Name
Abstract | ||
|---|---|---|
Many classical encoding algorithms of vector quantization (VQ) of image compression that can obtain global optimal solution have computational complexity O(N). A pure quantum VQ encoding algorithm with probability of success near 100% has been proposed, that performs operations 45v N times approximately. In this paper, a hybrid quantum VQ encoding algorithm between the classical method and the quantum algorithm is presented. The number of its operations is less than v N for most images, and it is more efficient than the pure quantum algorithm. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1088/1009-1963/15/12/044 | CHINESE PHYSICS |
Keywords | Field | DocType |
vector quantization,Grover's algorithm,image compression,quantum algorithm | Quantum phase estimation algorithm,Linde–Buzo–Gray algorithm,Quantum mechanics,Learning vector quantization,Algorithm,Quantum algorithm for linear systems of equations,Quantum Fourier transform,Quantum algorithm,Vector quantization,Quantization (image processing),Physics | Journal |
Volume | Issue | ISSN |
15 | 12.0 | 1009-1963 |
Citations | PageRank | References |
5 | 0.60 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao-yang Pang | 1 | 34 | 7.10 |
| Zheng-Wei Zhou | 2 | 6 | 1.08 |
| Guangcan Guo | 3 | 22 | 9.33 |
| 庞朝阳 | 4 | 5 | 0.60 |
| 周正威 | 5 | 5 | 0.60 |
| 郭光灿 | 6 | 5 | 0.60 |