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A Fast Block Matching Algorithm for Video Motion Estimation Based on Particle Swarm Optimization and Motion Prejudgment

Ran Ren·Madan mohan Manokar·Yaogang Shi·Baoyu Zheng
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Abstract

In this paper, we propose a fast 2-D block-based motion estimation algorithm called Particle Swarm Optimization - Zero-motion Prejudgment(PSO-ZMP) which consists of three sequential routines: 1)Zero-motion prejudgment. The routine aims at finding static macroblocks(MB) which do not need to perform remaining search thus reduces the computational cost; 2)Predictive image coding and 3)PSO matching routine. Simulation results obtained show that the proposed PSO-ZMP algorithm achieves over 10 times of computation less than Diamond Search(DS) and 5 times less than the recent proposed Adaptive Rood Pattern Searching(ARPS). Meanwhile the PSNR performances using PSO-ZMP are very close to that using DS and ARPS in some less-motioned sequences. While in some sequences containing dense and complex motion contents, the PSNR performances of PSO-ZMP are several dB lower than that using DS and ARPS but in an acceptable degree.

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Ran Ren, Madan mohan Manokar, Yaogang Shi, Baoyu Zheng. 2006-09-24. A Fast Block Matching Algorithm for Video Motion Estimation Based on Particle Swarm Optimization and Motion Prejudgment. https://arxiv.org/abs/cs/0609131

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