A lossless compression method based on vector quantization and linear prediction for 3D GIIRS datacubes
This paper designs a lossless compression scheme based on interferogram shape for 3D datacubes from the Geostationary Interferometric Infrared Sounder (GIIRS). According to the features of data, this scheme combines Vector Quantization with Linear Prediction to compress. The MATLAB simulations prove that the raised scheme is feasible. Finally, a Xilinx Zynq XC7020 HPSoC is employed to realize this scheme within 1.2508s, achieving compression ratios (CRs) from 3.79 to 3.95.
Authors
- Minzhu Yang
- Jiabin Yu (ORCID: https://orcid.org/0000-0002-4261-1585)
- Changpei Han (ORCID: https://orcid.org/0000-0001-9162-7367)
- Raúl Guerra (ORCID: https://orcid.org/0000-0002-4303-3051)
- José F. López (ORCID: https://orcid.org/0000-0002-6304-2801)
- Zhen Wu (ORCID: https://orcid.org/0009-0006-7982-2884)
Institutions
- Universidad de Las Palmas de Gran Canaria (ES)
- Shanghai Institute of Technical Physics (CN)
- China Jiliang University (CN)
Publication Details
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1109/itaic64559.2025.11163388
- Primary Topic
- Distributed and Parallel Computing Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00