一種新的模糊K鄰域矢量量化碼本設(shè)計算法
A NEW FUZZY K-NEAREST NEIGHBOR CODEBOOK DESIGN ALGORITHM OF VECTOR QUANTIZATION
-
摘要: 本文提出了一種新的模糊K鄰域矢量量化碼本設(shè)計算法(FKNNVQ)。該算法具有對 初始碼本依賴性小，不會局部最小，收斂速度快，碼本性能好等優(yōu)點。實驗結(jié)果表明，F(xiàn)KNNVQ算法與Karayannis等1995年提出的模糊矢量量化算法(FVQ)相比，設(shè)計的圖象碼本峰值信噪比和收斂速度都有明顯改善。
-
關(guān)鍵詞:
- 圖象編碼; 模糊K鄰域算法; 模糊矢量量化
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. -
張基宏 基于矢量量化自適應(yīng)圖象編碼的研究:[博士學(xué)位論文].南京:東南大學(xué)無線電系,1992.[2]Gray R M. Vector quantization. IEEE ASSP Magazine, 1984, 1(1): 4-29.[3]Pal N R, et al. Generalized clustering networks and Kohonens self-organizing scheme. IEEE Trans. on NN, 1993, NN-4(4): 549-557.[4]Zeger K, et al. Globally optimal vector quantizer design by stochastic relaxation. IEEE Trans.on IT, 1992, IT-28(2): 256-261.[5]Bezdek J C, et al. FCM: The fuzzy C-mean clustering algorithm[J].Comput. Geosciences.1984, 10(2-3):191-203[6]Karayannis N B, et al. Fuzzy vector quantization algorithm and their application in image com-pression. IEEE Trans. on IP, 1995, IP-4(9): 1193-1201.[7]張基宏, 王暉, Ueno Y. 基于模糊矢量量化圖象編碼的研究. 中國圖象圖形學(xué)報,1998, 3(4): 295-298.[8]張基宏, 何振亞. 一種指數(shù)型模糊學(xué)習(xí)矢量量化圖象編碼算法. 通信學(xué)報, 1998, 19(10): 1-6.[9]Keller J M, et al. A fuzzy K-nearest neighbor algorithm. IEEE Trans. on SMC, 1985, SMC-15(5):[10]8-263.[11]Bezdek J C. A convergence theorem for the fuzzy ISODATA clustering algorithms. IEEE Trans. on PAMI, 1980, PAMI-2(1): 1-8. -
計量
- 文章訪問數(shù): 2163
- HTML全文瀏覽量: 114
- PDF下載量: 447
- 被引次數(shù): 0
下載:
