  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.
