An efficient and low power architecture design for motion estimation using global elimination algorithm

This paper presents a new algorithm and architecture for motion estimation. The proposed global elimination algorithm (GEA) is derived from successive elimination algorithm (SEA). The main idea is to remove the branches of SEA to make data flow more regular and suitable for hardware. Besides, the processing time per motion vector for GEA is fixed, no initial guess is required, and the skipping ratio of search positions can be fixed within frames and is even higher than 99%. The average PSNR of compensated frames is almost the same (within 0.1 dB) as that of full-search block matching algorithm (FBMA). An architecture composed of a systolic part, an adder tree, and a comparator tree is also developed for GEA. Simulation results show our design outperforms many FBMA architectures in normalized processing capability per gate and normalized power at gate level.