The parametrically adjusted hyperspectral data compression algorithm based on wavelet decomposition
Abstract
The parametrically adjusted hyperspectral data compression algorithm based on wavelet decomposition is presented. Data stream compression throughput assessment depending on wavelet decomposition level is carried out, the overall performance of the presented algorithm is estimated.
About the Authors
D. Y. Pertsau
Belarusian state university of informatics and radioelectronics
Belarus
junior researcher of R&D department
Belarus
junior researcher of R&D department
A. A. Doudkin
United institute of informatics problems of NAS of Belarus
Belarus
Belarus
Doudkin Alexander Arsent'evich - D.Sci, professor, head of the laboratory of system identification
220012, Minsk, Surganova st., 6
References
1. Airborne Visible/Infrared Imaging Spectrometer. Официальный портал AVIRIS [Electronic resource]. URL: http://aviris.jpl.nasa.gov/ (date of access: 20.04.2018).
2. Klimesh M. Low-complexity lossless compression of hyperspectral imagery via adaptive filtering. Technical Report 42-163, Jet Propulsion Laboratory, California Institute of Technology, 2005.
3. Pizzolante R. Lossless compression of hyperspectral imagery // Proc. of the First International Conference on Data Compression, Communications and Processing. 2011. P. 157–162.
4. Wang H., Babacan S.D., Sayood K. Lossless hyperspectral-image compression using context-based conditional average // Geoscience and Remote Sensing, IEEE Transactions on. 2007. Vol. 45, iss. 12. P. 4187–4193.
5. Magli E., Olmo G., Quacchio E. Optimized onboard lossless and near-lossless compression of hyperspectral data using CALIC // Geoscience and Remote Sensing Letters, IEEE. 2004. Vol. 1, iss. 1. P. 21–25.
6. Huang B., Sriraja Y. Lossless compression of hyperspectral imagery via lookup tables with predictor selection // Proc. Image and Signal Processing for Remote Sensing XII. 2006. Vol. 63–65. P. 131–139.
7. Mielikainen J., Toivanen P. Lossless compression of hyperspectral images using a quantized index to lookup tables // Geoscience and Remote Sensing Letters, IEEE. 2008. Vol. 5, iss. 3. P. 474–478.
8. Chang C.-I. Hyperspectral data processing: algorithm design and analysis. New York: John Wiley & Sons, 2013. 1164 p.
9. Sayood Kh. Introduction to Data Compression. Morgan Kaufmann, 2017. 765 p.
Review
For citations:
Pertsau D.Y., Doudkin A.A. The parametrically adjusted hyperspectral data compression algorithm based on wavelet decomposition. Doklady BGUIR. 2019;(1):26-31. (In Russ.)
Views: 736
Email this article 