A new motion estimation method and its hardware implementation are presented in this paper. In this method, all the frames are firstly gray coded. After that, the two most significant bits from the current frame and reference frame are used to compute the motion vector. Besides, a diamond search algorithm is used in place of the full-search algorithm. The motion estimation scheme proposed in the present paper is also verified to work on various standard video sequences. The experimental results thus obtained show that the proposed algorithm has an excellent balance of performance and computational complexity. External memory access has been reduced drastically by incorporating search pixel reuse. The resulting architecture is simple in terms of the hardware cost and power requirements while being faster than a recently reported similar architecture. The proposed architecture requires less hardware than comparable systems without compromising performance. The proposed architecture is therefore suited to be used in portable consumer electronic devices with real-time video applications in which power consumption is a concern.

本文提出了一种新的运动估计方法及其硬件实现。在该方法中，首先对所有帧进行格雷编码。之后，使用当前帧和参考帧的两个最高有效位来计算运动矢量。此外，使用菱形搜索算法代替全搜索算法。本文提出的运动估计方案也被验证可以在各种标准视频序列上工作。由此获得的实验结果表明，所提出的算法在性能和计算复杂度之间具有良好的平衡。通过合并搜索像素重用，外部存储器访问已大大减少。由此产生的架构在硬件成本和功耗要求方面很简单，同时比最近报道的类似架构更快。所提出的架构比同类系统需要更少的硬件，而不会影响性能。因此，所提出的架构适合用于具有实时视频应用的便携式消费电子设备，其中功耗是一个问题。