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Johan Aubray
Former Master Student, ENAC
 Keywords : Wavelets, Parameter Estimation, Texture
 Contact :
| Mail : | | JohandotAubrayatinriadotfr | | Phone : | | (33)4-92-38-75-95 | | Fax : | | (33)4-92-38-76-43 | | Postal adress : | | INRIA Sophia Antipolis
2004, route des Lucioles
06902 Sophia Antipolis Cedex
France |
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| Abstract :
My work is about studying texture images using wavelets. The very idea of texture is ill-defined, but it includes the underlying concept of periodicities, which leads to think of a frequential study. And the idea of using wavelets is supported by biological studies that have shown that the human brain naturally uses multiscale processing for vision.
The adaptive wavelet packet decomposition highlights a very specific distribution (in fact, a bimodal one) for the resulting coefficients in some subbands (whose frequency support is rather narrow). Therefore, my work consists in modeling these distributions and estimating their parameters. |
Last publications in Ariana Research Group :
Nonlinear models for the statistics of adaptive wavelet packet coefficients of texture.
J. Aubray and I. H. Jermyn and J. Zerubia. In Proc. European Signal Processing Conference (EUSIPCO), Florence, Italy, September 2006.
Keywords : Texture, Adaptive, Wavelet packet, Nonlinear, Bimodal, Statistics.
@INPROCEEDINGS{aubray_eusipco06,
|
| author |
= |
{Aubray, J. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Nonlinear models for the statistics of adaptive wavelet packet coefficients of texture}, |
| year |
= |
{2006}, |
| month |
= |
{September}, |
| booktitle |
= |
{Proc. European Signal Processing Conference (EUSIPCO)}, |
| address |
= |
{Florence, Italy}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2006_aubray_eusipco06.pdf}, |
| keyword |
= |
{Texture, Adaptive, Wavelet packet, Nonlinear, Bimodal, Statistics} |
| } |
Abstract :
Probabilistic adaptive wavelet packet models of
texture pro- vide new insight into texture structure
and statistics by focus- ing the analysis on
significant structure in frequency space. In very
adapted subbands, they have revealed new bimodal
statistics, corresponding to the structure inherent to
a texture, and strong dependencies between such
bimodal sub- bands, related to phase coherence in a
texture. Existing models can capture the former but
not the latter. As a first step to- wards modelling
the joint statistics, and in order to simplify earlier
approaches, we introduce a new parametric family of
models capable of modelling both bimodal and unimodal
subbands, and of being generalized to capture the
joint statistics. We show how to compute MAP estimates
for the adaptive basis and model parameters, and apply
the models to Brodatz textures to illustrate their
performance. |
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All publications in Ariana Research Group
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