Greedy tree growing algorithms for designing variable rate vector quantizers
Wenjun Zeng, Yih-Fang Huang, S.C. Huang · IEEE International Conference on Acoustics Speech and Signal Processing · 1993
The performance of vector quantization for image compression can be improved by using a variable-rate code which is able to designate more bits to regions of an image that are active or difficult to code, and fewer bits to less active regions. Two schemes are presented for directly designing variable-rate tree-structured vector quantizers by growing the tree one node at a time. One involves selecting the node with the largest average distortion within one node to split. The other involves splitting the node with the largest eigenvalue of the input covariance matrix. A comparison with the scheme of E.A. Riskin and R.M. Gray (1991) shows that the proposed schemes perform better in terms of visual quality with reduced complexity.>