A NEW FUZZY K-NEAREST NEIGHBOR CODEBOOK DESIGN ALGORITHM OF VECTOR QUANTIZATION
一种新的模糊K邻域矢量量化码本设计算法

This paper presents a new fuzzy K-nearest neighbor codebook design algorithm of vector quantization, the algorithm can eliminate the effect of initial codebook selection on the quality of clustering, is not trapped in local minimum, has a good convergence rate, and can get the codebook with good performance. Simulation results show both the convergence rate and PSNR of our method are significantly improved than that of fuzzy vector quantization algorithm presented by N.B. Karayannis, et al in 1995.