Towards Loss-Resilient Image Coding for Unstable Satellite Networks Article Swipe
Hongwei Sha
,
Muchen Dong
,
Qingming Luo
,
Ming‐De Lu
,
Hao Chen
,
Zhan Ma
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v39i12.33363
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v39i12.33363
Geostationary Earth Orbit (GEO) satellite communication demonstrates significant advantages in emergency short burst data services. However, unstable satellite networks, particularly those with frequent packet loss, present a severe challenge to accurate image transmission. To address it, we propose a loss-resilient image coding approach that leverages end-to-end optimization in learned image compression (LIC). Our method builds on the channel-wise progressive coding framework, incorporating Spatial-Channel Rearrangement (SCR) on the encoder side and Mask Conditional Aggregation (MCA) on the decoder side to improve reconstruction quality with unpredictable errors. By integrating the Gilbert-Elliot model into the training process, we enhance the model's ability to generalize in real-world network conditions. Extensive evaluations show that our approach outperforms traditional and deep learning-based methods in terms of compression performance and stability under diverse packet loss, offering robust and efficient progressive transmission even in challenging environments.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v39i12.33363
- https://ojs.aaai.org/index.php/AAAI/article/download/33363/35518
- OA Status
- diamond
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409364733
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4409364733Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1609/aaai.v39i12.33363Digital Object Identifier
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Towards Loss-Resilient Image Coding for Unstable Satellite NetworksWork title
- Type
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
- Publication date
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2025-04-11Full publication date if available
- Authors
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Hongwei Sha, Muchen Dong, Qingming Luo, Ming‐De Lu, Hao Chen, Zhan MaList of authors in order
- Landing page
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https://doi.org/10.1609/aaai.v39i12.33363Publisher landing page
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https://ojs.aaai.org/index.php/AAAI/article/download/33363/35518Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://ojs.aaai.org/index.php/AAAI/article/download/33363/35518Direct OA link when available
- Concepts
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Satellite image, Satellite, Coding (social sciences), Computer science, Image (mathematics), Remote sensing, Artificial intelligence, Computer vision, Geology, Mathematics, Physics, Astronomy, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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26Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.optimization | 46 |
| abstract_inverted_index.particularly | 19 |
| abstract_inverted_index.transmission | 133 |
| abstract_inverted_index.Geostationary | 0 |
| abstract_inverted_index.Rearrangement | 63 |
| abstract_inverted_index.communication | 5 |
| abstract_inverted_index.environments. | 137 |
| abstract_inverted_index.incorporating | 61 |
| abstract_inverted_index.transmission. | 32 |
| abstract_inverted_index.unpredictable | 83 |
| abstract_inverted_index.Gilbert-Elliot | 88 |
| abstract_inverted_index.learning-based | 115 |
| abstract_inverted_index.loss-resilient | 39 |
| abstract_inverted_index.reconstruction | 80 |
| abstract_inverted_index.Spatial-Channel | 62 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.17572693 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |