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Efficient Lossless Compression of 4D Hyperspectral Image Data

机译:高效无损压缩4D高光谱图像数据

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Time-lapse hyperspectral imaging technology has been used for various remote sensing applications due to its excellent capability of monitoring regions of interest over a period of time. However, large data volume of four-dimensional hyperspectral imagery demands for massive data compression techniques. While conventional 3D hy-perspectral data compression methods exploit only spatial and spectral correlations, we proposed a novel lossless compression algorithm that can achieve significant gains on compression efficiency by also taking into account temporal correlations inherent in the dataset. Experimental results demonstrated the effectiveness of the proposed algorithm.
机译:由于其在一段时间内监测感兴趣区域的优异能力,延时高光谱成像技术已被用于各种遥感应用。但是,大量数据量为大规模数据压缩技术的四维高光谱图像要求。虽然传统的3D Hy-Perspectral数据压缩方法仅利用空间和光谱相关性,但我们提出了一种新的无损压缩算法,可以通过考虑数据集中固有的时间相关性来实现压缩效率的显着增益。实验结果表明了该算法的有效性。

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