FU Yua. Design of a mine monitoring image restoration device based on L-R algorithm[J]. Industry and Mine Automation, 2020, 46(8): 101-105. doi: 10.13272/j.issn.1671-251x.17656
Citation: FU Yua. Design of a mine monitoring image restoration device based on L-R algorithm[J]. Industry and Mine Automation, 2020, 46(8): 101-105. doi: 10.13272/j.issn.1671-251x.17656

Design of a mine monitoring image restoration device based on L-R algorithm

doi: 10.13272/j.issn.1671-251x.17656
  • Publish Date: 2020-08-20
  • The intelligent technology of mine video monitoring is one of the key technologies to realize visual remote intervention intelligent unmanned mining in coal mine.However, due to bad working environment of mining face in underground coal mine, the collected mine monitoring images have serious degradation, which affects development of intelligence of coal mining. The collection process of mine monitoring images is affected by vibration of hydraulic support, shearer, crusher and belt conveyor, as well as random factors such as mineral dust and spray, so the useful information such as depth, strength and range of images degradation cannot be accurately acquired. In view of the above problems, a mine monitoring image restoration device based on L-R algorithm was designed, which includes a stream fetching module, a configuration module, an image restoration module and a forwarding module. Firstly, the device uses stream fetching module to obtain video stream of camera and decodes it into image frames. Then, it uses configuration module to configure parameters of the restoration module, and adopts degradation function model and image restoration module based on L-R algorithm to restore the image and output the restored image. Finally, it uses forwarding module to transmit the restored image frame to video monitoring end in form of video stream, so as to provide clear video information for operators to operate coal mining equipment remotely. The experimental results show that the device can improve quality of mine monitoring images, and the restored images are clear and bright.

     

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    通讯作者: 陈斌, bchen63@163.com
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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