摘要
矿井下阴暗潮湿、环境恶劣,通过监控摄像机采集的图像质量差,为此提出基于粗糙集理论的矿井图像增强算法,与基于Retinex理论的图像增强算法进行实验对比,该算法使均值提高了4.759,标准差增加了1.8953,监控图像更清晰、质量更高、更精准地呈现了矿井下作业环境,从而加强了安全生产监控与管理.
For the dark,humid and tough environment underground of the mine,and the poor quality of the images acquired by surveillance cameras,the paper proposed the mine image enhancement algorithm based on rough set theory.Compared experimentally with the image enhancement algorithm based on the theory of the Retinex,the algorithm increased the average value by 4.759,and the standard deviation by 1.8953.It made monitoring image clearer and of higher quality,presenting the underground work environment more accurately,thus strengthening the monitoring and management of safety production.
作者
叶允英
YE Yun-ying(Department of Information Technology and Engineering,Ningde Vocational and Technical College,Ningde Fujian 355000)
出处
《辽宁师专学报（自然科学版）》
2020年第4期78-81,108,共5页
Journal of Liaoning Normal College(Natural Science Edition)
关键词
粗糙集理论
矿井
图像增强算法
rough set theory
mine
image enhancement algorithm
