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Article

Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith

1
School of Electrical Engineering, Aalto University, P.O. Box 15500, 00076 Aalto, Finland
2
Institute of Geology, Czech Academy of Sciences, Rozvojová 269, 165 00 Prague 6, Czech Republic
3
Department of Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
4
Faculty of Information Technology, Brno University of Technology, 612 00 Brno, Czech Republic
5
Institute of Information Technology, Jamk University of Applied Sciences, 40101 Jyväskylä, Finland
6
Faculty of Information Technology, University of Jyväskylä, 40014 Jyväskylä, Finland
*
Author to whom correspondence should be addressed.
Remote Sens. 2025, 17(5), 899; https://doi.org/10.3390/rs17050899
Submission received: 8 November 2024 / Revised: 26 February 2025 / Accepted: 27 February 2025 / Published: 4 March 2025
(This article belongs to the Section Remote Sensing Image Processing)

Abstract

Lossless image compression is vital for missions with limited data transmission bandwidth. Reducing file sizes enables faster transmission and increased scientific gains from transient events. This study compares two wavelet-based image compression algorithms, CCSDS 122.0 and JPEG 2000, used in the European Space Agency Comet Interceptor and Hera missions, respectively, in varying scenarios. The JPEG 2000 implementation is sourced from the JasPer library, whereas a custom implementation was written for CCSDS 122.0. The performance analysis for both algorithms consists of compressing simulated asteroid images in the visible and near-infrared spectral ranges. In addition, all test images were noise-filtered to study the effect of the amount of noise on both compression ratio and speed. The study finds that JPEG 2000 achieves consistently higher compression ratios and benefits from decreased noise more than CCSDS 122.0. However, CCSDS 122.0 produces comparable results faster than JPEG 2000 and is substantially less computationally complex. On the contrary, JPEG 2000 allows dynamic (entropy-permitting) reduction in the bit depth of internal data structures to 8 bits, halving the memory allocation, while CCSDS 122.0 always works in 16-bit mode. These results contribute valuable knowledge to the behavioral characteristics of both algorithms and provide insight for entities planning on using either algorithm on board planetary missions.
Keywords: image compression; CCSDS 122.0; JPEG 2000; hyperspectral; noise filtering; Didymos; Dimorphos; comet image compression; CCSDS 122.0; JPEG 2000; hyperspectral; noise filtering; Didymos; Dimorphos; comet

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MDPI and ACS Style

Skog, K.; Kohout, T.; Kašpárek, T.; Penttilä, A.; Wolfmayr, M.; Praks, J. Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith. Remote Sens. 2025, 17, 899. https://doi.org/10.3390/rs17050899

AMA Style

Skog K, Kohout T, Kašpárek T, Penttilä A, Wolfmayr M, Praks J. Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith. Remote Sensing. 2025; 17(5):899. https://doi.org/10.3390/rs17050899

Chicago/Turabian Style

Skog, Kasper, Tomáš Kohout, Tomáš Kašpárek, Antti Penttilä, Monika Wolfmayr, and Jaan Praks. 2025. "Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith" Remote Sensing 17, no. 5: 899. https://doi.org/10.3390/rs17050899

APA Style

Skog, K., Kohout, T., Kašpárek, T., Penttilä, A., Wolfmayr, M., & Praks, J. (2025). Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith. Remote Sensing, 17(5), 899. https://doi.org/10.3390/rs17050899

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