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  3. Volume 7, Number 2, 2025
  4. Methods for Parallelizing the Compression of Video Streams From Earth Surface Scanners

Methods for Parallelizing the Compression of Video Streams From Earth Surface Scanners

CSN.
2025;
Volume 7, Number 2
: pp. 43 - 49
https://doi.org/10.23939/csn2025.02.043
Authors:
  1. T. L. Hrytsko
  2. V. S. Hlukhov
1
Lviv Polytechnic National University, Department of Electronic Computing Machines, Ukraine
2
L’viv Polytechnic National University, Department of Electronic Computing Machines, Ukraine

This article proposes three methods for parallelizing the compression of video streams from Earth surface scanners installed on microsatellites. The core innovation lies in the application of vertical, horizontal, and block-based segmentation of the input stream to enable scalable and high-throughput image compression. The study establishes a quantitative relationship between video stream intensity and satellite parameters, and also determines the required number of compression cores based on the satellite's characteristics and the performance of a single core. The proposed methods are designed to support real- time, resource-efficient onboard compression for modern Earth observation missions. It was calculated that for an 8-bit monochrome scanner, the video stream rate ranges from approximately 45 Mbit/s to 6.46 Gbit/s. The required number of compression cores was determined to be from 1 (where sequential processing is sufficient) to 5, assuming a single-core throughput of 1.434 Gbit/s.

JPEG-LS
FPGA
Field-programmable gate arrays
image compression
image processing
Video compression
Video stream processing
parallelization
  1. Weinberger M. J., Seroussi G., Sapiro G. The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS. IEEE Transactions on Image Processing, vol. 9, no. 8, pp. 1309–1324, Aug. 2000. DOI: 10.1109/83.855427.
  2. Regoršek Ž., Gorkič A., Trost A. Parallel Lossless Compression of Raw Bayer Images on FPGA-Based High- Speed Camera. Sensors, vol. 24, no. 20, Art. no. 20, Jan. 2024. DOI: 10.3390/s24206632.
  3. Hrytsko T., Lenskiy D., Hlukhov V. Review of the Capabilities of the Jpeg-ls Algorithm for Its Use With Earth Surface  Scanners.  Scientific  journal  “Computer  Systems  and  Networks”,  vol.  6,  pp.  17-19,  Dec.  2024.  DOI: 10.23939/csn2024.02.015.
  4. Wang X., Gong L., Wang C., Li X., Zhou X. UH-JLS: A Parallel Ultra-High Throughput JPEG-LS Encoding Architecture for Lossless Image Compression, in 2021 IEEE 39th International Conference on Computer Design (ICCD), Oct. 2021, pp. 335–343. DOI: 10.1109/ICCD53106.2021.00060.
  5. Duan H., Fang Y., Huang B. Parallel design of JPEG-LS encoder on graphics processing units. JARS, vol. 6, no. 1, p. 061508, Sep. 2012. DOI: 10.1117/1.JRS.6.061508.
  6. Sullivan G. J. et al. Overview of the High Efficiency Video Coding (HEVC) standard. IEEE Transactions on Circuits and Systems for Video Technology. 2012. 22(12), 1649–1668.
  7. “SICH-3O.” Accessed: May 04, 2025. URL: https://www.nkau.gov.ua/en/space-complexes/spacecraft/sich-3o.
  8. “SICH-2-1” Accessed: July 24, 2025. URL: https://www.nkau.gov.ua/en/space-complexes/spacecraft/sich-2-1.
  9. ‘Maxar WorldView-4 Data Sheet | L3Harris® Fast. Forward.’ Accessed: May 03, 2025. URL: https://www.l3harris.com/resources/maxar-worldview-4-data-sheet.
  10. Dawwd S., Fathi F. Hardware Implementation of 2D convolution on FPGA. 2023.
  11. Ustin S. L., Middleton E. M. Current and Near-Term Earth-Observing Environmental Satellites, Their Missions, Characteristics, Instruments, and Applications. Sensors, vol. 24, no. 11, Art. no. 11, Jan. 2024. DOI: 10.3390/s24113488.
  12. ‘Searchable Table of Earth Observation Satellite Missions | CEOS Database’. Accessed: Jun. 29, 2025. [Online]. Available: https://database.eohandbook.com/database/missiontable.aspx.
  13. Hinnerson M. ‘A Resource Efficient, High Speed FPGA Implementation of Lossless Image Compression for 3D Vision’, Dissertation, 2019, oai: DiVA.org:liu-165300.
  14. Sullivan G. J., Ohm J.-R., Han W.-J., Wiegand T. Overview of the High Efficiency Video Coding (HEVC) Standard, in IEEE Transactions on Circuits and Systems for Video Technology, vol. 22, no. 12, pp. 1649-1668, Dec. 2012. DOI: 10.1109/TCSVT.2012.2221191.
  15. Грицько Т., Глухов В. ‘Розпаралелювання стиску зображень зі сканерів земної поверхні’, Міжнародна науково – практична конференція Інформаційні технології та комп’ютерне моделювання, pp. 78–80, May 2025, Accessed: Sept. 18, 2025. URL: https://journal.comp-sc.if.ua/test/index.php/ITCM/article/view/670.
  16. Hrytsko T., Hlukhov V. Satellite Image Compression Parallelization Methods in 13th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, Sep. 2025.