一种新的模糊K邻域矢量量化码本设计算法
A NEW FUZZY K-NEAREST NEIGHBOR CODEBOOK DESIGN ALGORITHM OF VECTOR QUANTIZATION
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摘要: 本文提出了一种新的模糊K邻域矢量量化码本设计算法(FKNNVQ)。该算法具有对 初始码本依赖性小，不会局部最小，收敛速度快，码本性能好等优点。实验结果表明，FKNNVQ算法与Karayannis等1995年提出的模糊矢量量化算法(FVQ)相比，设计的图象码本峰值信噪比和收敛速度都有明显改善。Abstract: 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.
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