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Thermal infrared hyperspectral data compression

机译:热红外高光谱数据压缩

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Abstract: Hyperspectral imagers sample the electromagnetic spectrum at greater resolution than more traditional imaging systems, which result in a higher band-to-band correlation and greater amounts of data. With bandwidth limitations on the communications channels and storage space, intelligent system design, band selection, and/or data compression will be very important. The data from a new hyperspectral sensor, SEBASS, which collects data in the thermal IR was characterized for compression. As expected, it was found that the data's spectral characteristics were very dependent on scheme content and the collection time of day. It was found that the band-to-band correlation was greater in this data than either HYDICE or AVIRIS hyperspectral data. Compression ratios of 7:1 lossless and 20:1 with minimal loss were achieved compared to 3:1 lossless and 7:1 lossy for HYDICE and AVIRIS data. This increase in compression is directly attributable to the increase in band-to-band correlation. Unique characteristics of the thermal IR hyperspectral data is also discussed. !7
机译:摘要:高光谱成像仪以比传统成像系统更高的分辨率对电磁频谱进行采样,这导致更高的带间相关性和更多的数据量。由于通信通道和存储空间的带宽限制,智能系统设计,频带选择和/或数据压缩将非常重要。来自新的高光谱传感器SEBASS的数据进行了压缩,该传感器在热红外中收集数据。如预期的那样,发现数据的光谱特性非常依赖于方案内容和一天中的采集时间。发现该数据中的带间相关性大于HYDICE或AVIRIS高光谱数据。与HYDICE和AVIRIS数据的3:1无损和7:1有损相比,压缩比达到7:1无损和20:1,损失极小。压缩的增加直接归因于频带间相关性的增加。还讨论了热红外高光谱数据的独特特征。 !7

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