| dc.contributor.author |
Kasaei, S |
|
| dc.contributor.author |
Deriche, M |
|
| dc.contributor.author |
Boashash, B |
|
| dc.date.accessioned |
2011-10-18T19:24:51Z |
|
| dc.date.available |
2011-10-18T19:24:51Z |
|
| dc.date.issued |
1997-08 |
|
| dc.identifier.citation |
Signal Processing vol. 62 Issue 3, pages 361-366 |
en_US |
| dc.identifier.other |
doi:10.1016/S0165-1684(97)00169-2 |
|
| dc.identifier.uri |
http://hdl.handle.net/10576/10762 |
|
| dc.description |
A new quantization technique for wavelet coefficients
is designed based on an accurate
distribution model of wavelet coefficients in each
sub band aimed at achieving the best rate-distortion
function.
(Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://www.elsevier.com/locate/isbn/0080443354).
In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). |
en_US |
| dc.description.abstract |
In this paper, a novel quantization scheme for the wavelet coefficients is introduced. Using the wavelet packet transform (WPT) and lattice vector quantization (LVQ), we present here a new lattice optimization scheme based on an accurate model for the distribution of the wavelet coefficients. The model is based on the generalized gaussian distribution (GGD). A least squares algorithm on a non-linear function of the shape parameter is formulated to estimate the model parameters. The proposed algorithm adapts to non-stationarity in input images and to given bit rates. Compared to other wavelet-based algorithms, the technique proposed here results in higher reconstructed image qualities for identical bit rates. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
Elsevier |
en_US |
| dc.subject |
Wavelet packet transform |
en_US |
| dc.subject |
Lattice vector quantization |
en_US |
| dc.subject |
Distribution model |
en_US |
| dc.subject |
Fingerprints |
en_US |
| dc.subject |
time-frequency methods |
en_US |
| dc.subject |
time-scale methods |
en_US |
| dc.subject |
image quantization |
en_US |
| dc.subject |
image processing |
en_US |
| dc.subject |
image recognition |
en_US |
| dc.title |
An efficient quantization technique for wavelet coefficients of fingerprint images |
en_US |
| dc.type |
Article |
en_US |