一种改进的矢量量化码字搜索算法

AN IMPROVED CODEWORD SEARCHING ALGORITHM FOR VECTOR QUANTIZATION

该文利用图像矢量的平均值和方差,结合了最近邻域搜索算法,构造了一种新的快速矢量量化编码算法。将一个输入矢量分为两个子矢量,分别计算原始矢量、两个子矢量的和以及方差值,利用在这些数值基础上建立的一组三角不等式来排除不可能的码字。仿真结果表明新算法在所需时间和计算复杂度方面优于改进的EENNS算法,为矢量量化算法的研究提供了一种新的思路。

In this paper, an improved codeword searching algorithm is proposed on the basis of nearest-neighbor search algorithm. The new algorithm considers the sums and variances of image vectors. A vector is separated into two subvectors: the first half of the coordinates and the second half of the coordinates. Calculate the sums and variances of the vector and its two subvectors. Apply the result to a set of inequalities to eliminate the impossible codeword candidates. The simulation results show that the proposed algorithm is faster than the improved EENNS algorithm, and it also has the advantage in decreasing the computing complexity.