Channel-Adaptive Region Adjacency Graph Carriers for Semantic Image Communication
Semantic image communication seeks to preserve task-relevant scene structure under limited channel resources, but carriers are often dense latent tensors or grid-aligned semantic layouts that do not explicitly encode region-level relations. This work introduces a segmentation-derived region adjacency graph (RAG) carrier, termed channel-adaptive RAG (CA-RAG), for joint source-channel coding-style image communication. Nodes store interpretable region attributes, edges preserve adjacency, channel-adaptive graph simplification (CGS) controls the node budget, and semantic belief propagation refines noisy graph embeddings before diffusion-based reconstruction. On Cityscapes, pre-channel RAG pay...
| Authors | Karim Abdallah, Maria Slim, Mariette Awad et al. |
|---|---|
| Primary category | eess.SP |
| Published | 13 September 2026 |
| Last updated at source | 13 September 2026 |
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