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Performance Analysis of Hexagon-Diamond Search Algorithm for Motion Estimation

To achieve a high compression ratio in coding video data, a method known as Motion Estimation (ME) is often applied to reduce the temporal redundancy between successive frames of a video sequence. One of ME techniques, known as Block Matching Algorithm (BMA), has been widely used in various video coding standards. In recent years, many of these BMAs have been developed with similar intention of reducing the computational costs while at the same time maintaining the video signal quality. In this paper, an algorithm called Hexagon-Diamond Search (HDS) is proposed for ME where the algorithm and several fast BMAs, namely Three Step Search (TSS), New Three Step Search (NTSS), Four Step Search (4SS) as well as Diamond Search (DS), are first selected to be implemented onto various type of standard test video sequence using MATLAB before their performances are compared and analyzed in terms of peak signal-to-noise ratio (PSNR), number of search points needed as well as their computational complexity. Simulation results demonstrate that HDS algorithm has speed up other algorithm's computational work up to 56% on average while at the same time maintains close performance in terms of average PSNR to others.