LWIR中基于高光谱与基于偏振的异常检测

D. Rosario, J. Romano
{"title":"LWIR中基于高光谱与基于偏振的异常检测","authors":"D. Rosario, J. Romano","doi":"10.1109/WHISPERS.2016.8071660","DOIUrl":null,"url":null,"abstract":"We examine for the first time in the scientific community the application of hyperspectral (HS) based anomaly detection in contrast to polarimetric (POL) based anomaly detection in the longwave infrared region of the spectrum, using a challenging dataset for the test that covers three diurnal cycles. For fairness, we standardized for both sensing modalities the characterization of the unknown background clutter through a repeated trial Binomial based random sampling approach, and attained in the process two new methods for anomaly detection. The POL method outperformed the HS method, especially in the most difficult time periods, between sunset and sunrise, by an average of 0.47 augmented performance.","PeriodicalId":369281,"journal":{"name":"2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hyperspectral-based verses polarimetric-based anomaly detection in the LWIR\",\"authors\":\"D. Rosario, J. Romano\",\"doi\":\"10.1109/WHISPERS.2016.8071660\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We examine for the first time in the scientific community the application of hyperspectral (HS) based anomaly detection in contrast to polarimetric (POL) based anomaly detection in the longwave infrared region of the spectrum, using a challenging dataset for the test that covers three diurnal cycles. For fairness, we standardized for both sensing modalities the characterization of the unknown background clutter through a repeated trial Binomial based random sampling approach, and attained in the process two new methods for anomaly detection. The POL method outperformed the HS method, especially in the most difficult time periods, between sunset and sunrise, by an average of 0.47 augmented performance.\",\"PeriodicalId\":369281,\"journal\":{\"name\":\"2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WHISPERS.2016.8071660\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WHISPERS.2016.8071660","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

我们首次在科学界研究了基于高光谱(HS)的异常检测与基于极化(POL)的异常检测在光谱长波红外区域的应用,使用了一个具有挑战性的数据集进行测试,该数据集涵盖了三个昼夜周期。为了公平起见,我们通过重复试验二项随机抽样方法标准化了两种感知方式对未知背景杂波的表征,并在此过程中获得了两种新的异常检测方法。POL方法的性能优于HS方法,特别是在最困难的时间段(日落和日出之间),平均增强性能为0.47。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Hyperspectral-based verses polarimetric-based anomaly detection in the LWIR
We examine for the first time in the scientific community the application of hyperspectral (HS) based anomaly detection in contrast to polarimetric (POL) based anomaly detection in the longwave infrared region of the spectrum, using a challenging dataset for the test that covers three diurnal cycles. For fairness, we standardized for both sensing modalities the characterization of the unknown background clutter through a repeated trial Binomial based random sampling approach, and attained in the process two new methods for anomaly detection. The POL method outperformed the HS method, especially in the most difficult time periods, between sunset and sunrise, by an average of 0.47 augmented performance.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Hyperspectral and color-infrared imaging from ultralight aircraft: Potential to recognize tree species in urban environments Mapping land covers of brussels capital region using spatially enhanced hyperspectral images Morpho-spectral objects classification by hyperspectral airborne imagery Land-cover monitoring using time-series hyperspectral data via fractional-order darwinian particle swarm optimization segmentation Nonnegative CP decomposition of multiangle hyperspectral data: A case study on CRISM observations of Martian ICY surface
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1