Single-Dimension Perturbation Glowworm Swarm Optimization Algorithm for Block Motion Estimation

Author:

Liu Xiangpin1,Xuan Shibin12,Liu Feng1

Affiliation:

1. College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, China

2. Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis, Nanning 530006, China

Abstract

In view of the fact that the classical fast motion estimation methods are easy to fall into local optimum and suffer the high computational cost, the convergence of the motion estimation method based on the swarm intelligence algorithm is very slow. A new block motion estimation method based on single-dimension perturbation glowworm swarm optimization algorithm is proposed. Single-dimension perturbation is a local search strategy which can improve the ability of local optimization. The proposed method not only has overcome the defect of falling into local optimum easily by taking use of both the global search ability of glowworm swarm optimization algorithm and the local optimization ability of single-dimension perturbation but also has reduced the computation complexity by using motion vector predictor and terminating strategies in view of the characteristic of video images. The experimental results show that the performance of the proposed method is better than that of other motion estimation methods for most video sequences, specifically for those video sequences with violent motion, and the searching precision has been improved obviously. Although the computational complexity of the proposed method is slightly higher than that of the classical methods, it is still far lower than that of full search method.

Funder

National Science Foundation Council of Guangxi

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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