Hyperspectral remote sensing data compression with neural networks

2022 Data Compression Conference (DCC)(2022)

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摘要
Hyperspectral images are typically highly correlated along their spectrum, and this similarity is usually found to cluster in intervals of consecutive bands. We identified 5 such intervals in AVIRIS uncalibrated data (i.e., as captured on-board). These 5 intervals maximised the average spectral correlation along the 224 band spectrum. The resulting in-tervals were composed of bands 1–40, 41–96, 97–155, 156–165, and 166–224, as seen in the figure to the right.
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关键词
hyperspectral remote sensing data compression,neural networks,hyperspectral images,consecutive bands,AVIRIS uncalibrated data,captured on-board,average spectral correlation,band spectrum
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