This paper presents a new strategy of particle-pair (PP) for vector quantization (VQ) in image coding.In this strategy

two particles are combined into a particle-pair based on conventional particle swarm optimization (PSO) algorithm.At each iteration

the particle-pair performs basic operations of PSO (velocity updating and position updating) and conventional LBG algorithm in sequence.The codevectors flying over the boundary are replaced with the training vectors

which have large distortions.This strategy prevents the particle from being trapped in a local optimum

memorizes and estimates the best direction the particle moves toward to find the optimum codebook design.The codevectors are scattered reasonably both in high density distribution regions and low density areas of the training vector space.Experimental results have demonstrated that the performance of this new algorithm is much better than that of FKM

FRLVQ

FRLVQ-FVQ consistently with shorter computational time and higher convergence rate

and the dependence of the final optimum codebook on the selection of the initial codebook is reduced effectively.