An Improved Tree-Structured Codebook Search Algorithm for Grayscale Image Compression

Authors:
Yu-Chen Hu;Chin-Chen Chang
Affiliations:
Department of Computer Science and Information Engineering Providence University Shalu 433, Taichung, Taiwan, R.O.C. E-mail: ychu@pu.edu.tw;Department of Information Engineering and Computer Science Feng Chia University Taichung 407, Taiwan, R.O.C. E-mail: ccc@cs.ccu.edu.tw
Venue:
Fundamenta Informaticae
Year:
2006

Citing 10
Cited 1

Vector quantization and signal compression

Vector quantization and signal compression
An improved search algorithm for vector quantization using mean pyramid structure

Pattern Recognition Letters
Tree Structured Vector Quantization with Dynamic Path Search

ICPP '99 Proceedings of the 1999 International Workshops on Parallel Processing
Fast K-dimensional tree algorithms for nearest neighborsearch with application to vector quantization encoding

IEEE Transactions on Signal Processing
On the structure of vector quantizers

IEEE Transactions on Information Theory
A fast LBG codebook training algorithm for vector quantization

IEEE Transactions on Consumer Electronics
Fast search algorithms for vector quantization of images using multiple triangle inequalities and wavelet transform

IEEE Transactions on Image Processing
A complexity reduction technique for image vector quantization

IEEE Transactions on Image Processing
Diagonal axes method (DAM): a fast search algorithm for vector quantization

IEEE Transactions on Circuits and Systems for Video Technology
Fast VQ encoding by an efficient kick-out condition

IEEE Transactions on Circuits and Systems for Video Technology

Hypergraphs for Generic Lossless Image Compression

Fundamenta Informaticae

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, an improved tree-structured codebook search algorithm is proposed. It is called the two-level codebook search algorithm (TLCS). The goal of this method is to reduce the computation cost of the multi-path-searching algorithm for TSVQ. It speeds up the codebook search by searching only a two-level codebook tree instead of the whole TSVQ codebook tree. According to the experimental results, a significant time reduction can be achieved with this method, compared to the multi-path-searching algorithm. In other words, our TLCS outperforms the multi-path-searching algorithm.