In the encoding process of vector quantization (VQ)

a great deal of distance computations between vectors are needed

which is computationally expensive and prevents its practical applications. In order to speed up the VQ encoding process

lots of fast codeword search algorithms based on 1-D characteristics have been proposed for reducing the codeword search space. This paper aims at improving the method using inequality proposed by Mu et al by using more effective method based on 1-D characteristics and adaptive subvector povrtitions. The experimental results show that our proposed scheme can reduce the extra memory requirment from (-1)/2 to 13

meanwhile reducing the codeword search space by 33.88%50.94% and reducing the encoding time by 10.82%27.16%.