Gaussian Mixture Model Based Cloud Detection for Chinese High Resolution Satellite Imagery

KANG Yifei; PAN Li; SUN Mingwei; CHEN Qi; WANG Yue

doi:10.13203/j.whugis20140875

Volume 42 Issue 6

Jun. 2017

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Geomatics and Information Science of Wuhan University > 2017 > 42(6): 782-788. > DOI: 10.13203/j.whugis20140875

KANG Yifei, PAN Li, SUN Mingwei, CHEN Qi, WANG Yue. Gaussian Mixture Model Based Cloud Detection for Chinese High Resolution Satellite Imagery[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6): 782-788. DOI: 10.13203/j.whugis20140875

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Gaussian Mixture Model Based Cloud Detection for Chinese High Resolution Satellite Imagery

1.
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2.
Faculty of Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China
3.
Wuhan Geotechnical Engineering and Surveying Institute, Wuhan 430022, China

Funds:

The Major State Basic Research Development National of China (973 Program) 2012CB719900

the National Natural Science Foundation of China 41301519

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Author Bio:
KANG Yifei, PhD candidate, specializes in digital photogrammetry. E-mail:2217707@163.com
Corresponding author:
PAN Li, PhD, professor. E-mail:panli@whu.edu.cn
Received Date: October 21, 2015
Published Date: June 04, 2017

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Abstract

Abstract

Domestic earth observation satellites, such as ZY-3 and GF-1, have few image bands and limited spectral range. Focusing on those features, this paper outlines a cloud detection algorithm that automatically obtains the grey threshold through histogram fitting by the Gaussian Mixture Model. The algorithm obtains initial parameters automatically from the image histogram; and then it adjusts these parameters by iteration based on the Expectation Maximum principle. It automatically obtains the grey threshold between cloud and clear sky in a chosen image, in line with the distribution features of the components in the Gaussian Mixture Model. Experimental results show that this method has strong advantages, as the range of the spectral bands are not a limit and thus is suitable for both cloudy and cloudless images. In addition, the proposed method needs no auxillary information or manual intervention. It has high computational accuracy and efficiency meeting the requirements for automatic engineering production.
- Chinese high resolution satellite imagery,
- cloud detection,
- Gaussian mixture model,
- threshold

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References

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Gaussian Mixture Model Based Cloud Detection for Chinese High Resolution Satellite Imagery

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