Name
Title | ||
|---|---|---|
Efficient codebooks for vector quantization image compression with an adaptive tree search algorithm |
Abstract | ||
|---|---|---|
This paper discusses some algorithms to be used for the generation of an efficient and robust codebook for vector quantization (VQ). Some of the algorithms reduce the required codebook size by 4 or even 8 b to achieve the same level of performance as some of the popular techniques. This helps in greatly reducing the complexity of codebook generation and encoding. We also present a new adaptive tree search algorithm which improves the performance of any product VQ structure. Our results show an improvement of nearly 3 dB over the fixed rate search algorithm at a bit rate of 0.75 b/pixel |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1109/26.328984 | Communications, IEEE Transactions |
Keywords | Field | DocType |
image coding,search problems,vector quantisation,VQ,adaptive tree search algorithm,codebook generation,codebook size,encoding,image compression,robust codebook,vector quantization | Tree traversal,Search algorithm,Pattern recognition,Linde–Buzo–Gray algorithm,Computer science,Vector quantization,Tree structure,Artificial intelligence,Data compression,Image compression,Codebook | Journal |
Volume | Issue | ISSN |
42 | 11 | 0090-6778 |
Citations | PageRank | References |
6 | 0.61 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sitaram, V.S. | 1 | 6 | 0.61 |
| Chien-Min Huang | 2 | 6 | 0.61 |
| Israelsen, P.D. | 3 | 6 | 0.61 |