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Publications de Ian Jermyn
Résultat de la recherche dans la liste des publications :
46 Articles de conférence |
29 - Shape Moments for Region-Based Active Contours.
P. Horvath et A. Bhattacharya et I. H. Jermyn et J. Zerubia et Z. Kato. Dans Proc. Hungarian-Austrian Conference on Image Processing and Pattern Recognition, Szeged, Hungary, mai 2005.
@INPROCEEDINGS{horvath_hacippr05,
|
| author |
= |
{Horvath, P. and Bhattacharya, A. and Jermyn, I. H. and Zerubia, J. and Kato, Z.}, |
| title |
= |
{Shape Moments for Region-Based Active Contours}, |
| year |
= |
{2005}, |
| month |
= |
{mai}, |
| booktitle |
= |
{Proc. Hungarian-Austrian Conference on Image Processing and Pattern Recognition}, |
| address |
= |
{Szeged, Hungary}, |
| url |
= |
{http://vision.vein.hu/HACIPPR/}, |
| keyword |
= |
{} |
| } |
|
30 - Multimodal statistics of adaptive wavelet packet coefficients: experimental evidence and theory.
R. Cossu et I. H. Jermyn et J. Zerubia. Dans Proc. Physics in Signal and Image Processing, Toulouse, France, janvier 2005.
Mots-clés : Bimodale, Statistics, Paquet d'ondelettes, Adaptatif, Texture.
@INPROCEEDINGS{cossu_psip05,
|
| author |
= |
{Cossu, R. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Multimodal statistics of adaptive wavelet packet coefficients: experimental evidence and theory}, |
| year |
= |
{2005}, |
| month |
= |
{janvier}, |
| booktitle |
= |
{Proc. Physics in Signal and Image Processing}, |
| address |
= |
{Toulouse, France}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Cossu05psip.pdf}, |
| keyword |
= |
{Bimodale, Statistics, Paquet d'ondelettes, Adaptatif, Texture} |
| } |
Abstract :
In recent work, it was noted that although the subband histograms
for standard wavelet coefcients take on a generalized
Gaussian form, this is no longer true for wavelet packet
bases adapted to a given texture. Instead, three types of subband
statistics are observed: Gaussian, generalized Gaussian,
and interestingly, in some subbands, bi- or multi-modal histograms.
Motivated by this observation, we provide additional
experimental conrmation of the existence of multimodal
subbands, and provide a theoretical explanation for
their occurrence. The results reveal the connection of such
subbands with the characteristic structure in a texture, and
thus confirm the importance of such subbands for image modelling
and applications. |
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31 - Texture discrimination using multimodal wavelet packet subbands.
R. Cossu et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Singapore, octobre 2004.
Mots-clés : Bimodale, Adaptatif, probabilistic, Paquet d'ondelettes, Texture.
@INPROCEEDINGS{cossu_icip04,
|
| author |
= |
{Cossu, R. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture discrimination using multimodal wavelet packet subbands}, |
| year |
= |
{2004}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Singapore}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Cossu04icip.pdf}, |
| keyword |
= |
{Bimodale, Adaptatif, probabilistic, Paquet d'ondelettes, Texture} |
| } |
Abstract :
The subband histograms of wavelet packet bases adapted to individual
texture classes often fail to display the leptokurtotic behaviour
shown by the standard wavelet coefcients of `natural'
images. While many subband histograms remain leptokurtotic
in adaptive bases, some subbands are Gaussian. Most interestingly,
however, some subbands show multimodal behaviour, with
no mode at zero. In this paper, we provide evidence for the existence
of these multimodal subbands and show that they correspond
to narrow frequency bands running throughout images of the texture.
They are thus closely linked to the texture's structure. As
such, they seem likely to possess superior descriptive and discriminative
power as compared to unimodal subbands. We demonstrate
this using both Brodatz and remote sensing images. |
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32 - Gap closure in (road) networks using higher-order active contours.
M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Singapore, octobre 2004.
Mots-clés : Contour actif, Gap closure, Ordre superieur, Forme, Reseaux routiers.
