@inproceedings{c62c88cd5cb64a9789a6d40ae3d53d71,
title = "Automatic threshold selection method for SAR edge detection",
abstract = "In order to reduce the manual intervention and calculate amount in edge detection processing, an automatic threshold selection method for edge detection of synthetic aperture radar (SAR) images is proposed. The proposed automatic threshold selection (ATS) method determines the optimal thresholds by establishing a relationship between different thresholds and corresponding detection results. The thresholds chosen by the proposed ATS method are very close to the thresholds determined by manual intervention. Comparing with conventional method, ratio-based detectors with ATS obviously reduce the calculate amount and ensure the accuracy of edge detection at the same time, benefiting from less manual intervention and almost the same thresholds. The experimental results on SAR images show that ratio-based detectors combined with the proposed ATS method not only achieve the accurate detection results, but also effectively reduce the time consumption during thresholds selection.",
keywords = "Automatic threshold selection method, Edge detection, Synthetic aperture radar (SAR)",
author = "Pengyi Xie and Jiangbin Zheng and Qianru Wei and Yuke Wang",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 10th International Conference on Brain Inspired Cognitive Systems, BICS 2019 ; Conference date: 13-07-2019 Through 14-07-2019",
year = "2020",
doi = "10.1007/978-3-030-39431-8_51",
language = "英语",
isbn = "9783030394301",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "530--539",
editor = "Jinchang Ren and Amir Hussain and Huimin Zhao and Jun Cai and Rongjun Chen and Yinyin Xiao and Kaizhu Huang and Jiangbin Zheng",
booktitle = "Advances in Brain Inspired Cognitive Systems - 10th International Conference, BICS 2019, Proceedings",
}