TYPICAL DATA MODELS ARE INADEQUATE FOR HYPERTEMPORAL IMAGERY

被引：0

作者：

Rosario, Dalton ^{[1
]}

Romano, Joao ^{[2
]}

机构：

[1] Army Res Lab, Adelphi, MD USA

[2] Arrny Armament RDEC, Picatinny Arsenal, NJ USA

来源：

2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2015年

关键词：

Persistent imaging; longwave infrared;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We highlight challenges associated with using conventional pattern recognition methods to test imagery from a persistent longwave infrared remote sensing experiment, where material surface emissivity and temperature among other factors dominate the apparent radiance observed at the sensor. We also propose a superior data model for the task.

引用

页码：3691 / 3694

页数：4

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