@inproceedings{f18f804bbfc142c08f2b0a54ab1133fc,
title = "Removing thin cloud from remote sensing digital images based on robust kernel regression",
abstract = "This paper suggests a thin cloud removing approach of remote sensing image based on robust kernel regression. Due to the influence of atmosphere condition, cloud cover is one of the most disturbance factors in remote sensing image. So cloud removal is a very important step for improving the quality of the image before making analysis. Because thin cloud is the low frequency component in remote sensing images, thin cloud can be removed efficiently by using the method introduced in this paper.",
keywords = "cloud removing, kernel regression, N-term Taylor series, robust optimization",
author = "Guohong Liang and Ying Li",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Orange Technologies, ICOT 2014 ; Conference date: 20-09-2014 Through 23-09-2014",
year = "2014",
month = nov,
day = "12",
doi = "10.1109/ICOT.2014.6956636",
language = "英语",
series = "IEEE International Conference on Orange Technologies, ICOT 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "209--211",
booktitle = "IEEE International Conference on Orange Technologies, ICOT 2014",
}