Report
Towards Loss-Resilient Image Coding for Unstable Satellite Networks
| العنوان: | Towards Loss-Resilient Image Coding for Unstable Satellite Networks |
|---|---|
| المؤلفون: | Sha, Hongwei, Dong, Muchen, Luo, Quanyou, Lu, Ming, Chen, Hao, Ma, Zhan |
| سنة النشر: | 2025 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing |
| الوصف: | 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. Comment: Accepted as a poster presentation at AAAI 2025 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2501.11263 |
| رقم الانضمام: | edsarx.2501.11263 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |