Fast tree-structured nearest neighbor encoding for vector quantization

  • Authors:
  • I. Katsavounidis;C. -C.J. Kuo;Zhen Zhang

  • Affiliations:
  • Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA;-;-

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 1996

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Abstract

This work examines the nearest neighbor encoding problem with an unstructured codebook of arbitrary size and vector dimension. We propose a new tree-structured nearest neighbor encoding method that significantly reduces the complexity of the full-search method without any performance degradation in terms of distortion. Our method consists of efficient algorithms for constructing a binary tree for the codebook and nearest neighbor encoding by using this tree. Numerical experiments are given to demonstrate the performance of the proposed method