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First observations using SPICE hyperspectral dataset

机译：使用SPICE高光谱数据集的首次观察

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Our first observations using the longwave infrared (LWIR) hyperspectral data subset of the Spectral and Polarimetric Imagery Collection Experiment (SPICE) database are summarized in this paper, focusing on the inherent challenges associated with using this sensing modality for the purpose of object pattern recognition. Emphases are also put on data quality, qualitative validation of expected atmospheric spectral features, and qualitative comparison against another dataset of the same site using a different LWIR hyperspectral sensor. SPICE is a collaborative effort between the Army Research Laboratory, U.S. Army Armament RDEC, and more recently the Air Force Institute of Technology. It focuses on the collection and exploitation of longwave and midwave infrared (LWIR and MWIR) hyperspectral and polarimetric imagery. We concluded from this work that the quality of SPICE hyperspectral LWIR data is categorically comparable to other datasets recorded by a different sensor of similar specs; and adequate for algorithm research, given the scope of SPICE. The scope was to conduct a long-term infrared data collection of the same site with targets, using both sensing modalities, under various weather and non-ideal conditions. Then use the vast dataset and associated ground truth information to assess performance of the state of the art algorithms, while determining performance degradation sources. The expectation is that results from these assessments will spur new algorithmic ideas with the potential to augment pattern recognition performance in remote sensing applications. Over time, we are confident the SPICE database will prove to be an asset to the wide open remote sensing community.
机译：本文总结了我们使用光谱和极化影像收集实验（SPICE）数据库的长波红外（LWIR）高光谱数据子集的第一个观察结果，重点关注与使用这种传感方式进行目标模式识别相关的固有挑战。重点还放在数据质量，预期大气光谱特征的定性验证以及使用不同的LWIR高光谱传感器与同一站点的另一个数据集的定性比较上。 SPICE是美国陆军装备RDEC的陆军研究实验室与最近的空军技术学院之间的共同努力。它专注于长波和中波红外（LWIR和MWIR）高光谱和偏振图像的收集和开发。我们从这项工作得出的结论是，SPICE高光谱LWIR数据的质量在类别上可以与其他由类似规格的传感器记录的数据集相比。在SPICE的范围内，足够进行算法研究。范围是在各种天气和非理想条件下，使用两种感应方式，对具有目标的同一地点进行长期红外数据收集。然后使用庞大的数据集和相关的地面真相信息来评估最新算法的性能，同时确定性能下降的来源。期望这些评估的结果将激发新的算法思想，并有可能增强遥感应用中的模式识别性能。随着时间的流逝，我们相信SPICE数据库将成为广泛开放的遥感社区的资产。

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