A Scalable Reduced-Complexity Compression of Hyperspectral Remote Sensing Images Using Deep Learning
Sebastià Mijares i Verdú,
Johannes Ballé,
Valero Laparra
et al.
Abstract:Two key hurdles to the adoption of Machine Learning (ML) techniques in hyperspectral data compression are computational complexity and scalability for large numbers of bands. These are due to the limited computing capacity available in remote sensing platforms and the high computational cost of compression algorithms for hyperspectral data, especially when the number of bands is large. To address these issues, a channel clusterisation strategy is proposed, which reduces the computational demands of learned com… Show more
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