Scholarlink

<p>Distributed compressive video sensing (DCVS) for wireless visual sensor networks faces challenges due to computational limitations and bandwidth constraints. This paper presents a rate-adaptive DCVS scheme that dynamically allocates measurements based on temporal correlation and sparsity estimation. By skipping highly correlated blocks and adaptively sampling others, the proposed method achieves improved rate-distortion performance with reduced sampling complexity and transmission burden. Experimental results demonstrate substantial gains over state-of-the-art methods, especially for videos with low motion speeds. Codes and data are available at <a href="https://github.com/SongHere/USE_DCVS">https://github.com/SongHere/USE_DCVS</a>.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Adaptive rate compression for distributed video sensing in wireless visual sensor networks

  • 期刊论文

  • 发表日期：

    2025年3月3日

查看全文
  • Zhen Song,
  • Jianhua Chen

摘要

Distributed compressive video sensing (DCVS) for wireless visual sensor networks faces challenges due to computational limitations and bandwidth constraints. This paper presents a rate-adaptive DCVS scheme that dynamically allocates measurements based on temporal correlation and sparsity estimation. By skipping highly correlated blocks and adaptively sampling others, the proposed method achieves improved rate-distortion performance with reduced sampling complexity and transmission burden. Experimental results demonstrate substantial gains over state-of-the-art methods, especially for videos with low motion speeds. Codes and data are available at https://github.com/SongHere/USE_DCVS.