@inproceedings{dd9aabb5f32f478c8cab401ab6279f24,
title = "An Improved Cloud Detection Method of Optical Remote Sensing Image",
abstract = "The effect of cloud cover on the quality of remote sensing data becomes an unavoidable problem when dealing with a large amount of remote sensing data obtained from satellite sensors. As an important meteorological element, cloud plays a vital role in all areas of atmospheric science. In this paper, we propose a cloud detection method based on multi-feature hierarchical judgement. First, the gray histogram of the object to be interpreted is extracted and the histogram is intercepted to remove the singular value. Then, five types of feature are employed in feature extraction. After that, the objects to be interpreted is divided into single type and mixed type, and mixed type can be further divided into certain mixed type and uncertain type. Finally, threshold method and support vector machine(SVM) are employed to classify these types. Experiment has shown good performance of the proposed method.",
keywords = "Cloud detection, Feature extraction, Remote sensing",
author = "Yang Gao and Zhou, {Hao Tian} and Liang Chen",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2017 ; Conference date: 13-09-2017 Through 15-09-2017",
year = "2018",
doi = "10.1007/978-981-10-7521-6_32",
language = "English",
isbn = "9789811075209",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "265--271",
editor = "Songlin Sun and Na Chen and Tao Tian",
booktitle = "Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC",
address = "Germany",
}