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/10.48550/arxiv.2501.11263
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2501.11263
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. Code is available at https://github.com/NJUVISION/LossResilientLIC.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2501.11263
- https://arxiv.org/pdf/2501.11263
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4406734990
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4406734990Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2501.11263Digital Object Identifier
- Title
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Towards Loss-Resilient Image Coding for Unstable Satellite NetworksWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-01-20Full publication date if available
- Authors
-
Hongwei Sha, Muchen Dong, Qingming Luo, Ming‐De Lu, Hao Chen, Zhan MaList of authors in order
- Landing page
-
https://arxiv.org/abs/2501.11263Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2501.11263Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2501.11263Direct OA link when available
- Concepts
-
Satellite image, Satellite, Coding (social sciences), Computer science, Image (mathematics), Telecommunications, Computer vision, Artificial intelligence, Mathematics, Engineering, Aerospace engineering, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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