@inproceedings{45cd85bbc9d44f0ebd5a7d36736f35a3,
title = "SAR target detection based on PSIFT feature clustering",
abstract = "Aiming at the problem that it is difficult to obtain a big SAR target set with different angles, a sample-free SAR target detection method is proposed in this paper. This new method adopts PSIFT features with rotation invariance to describe the texture of potential targets, and divides the features of potential targets into target regions and non-target regions through NCM clustering. This method proposed of this paper can realize the automatic detection of SAR targets, and is also effective for targets with different orientation. The experimental results verify the feasibility and validity of the proposed method.",
keywords = "NCM clustering, PSIFT feature, SAR images, Target detection",
author = "Lina Zeng and Deyun Zhou and Qian Pan and Chao Lu and Ying Zhou",
note = "Publisher Copyright: {\textcopyright}2019 IEEE; 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 ; Conference date: 28-07-2019 Through 02-08-2019",
year = "2019",
doi = "10.1109/IGARSS.2019.8900284",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS) ",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "17--20",
booktitle = "2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings",
}