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Pàgina inicial > Articles > Articles publicats > High-performance lossless compression of hyperspectral remote sensing scenes based on spectral decorrelation |
Data: | 2020 |
Resum: | The capacity of the downlink channel is a major bottleneck for applications based on remote sensing hyperspectral imagery (HSI). Data compression is an essential tool to maximize the amount of HSI scenes that can be retrieved on the ground. At the same time, energy and hardware constraints of spaceborne devices impose limitations on the complexity of practical compression algorithms. To avoid any distortion in the analysis of the HSI data, only lossless compression is considered in this study. This work aims at finding the most advantageous compression-complexity trade-off within the state of the art in HSI compression. To do so, a novel comparison of the most competitive spectral decorrelation approaches combined with the best performing low-complexity compressors of the state is presented. Compression performance and execution time results are obtained for a set of 47 HSI scenes produced by 14 different sensors in real remote sensing missions. Assuming only a limited amount of energy is available, obtained data suggest that the FAPEC algorithm yields the best trade-off. When compared to the CCSDS 123. 0-B-2 standard, FAPEC is 5. 0 times faster and its compressed data rates are on average within 16% of the CCSDS standard. In scenarios where energy constraints can be relaxed, CCSDS 123. 0-B-2 yields the best average compression results of all evaluated methods. |
Ajuts: | Ministerio de Economía y Competitividad RTI2018-095287-B-I00 Ministerio de Economía y Competitividad TIN2015-71126-R Ministerio de Economía y Competitividad RTI2018-095076-B-C21 Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-463 Agència de Gestió d'Ajuts Universitaris i de Recerca 2018/BP-00008 European Commission 801370 |
Drets: | Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. |
Llengua: | Anglès |
Document: | Article ; recerca ; Versió publicada |
Matèria: | Multispectral ; Hyperspectral ; CCSDS ; FAPEC ; Data compression ; Transform |
Publicat a: | Remote sensing (Basel), Vol. 12, Núm. 18 (September 2020) , art. 2955, ISSN 2072-4292 |
16 p, 929.4 KB |