Department of Computer Information Science, Korea University, Sejong KS002, Korea.
Sensors (Basel). 2012 Nov 1;12(11):14647-70. doi: 10.3390/s121114647.
In transmitting image/video data over Video Sensor Networks (VSNs), energy consumption must be minimized while maintaining high image/video quality. Although image/video compression is well known for its efficiency and usefulness in VSNs, the excessive costs associated with encoding computation and complexity still hinder its adoption for practical use. However, it is anticipated that high-performance handheld multi-core devices will be used as VSN processing nodes in the near future. In this paper, we propose a way to improve the energy efficiency of image and video compression with multi-core processors while maintaining the image/video quality. We improve the compression efficiency at the algorithmic level or derive the optimal parameters for the combination of a machine and compression based on the tradeoff between the energy consumption and the image/video quality. Based on experimental results, we confirm that the proposed approach can improve the energy efficiency of the straightforward approach by a factor of 2~5 without compromising image/video quality.
在通过视频传感器网络(VSN)传输图像/视频数据时,必须在保持高质量图像/视频的同时最小化能量消耗。虽然图像/视频压缩因其在 VSN 中的效率和实用性而广为人知,但与编码计算和复杂性相关的过高成本仍然阻碍了其实际应用。然而,预计高性能手持多核设备将在不久的将来用作 VSN 处理节点。在本文中,我们提出了一种在保持图像/视频质量的同时,利用多核处理器提高图像和视频压缩能效的方法。我们通过在算法级别提高压缩效率,或根据能量消耗和图像/视频质量之间的权衡为机器和压缩的组合推导出最佳参数,从而提高压缩效率。基于实验结果,我们确认所提出的方法可以在不影响图像/视频质量的情况下将直接方法的能效提高 2.5 倍。