Semantic-Aware Visual Information Transmission With Key Information Extraction Over Wireless Networks

• URL: http://arxiv.org/abs/2506.12786v1
• Date: Sun, 15 Jun 2025 09:32:48 GMT
• Title: Semantic-Aware Visual Information Transmission With Key Information Extraction Over Wireless Networks
• Authors: Chen Zhu, Kang Liang, Jianrong Bao, Zhouxiang Zhao, Zhaohui Yang, Zhaoyang Zhang, Mohammad Shikh-Bahaei,
• Abstract summary: This paper proposes an AI-native deep joint source-channel coding (JSCC) framework tailored for resource-constrained 6G networks.<n>Our approach integrates key information extraction and adaptive background synthesis to enable intelligent, semantic-aware transmission.
• Score: 34.11565549404313
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The advent of 6G networks demands unprecedented levels of intelligence, adaptability, and efficiency to address challenges such as ultra-high-speed data transmission, ultra-low latency, and massive connectivity in dynamic environments. Traditional wireless image transmission frameworks, reliant on static configurations and isolated source-channel coding, struggle to balance computational efficiency, robustness, and quality under fluctuating channel conditions. To bridge this gap, this paper proposes an AI-native deep joint source-channel coding (JSCC) framework tailored for resource-constrained 6G networks. Our approach integrates key information extraction and adaptive background synthesis to enable intelligent, semantic-aware transmission. Leveraging AI-driven tools, Mediapipe for human pose detection and Rembg for background removal, the model dynamically isolates foreground features and matches backgrounds from a pre-trained library, reducing data payloads while preserving visual fidelity. Experimental results demonstrate significant improvements in peak signal-to-noise ratio (PSNR) compared with traditional JSCC method, especially under low-SNR conditions. This approach offers a practical solution for multimedia services in resource-constrained mobile communications.

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