辽宁工程技术大学学报（自然科学版）2024，Vol.43Issue(2)：225-231,7.DOI:10.11956/j.issn.1008-0562.2024.02.014
基于全局双约束的矿井尘雾图像增强方法
Mine dust image enhancement method based on global double constraints
摘要
Abstract
In order to improve the observability of dust haze images in coal mines,a dust haze image enhancement algorithm based on global double constraint Retinex algorithm was proposed.Firstly,the input image is cycled inside and outside,and the overcomplete dictionary under the double constraints of clustering and sparse is trained to suppress the noise component in the image.Then,the Retinex algorithm was used to estimate and extract illuminance and reflection components,and adaptive Gamma correction was performed for the extracted illuminance components.The final output of the enhanced image.The research results show that the proposed image enhancement algorithm can effectively improve the contrast and clarity of dust fog image in the complex underground environment of coal mine,remove the real dust,and suppress the phenomenon of image halo and edge blur.The enhanced image color is natural,and the visual effect is significantly improved.The research conclusion provides a theoretical basis for the engineering application of mine video monitoring sharpening.关键词
图像增强/图像去噪/稀疏约束/聚类约束/Retinex算法Key words
image enhancement/image denoising/sparse constraint/clustering constraint/Retinex algorithm分类
矿业与冶金引用本文复制引用
冀常鹏,贺丽娜,代巍..基于全局双约束的矿井尘雾图像增强方法[J].辽宁工程技术大学学报（自然科学版）,2024,43(2):225-231,7.基金项目
辽宁省教育厅基本科研项目(LJKMZ20220677) （LJKMZ20220677）