@INPROCEEDINGS{Rochery04,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Gap closure in (road) networks using higher-order active contours}, |
| year |
= |
{2004}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Singapore}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_icip04.pdf}, |
| keyword |
= |
{Contour actif, Gap closure, Ordre superieur, Forme, Reseaux routiers} |
| } |
Abstract :
We present a new model for the extraction of networks from images in the presence of occlusions. Such occlusions cause gaps in the extracted network that need to be closed. Using higher-order active contours, which allow the incorporation of sophisticated geometric information, we introduce a new, non-local, `gap closure' force that causes pairs of network extremities that are close together to extend towards one another and join, thus closing the gap
between them. We demonstrate the benefits of the model using the problem of road network extraction, presenting results on aerial images. |
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33 - Texture analysis using adaptative biorthogonal wavelet packets.
G.C.K. Abhayaratne et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Singapore, octobre 2004.
Mots-clés : Adaptatif, Paquet d'ondelettes, Biorthogonal, Texture, Statistics.
@INPROCEEDINGS{Abhayratne_icip04,
|
| author |
= |
{Abhayaratne, G.C.K. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture analysis using adaptative biorthogonal wavelet packets}, |
| year |
= |
{2004}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Singapore}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Abhayaratne04icip.pdf}, |
| keyword |
= |
{Adaptatif, Paquet d'ondelettes, Biorthogonal, Texture, Statistics} |
| } |
Abstract :
We discuss the use of adaptive biorthogonal wavelet packet bases
in a probabilistic approach to texture analysis, thus combining the
advantages of biorthogonal wavelets (FIR, linear phase) with those
of a coherent texture model. The computation of the probability
uses both the primal and dual coefcients of the adapted biorthogonal
wavelet packet basis. The computation of the biorthogonal
wavelet packet coefcients is done using a lifting scheme, which
is very efficient. The model is applied to the classification of mosaics
of Brodatz textures, the results showing improvement over
the performance of the corresponding orthogonal wavelets. |
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34 - Texture analysis using probabilistic models of the unimodal and multimodal statistics of adaptative wavelet packet coefficients.
R. Cossu et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Montreal, Canada, mai 2004.
Mots-clés : Bimodale, Adaptatif, Paquet d'ondelettes, Texture, Mixture de gaussiennes, Statistics.
@INPROCEEDINGS{cossu04a,
|
| author |
= |
{Cossu, R. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture analysis using probabilistic models of the unimodal and multimodal statistics of adaptative wavelet packet coefficients}, |
| year |
= |
{2004}, |
| month |
= |
{mai}, |
| booktitle |
= |
{Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
| address |
= |
{Montreal, Canada}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Cossu04icassp.pdf}, |
| keyword |
= |
{Bimodale, Adaptatif, Paquet d'ondelettes, Texture, Mixture de gaussiennes, Statistics} |
| } |
Abstract :
Although subband histograms of the wavelet coefficients of
natural images possess a characteristic leptokurtotic form,
this is no longer true for wavelet packet bases adapted to
a given texture. Instead, three types of subband statistics
are observed: Gaussian, leptokurtotic, and interestingly, in
some subbands, multimodal histograms. These subbands
are closely linked to the structure of the texture, and guarantee
that the most probable image is not flat. Motivated by
these observations, we propose a probabilistic model that
takes them into account. Adaptive wavelet packet subbands
are modelled as Gaussian, generalized Gaussian, or a constrained
Gaussian mixture. We use a Bayesian methodology,
finding MAP estimates for the adaptive basis, for subband
model selection, and for subband model parameters.
Results confirm the effectiveness of the proposed approach,
and highlight the importance of multimodal subbands for
texture discrimination and modelling. |
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35 - Wavelet-Based Superresolution in Astronomy.
R. Willett et I. H. Jermyn et R. Nowak et J. Zerubia. Dans Proc. Astronomical Data Analysis Software and Systems, Strasbourg, France, octobre 2003.
Mots-clés : Superresolution, Ondelettes, Astronomy.
@INPROCEEDINGS{Willett03,
|
| author |
= |
{Willett, R. and Jermyn, I. H. and Nowak, R. and Zerubia, J.}, |
| title |
= |
{Wavelet-Based Superresolution in Astronomy}, |
| year |
= |
{2003}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. Astronomical Data Analysis Software and Systems}, |
| address |
= |
{Strasbourg, France}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Willett03adass.pdf}, |
| keyword |
= |
{Superresolution, Ondelettes, Astronomy} |
| } |
Abstract :
High-resolution astronomical images can be reconstructed
from several blurred and noisy low-resolution images using a computational
process known as superresolution reconstruction. Superresolution
reconstruction is closely related to image deconvolution, except that the
low-resolution images are not registered and their relative translations
and rotations must be estimated in the process. The novelty of our approach
to the superresolution problem is the use of wavelets and related
multiresolution methods within an expectation-maximization reconstruction
process to improve the accuracy and visual quality of the reconstructed
image. Simulations demonstrate the effectiveness of the proposed
method, including its ability to distinguish between tightly grouped stars
with a small set of observations. |
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36 - Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery.
