一种矿井图像增强算法

王星; 白尚旺; 潘理虎; 陈立潮

doi:10.13272/j.issn.1671-251x.2017.03.011

一种矿井图像增强算法

王星¹,
白尚旺¹,
潘理虎^{1, 2},
陈立潮¹

1.
太原科技大学计算机科学与技术学院，山西太原030024
2.
中国科学院地理科学与资源研究所，北京100101

基金项目:

“十二五”山西省科技重大专项项目(20121101001)

山西省中科院科技合作项目(20141101001)

山西省科技攻关项目(20141039)

详细信息

中图分类号: TD67
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出版历程
- 刊出日期: 2017-03-09

A mine image enhancement algorithm

1.
Department of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan 030024, China
2.
Institute of Geographic Science and Natural Resource Research, Chinese Academy o

摘要

摘要: 针对煤矿井下视频监控系统采集图像对比度低、光照不均、伴有大量噪声等问题，提出一种基于加权引导滤波同步去噪的单尺度Retinex算法对矿井图像进行增强。该算法首先采用加权引导滤波代替单尺度Retinex算法的高斯滤波对图像的低频分量进行照度估计，然后采用加权引导滤波对图像的高频分量进行去噪处理，最后由对数域转换到实数域得到增强后的图像。通过主观视觉效果和客观质量评价对该算法进行验证，结果表明该算法较传统图像增强算法可获得更好的图像视觉效果，且图像处理速度更快。
- 矿井图像 /
- 视频监控图像 /
- 图像增强 /
- 单尺度Retinex算法 /
- 加权引导滤波
Abstract: For poor images captured by coal mine video monitoring system with low contrast, uneven illumination and a lot of noise, a single scale Retinex algorithm based on simultaneous denoising of weighted guided filtering was proposed for underground image enhancement. Firstly, low-frequency components of an image are estimated by the weighted guided filter, which replaces Gaussian filter in single scale Retinex algorithm. Secondly, high-frequency components of the image are denoised by the weighted guided filter. Finally, an enhanced image is obtained through conversion from log domain to real field. The subjective visual effect and objective evaluation results show the algorithm has better visual effect and higher image processing speed than traditional image enhancement algorithms.
- mine image /
- video monitoring image /
- image enhancement /
- single scale Retinex algorithm /
- weighted guided filtering