亮度模型中权重进行估计,从而实现去雾效果。与其他几种算法的实验结果比较表明,所提算法运算效率提高1倍左右。同时该算法能有效增强图像清晰度,能很好地运用于单幅图像去雾。

Abstract:

Images captured in hazy weather suffer from poor contrast and low visibility. This paper proposed a single image defogging algorithm to remove haze by combining with the characteristics of HSI color space. Firstly, the method converted original image from RGB color space to HSI color space. Then, based on the different affect to hue, saturation and intensity, a defogged model was established. Finally, the range of weight in saturation model was obtained by analyzing original images saturation, then the range of weight in intensity model was also estimated, and the original image was defogged. In comparison with other algorithms, the experimental results show that the running efficiency of the proposed method is doubled. And the proposed method effectively enhances clarity, so it is appropriate for single image defogging.

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