Efficient Block-based Motion Estimation

Architecture using Particle Swarm Optimization

Vani Rajamanickam1 and Sangeetha Marikkannan2

1Meenakshi College of Engineering, Anna University, India

2Karpaga Vinayaga College of Engineering and Technology, Anna University, India

Abstract: High speed video transmission is the key to achieve high quality live or through offline streaming. Block matching motion estimation is adopted in video coding standards to improve the performance in terms of speed and at the same time, the power consumption should be minimal. The paper proposes an efficient Block-based Motion Estimation architecture, in which the Motion Vectors (MV) are obtained by searching for the best match in the previous frame. A resizable smart snake order is utilized for scanning the frames of different block sizes which improves the data reuse efficiency. The architecture is based on applying the global search ability of Particle Swarm Optimization (PSO) that reduces the number of logic elements. The parallel execution involved in the processing of sub-regions in the search window enables the architecture to achieve high speed. The proposed work coded in Verilog Hardware Description Language, and implemented with Altera Cyclone II FPGA, operates at a maximum frequency of 265.01MHz. It is observed that the total thermal power dissipation is 74.27 mw, making it suitably efficient for low power implementation of Motion Estimation.

Keywords: Resizable smart snake scan, swarm optimization, motion estimation, block matching.