基于HSI亮度分量和RGB空间的图像去雾算法

doi:10.11772/j.issn.1001-9081.2016.05.1378

计算机应用 ›› 2016, Vol. 36 ›› Issue (5): 1378-1382.DOI: 10.11772/j.issn.1001-9081.2016.05.1378

基于HSI亮度分量和RGB空间的图像去雾算法

李慧慧, 秦品乐, 梁军

中北大学计算机与控制工程学院, 太原 030051

收稿日期:2015-10-16 修回日期:2015-12-01 出版日期:2016-05-10 发布日期:2016-05-09
通讯作者: 秦品乐
作者简介:李慧慧(1991-),女,山西太原人,硕士研究生,主要研究方向:海量视频数据分析、数字图像处理、机器学习、深度学习;秦品乐(1978-),男,山西长治人,副教授,博士,主要研究方向:大数据、机器视觉、三维重建;梁军(1978-),山西长治人,硕士研究生,主要研究方向:机器视觉、三维重建。
基金资助:
山西省自然基金资助项目(2015011045)。

Defogging algorithm based on HSI luminance component and RGB space

LI Huihui, QIN Pinle, LIANG Jun

School of Computer Science and Control Engineering, North University of China, Taiyuan Shanxi 030051, China

Received:2015-10-16 Revised:2015-12-01 Online:2016-05-10 Published:2016-05-09
Supported by:
This work is partially supported by the Natural Foundation of Shanxi Province (2015011045).

摘要/Abstract

摘要： 图像去雾技术处理的目的是消除雾霾对视频监控图像的影响,提高雾霾图像的视觉效果。目前,一般去雾图像只是比较去雾后和去雾前的图像,处理结果通常失真严重或过饱和,不能在保证细节清晰的同时保证颜色信息完整。针对上述问题,提出了一种基于大气散射模型和光学原理,建立具有散射特性的HIS亮度转换模型,并与RGB空间结合计算的图像复原方法。该方法通过分析晴天图像和雾霾图像的对比关系,结合HSI空间人眼视觉最敏感的亮度分量计算出图像场景的相对深度关系,利用大气散射模型以及景深比,对雾霾视频图像进行清晰复原和结果的测评。实验结果证明,与只从RGB空间计算的去雾霾方法对比,所提方法去雾效果更清晰,彩色失真和过饱和程度更小。

关键词: 视频监控, 去雾, 大气散射模型, 图像复原, 景深

Abstract: The purpose of image defogging is to remove the fog effect from image of surveillance video to improve the fog haze image visual effect. Presently, there is only a comparison between images before and after defogging, and the results are often distorted seriously and oversatuarted. Thereby, it is hard to ensure the clear details and the integrity of color information simultaneously. For tackling above problems, a new optimized method for images recovering was proposed with combination of HIS luminance component and RGB space, which was based on atmosphere scattering model and optical principals. In this method the relative depth relationship of image scene was analyzed by comparing images in fine and haze days with help of the most eye-sensitive HSI luminance component. Finally, by utilizing atmosphere scattering model and the comparison of depth of field, the recovering and result evaluation were conducted on the video obtained in haze. The experimental results show that, compared with the defogging methods calculated in RGB space, the proposed method has more clear defogging results and smaller degree of color distortion and oversaturation.

Key words: video surveillance, defogging, atmosphere scattering model, image recovering, depth of field

中图分类号:

TP752.2

李慧慧, 秦品乐, 梁军. 基于HSI亮度分量和RGB空间的图像去雾算法[J]. 计算机应用, 2016, 36(5): 1378-1382.

LI Huihui, QIN Pinle, LIANG Jun. Defogging algorithm based on HSI luminance component and RGB space[J]. Journal of Computer Applications, 2016, 36(5): 1378-1382.

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基于HSI亮度分量和RGB空间的图像去雾算法

Defogging algorithm based on HSI luminance component and RGB space

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