M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision, at ICCV, Nice, France, octobre 2003.
Mots-clés : Ordre superieur, Contour actif, Forme, Reseaux routiers, Segmentation, A priori.
@INPROCEEDINGS{Rochery03a,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher Order Active Contours and their Application to the Detection of Line Networks in Satellite Imagery}, |
| year |
= |
{2003}, |
| month |
= |
{octobre}, |
| booktitle |
= |
{Proc. IEEE Workshop Variational, Geometric and Level Set Methods in Computer Vision}, |
| address |
= |
{at ICCV, Nice, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_vlsm03.pdf}, |
| keyword |
= |
{Ordre superieur, Contour actif, Forme, Reseaux routiers, Segmentation, A priori} |
| } |
Abstract :
We present a novel method for the incorporation of shape information
into active contour models, and apply it to the extraction
of line networks (e.g. road, water) from satellite imagery.
The method is based on a new class of contour energies.
These energies are quadratic on the space of one-chains
in the image, as opposed to classical energies, which are linear.
They can be expressed as double integrals on the contour,
and thus incorporate non-trivial interactions between
different contour points. The new energies describe families
of contours that share complex geometric properties, without
making reference to any particular shape. Networks fall
into such a family, and to model them we make a particular
choice of quadratic energy whose minima are reticulated.
To optimize the energies, we use a level set approach. The
forces derived from the new energies are non-local however,
thus necessitating an extension of standard level set methods.
Promising experimental results are obtained using real
images. |
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37 - Texture Analysis: An Adaptive Probabilistic Approach.
K. Brady et I. H. Jermyn et J. Zerubia. Dans Proc. IEEE International Conference on Image Processing (ICIP), Barcelona, Spain, septembre 2003.
Mots-clés : Adaptatif, Paquet d'ondelettes, Statistics, Texture.
@INPROCEEDINGS{Brady03,
|
| author |
= |
{Brady, K. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Texture Analysis: An Adaptive Probabilistic Approach}, |
| year |
= |
{2003}, |
| month |
= |
{septembre}, |
| booktitle |
= |
{Proc. IEEE International Conference on Image Processing (ICIP)}, |
| address |
= |
{Barcelona, Spain}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/Brady03icip.pdf}, |
| keyword |
= |
{Adaptatif, Paquet d'ondelettes, Statistics, Texture} |
| } |
Abstract :
Two main issues arise when working in the area of texture
segmentation: the need to describe the texture accurately by
capturing its underlying structure, and the need to perform
analyses on the boundaries of textures. Herein, we tackle
these problems within a consistent probabilistic framework.
Starting from a probability distribution on the space of infinite
images, we generate a distribution on arbitrary finite
regions by marginalization. For a Gaussian distribution, the
computational requirement of diagonalization and the modelling
requirement of adaptivity together lead naturally to
adaptive wavelet packet models that capture the ‘significant
amplitude features’ in the Fourier domain. Undecimated
versions of the wavelet packet transform are used to diagonalize
the Gaussian distribution efficiently, albeit approximately.
We describe the implementation and application of
this approach and present results obtained on several Brodatz
texture mosaics. |
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38 - Étude D'une Nouvelle Classe de Contours Actifs Pour la Détection de Routes Dans Des Images de Télédétection.
M. Rochery et I. H. Jermyn et J. Zerubia. Dans Proc. GRETSI Symposium on Signal and Image Processing, Paris, France, septembre 2003.
@INPROCEEDINGS{Rochery03,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Étude D'une Nouvelle Classe de Contours Actifs Pour la Détection de Routes Dans Des Images de Télédétection}, |
| year |
= |
{2003}, |
| month |
= |
{septembre}, |
| booktitle |
= |
{Proc. GRETSI Symposium on Signal and Image Processing}, |
| address |
= |
{Paris, France}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/rochery_gretsi03.pdf}, |
| keyword |
= |
{} |
| } |
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Rapport d'activité 2011
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