Abstract
This letter presents a novel variable-rate vector quantizer (VQ) design algorithm, which is a hybrid approach combining a genetic algorithm with the entropy-constrained VQ (ECVQ) algorithm. The proposed technique outperforms the ECVQ algorithm in the sense that it reaches to a nearby global optimum rather than a local one. Simulation results show that, when applied to the image coding, the technique achieves higher PSNR and image quality than those of ECVQ algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 616-620 |
| Number of pages | 5 |
| Journal | IEICE Transactions on Information and Systems |
| Volume | E81-D |
| Issue number | 6 |
| Publication status | Published - 1998 |
| Externally published | Yes |
Keywords
- Genetic algorithm
- Global optimization
- Vector quantization
ASJC Scopus subject areas
- Software
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence