Fast tree-structured nearest neighbor encoding for vector quantization.
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.
Katsavounidis
I
I
Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA.
Kuo
C J
CJ
Zhang
Z
Z