Initial codebook method of vector quantisation in Hadamard domain

被引:7
|
作者
Chen, S. X. [1 ]
Li, F. W. [1 ]
机构
[1] Chongqing Univ Posts & Telecommun CQUPT, Commun & Informat Engn Coll, Chongqing 400065, Peoples R China
基金
中国国家自然科学基金;
关键词
IMAGE COMPRESSION; ALGORITHM; SEARCH;
D O I
10.1049/el.2010.3573
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
To deal with the problem that the initialisation method based on random selection may provide a suboptimal codebook of vector quantisation (VQ); an improved method is proposed. In the proposed method, Hadamard transform is performed on training vectors, and then the transformed vectors are sorted according to their first elements. The ordered transformed vectors are partitioned into groups. The initial codebook is composed of the mid vector of each ordered group. This method has a better performance and can be used as the initialisation method of VQ to improve and speed up codebook design.
引用
收藏
页码:630 / U47
页数:2
相关论文
共 50 条
  • [41] CODEBOOK GENERATION FOR VECTOR QUANTIZATION
    CHEN, CQ
    KOH, SN
    SIVAPRAKASAPILLAI, P
    ELECTRONICS LETTERS, 1995, 31 (07) : 522 - 523
  • [42] Supervised Online Hashing via Hadamard Codebook Learning
    Lin, Mingbao
    Ji, Rongrong
    Liu, Hong
    Wu, Yongjian
    PROCEEDINGS OF THE 2018 ACM MULTIMEDIA CONFERENCE (MM'18), 2018, : 1635 - 1643
  • [43] A Method of Adaptive ISF Split Vector Quantization Using Normalized Codebook
    Piao, Zhigang
    Lim, Jongha
    Hong, Gibong
    Lee, Insung
    JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, 2011, 30 (05): : 265 - 272
  • [44] A Codebook of Feature Vector for Underwater
    Binesh, T.
    Supriya, M. H.
    Pillai, P. R. Saseendran
    OCEANS 2009, VOLS 1-3, 2009, : 1966 - 1971
  • [45] New methodology for adaptive vector quantisation
    Scargall, LD
    Dlay, SS
    IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING, 2000, 147 (06): : 581 - 586
  • [46] Maximal Margin Learning Vector Quantisation
    Trung Le
    Dat Tran
    Van Nguyen
    Ma, Wanli
    2013 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2013,
  • [47] Fast clustering algorithm for vector quantisation
    Baek, S
    Jeon, B
    Lee, D
    Sung, KM
    ELECTRONICS LETTERS, 1998, 34 (02) : 151 - 152
  • [48] Plastic algorithm for adaptive vector quantisation
    S. Ridella
    S. Rovetta
    R. Zunino
    Neural Computing & Applications, 1998, 7 : 37 - 51
  • [49] Results on successive approximation vector quantisation
    Craizer, M
    da Silva, EAB
    Ramos, EG
    ELECTRONICS LETTERS, 1998, 34 (01) : 59 - 60
  • [50] MDL principle for robust vector quantisation
    Bischof, H
    Leonardis, A
    Selb, A
    PATTERN ANALYSIS AND APPLICATIONS, 1999, 2 (01) : 59 - 72