Publication detail
Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith
SKOG, K. KOHOUT, T. KAŠPÁREK, T. WOLFMAYR, M.
Original Title
Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith
Type
journal article - other
Language
English
Original 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 compared two 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 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 found that JPEG 2000 achieved consistently higher compression ratios and benefited from decreased noise more than CCSDS 122.0. However, CCSDS 122.0 produced comparable results faster than JPEG 2000 and is substantially less computationally complex. These results not only support previous findings while contributing valuable knowledge to the behavioral characteristics of both algorithms but also provide insight for entities planning on using either algorithm for on-board of planetary missions.
Keywords
image compression, CCSDS 122.0, JPEG 2000, hyperspectral data, noise filtering, comet, asteroid
Authors
SKOG, K.; KOHOUT, T.; KAŠPÁREK, T.; WOLFMAYR, M.
Released
4. 3. 2025
ISBN
2072-4292
Periodical
Remote Sensing
Year of study
17
Number
899
State
Swiss Confederation
Pages from
1
Pages to
18
Pages count
18
URL
BibTex
@article{BUT193376,
author="SKOG, K. and KOHOUT, T. and KAŠPÁREK, T. and WOLFMAYR, M.",
title="Lossless Hyperspectral Image Compression in Comet Interceptor and Hera Missions with Restricted Bandwith",
journal="Remote Sensing",
year="2025",
volume="17",
number="899",
pages="1--18",
doi="10.3390/rs17050899",
issn="2072-4292",
url="https://www.mdpi.com/2072-4292/17/5/899"
}