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  • Author or Editor: Yang Lu x
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Qingyong Li, Weitao Lu, and Jun Yang

Abstract

Cloud detection is the precondition for deriving other information (e.g., cloud cover) in ground-based sky imager applications. This paper puts forward an effective cloud detection approach, the Hybrid Thresholding Algorithm (HYTA) that fully exploits the benefits of the combination of fixed and adaptive thresholding methods. First, HYTA transforms an input color cloud image into a normalized blue/red channel ratio image that can keep a distinct contrast, even with noise and outliers. Then, HYTA identifies the ratio image as either unimodal or bimodal according to its standard deviation, and the unimodal and bimodal images are handled by fixed and minimum cross entropy (MCE) thresholding algorithms, respectively. The experimental results demonstrate that HYTA shows an accuracy of 88.53%, which is far higher than those of either fixed or MCE thresholding alone. Moreover, HYTA is also verified to outperform other state-of-the-art cloud detection approaches.

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Jun Yang, Weitao Lu, Ying Ma, and Wen Yao

Abstract

Cloud detection is a basic research for achieving cloud-cover state and other cloud characteristics. Because of the influence of sunlight, the brightness of sky background on the ground-based cloud image is usually nonuniform, which increases the difficulty for cirrus cloud detection, and few detection methods perform well for thin cirrus clouds. This paper presents an effective background estimation method to eliminate the influence of variable illumination conditions and proposes a background subtraction adaptive threshold method (BSAT) to detect cirrus clouds in visible images for the small field of view and mixed clear–cloud scenes. The BSAT algorithm consists of red-to-blue band operation, background subtraction, adaptive threshold selection, and binarization. The experimental results show that the BSAT algorithm is robust for all types of cirrus clouds, and the quantitative evaluation results demonstrate that the BSAT algorithm outperforms the fixed threshold (FT) and adaptive threshold (AT) methods in cirrus cloud detection.

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Luwen Chen, Yijun Zhang, Weitao Lu, Dong Zheng, Yang Zhang, Shaodong Chen, and Zhihui Huang

Abstract

Performance evaluation for the lightning location system (LLS) of the power grid in Guangdong Province, China, was conducted based on observation data of the triggered lightning flashes obtained in Conghua, Guangzhou, during 2007–11 and natural lightning flashes to tall structures obtained in Guangzhou during 2009–11. The results show that the flash detection efficiency and stroke detection efficiency were about 94% (58/62) and 60% (97/162), respectively. The arithmetic mean and median values for location error were estimated to be about 710 and 489 m, respectively, when more than two reporting sensors were involved in the location retrieval (based on 87 samples). After eliminating one obviously abnormal sample, the absolute percentage errors of peak current estimation were within 0.4%–42%, with arithmetic mean and median values of about 16.3% and 19.1%, respectively (based on 21 samples).

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