A Hybrid Thresholding Algorithm for Cloud Detection on Ground-Based Color Images

被引:190
作者
Li, Qingyong [1 ]
Lu, Weitao [2 ]
Yang, Jun [2 ]
机构
[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
[2] Chinese Acad Meteorol Sci, Inst Atmospher Sounding, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
COVER;
D O I
10.1175/JTECH-D-11-00009.1
中图分类号
P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
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.
引用
收藏
页码:1286 / 1296
页数:11
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