Low power motion estimation algorithm based on temporal correlation and its architecture

Sun-Hyoung Han, Sung-Woo Kwon, T. Lee, M. Lee
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引用次数: 7

Abstract

We propose architecture of low power motion estimation algorithm. There are two types of MB (macro block) modes in the proposed algorithm (fast MB mode and normal MB mode). In the fast MB mode, the motion vector found from the previous frame is utilized in the next frame. This mode can be adopted in the conventional fast motion estimation algorithm, and as a result, the computational power is reduced by 40%. In normal the MB mode, among the conventional fast search algorithms, we take the 4SS (four step search), and introduce an additional search method called a center-focused search in the step to increase the PSNR level. We then, implement the corresponding PE (processing element) architecture that gives the hardware performance improvement. The new motion estimation architecture is especially efficient for mobile phone and video conferencing applications in which there is not much motion.
基于时间相关的低功耗运动估计算法及其体系结构
提出了一种低功耗运动估计算法的结构。该算法有两种宏块模式(快速MB模式和正常MB模式)。在快速MB模式下,从前一帧找到的运动向量在下一帧中被利用。该模式可用于传统的快速运动估计算法,计算能力可降低40%。在常规的MB模式下,在传统的快速搜索算法中,我们采用了4SS(四步搜索),并在步骤中引入了一种额外的搜索方法,称为中心搜索,以提高PSNR水平。然后,我们实现相应的PE(处理元素)体系结构,从而提高硬件性能。新的运动估计体系结构对移动电话和视频会议应用尤其有效,在这些应用中没有太多的运动。
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