Dark Channel Based Visibility Measuring from Daytime Scene Videos,ERICDATA高等教育知識庫
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篇名
Dark Channel Based Visibility Measuring from Daytime Scene Videos
並列篇名
Dark Channel Based Visibility Measuring from Daytime Scene Videos
作者 Xiao-Han ChenZhao Li
英文摘要

Visibility is one of the most important factors of meteorological observation. Low visibility caused by fog often has a great impact on human production and daily life. Therefore, visibility measurements and warnings are given as early as possible to avoid accidents. This paper proposes a new visibility measuring method based on dark channel characteristics of digital images in natural scenes. It uses the means of dark channel values obtained from foggy images and high visibility reference images as inputs of a deep fully connected neural network, and then the trained model is applied to estimate visibility. Experiments conducted on a dataset contained two foggy scenes. The results demonstrate the effectiveness of our proposed method for daytime visibility measurement. At the same time, this paper proposes and designs an automatic detection system based on our algorithm. It implements the real time visibility measuring through edge computing.

 

起訖頁 593-599
關鍵詞 Meteorological visibilityDark channel priorTransmission factorEdge computing
刊名 網際網路技術學刊  
期數 202205 (23:3期)
出版單位 台灣學術網路管理委員會
DOI 10.53106/160792642022052303017  複製DOI
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