| Home > Articles > Published articles > Performance Improvement on k2-Raster Compact Data Structure for Hyperspectral Scenes |
| Date: | 2021 |
| Abstract: | This letter proposes methods to improve data size and access time for k2-raster, a losslessly compressed data structure that provides efficient storage and real-time processing. Hyperspectral scenes from real missions are used as our testing data. In previous studies, with k2-raster, the size of the hyperspectral data was reduced by up to 52% compared with the uncompressed data. In this letter, we continue to explore novel ways of further reducing the data size and access time. First, we examine the possibility of using the raster matrix of hyperspectral data without any padding (unpadded matrix) while still being able to compress the structure and access the data. Second, we examine some integer encoders, more specifically the Simple family. We discuss their ability to provide random element access and compare them with directly addressable codes (DACs), the integer encoder used in the original description for k2 -raster. Experiments show that the use of unpadded matrices has improved the storage size up to 6% while the use of a different integer encoder reduces the storage size up to 6% and element access time up to 20%. |
| Grants: | Agencia Estatal de Investigación RTI2018-095287-B-I00 Agencia Estatal de Investigación BES-2016-078369 Generalitat de Catalunya 2017/SGR-463 Generalitat de Catalunya 2018/BP-00008 European Commission 801370 |
| Rights: | 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. |
| Language: | Anglès |
| Document: | Article ; recerca ; Versió publicada |
| Subject: | Directly addressable codes (DACs) ; Image compression ; Lossless hyperspectral imaging ; PForDelta ; Remote sensing ; Simple-9 ; Simple-16 |
| Published in: | IEEE Geoscience and Remote Sensing Letters, Vol. 19 (June 2021) , art. 5506605, ISSN 1558-0571 |
5 p, 1.6 MB |