@inproceedings{453f7f2898364c318a9f31e285071265,
title = "Shoreline data based sea-land segmentation method for on-orbit ship detection from panchromatic Images",
abstract = "Sea-land segmentation is a key procedure of ship detection. However, most of the existing sea-land segmentation methods are designed for on-ground ship detection. Consequently, the computational costs of these methods are too expensive to be implemented in on-orbit platforms. To tackle this problem, first, a shoreline database is built according to the global geographic information systems; then, the sea-land segmentation method is proposed by utilizing the corresponding coastline data, which is obtained from the database according to the latitude and longitude of the candidate area. Compared to the existing sea-land segmentation methods, this method is more suitable for on-orbit platforms, because of the less computational costs, higher efficient, and acceptable robustness. The experimental results based on raw panchromatic images demonstrated that the proposed method had a good performance in sea-land segmentation for on-orbit processing.",
keywords = "on-orbit processing, panchromatic images, sea-land segmentation, shoreline data",
author = "Xupeng Lin and Qizhi Xu and Chuanzhao Han",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 5th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2018 ; Conference date: 18-06-2018 Through 20-06-2018",
year = "2018",
month = dec,
day = "31",
doi = "10.1109/EORSA.2018.8598619",
language = "English",
series = "5th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2018 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Qihao Weng and Paolo Gamba and Ni-Bin Chang and Guangxing Wang and Wanqiang Yao",
booktitle = "5th International Workshop on Earth Observation and Remote Sensing Applications, EORSA 2018 - Proceedings",
address = "United States",
}