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The Publications
Result of the query in the list of publications :
101 Articles |
31 - Efficient schemes for total variation minimization under constraints in image processing.
P. Weiss and L. Blanc-Féraud and G. Aubert. SIAM journal on Scientific Computing, 31(3): pages 2047-2080, 2009.
Keywords : Total variation, l1 norm, nesterov scheme, Rudin Osher Fatemi, fast optimization, real time.
Copyright : Copyright Siam Society for Industrial and Applied
@ARTICLE{SIAM_JSC_PWEISS,
|
| author |
= |
{Weiss, P. and Blanc-Féraud, L. and Aubert, G.}, |
| title |
= |
{Efficient schemes for total variation minimization under constraints in image processing}, |
| year |
= |
{2009}, |
| journal |
= |
{SIAM journal on Scientific Computing}, |
| volume |
= |
{31}, |
| number |
= |
{3}, |
| pages |
= |
{2047-2080}, |
| url |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/SIAM_JSC09_PWEISS.pdf}, |
| pdf |
= |
{http://www.math.univ-toulouse.fr/~weiss/Publis/SIAM_JSC09_PWEISS.pdf}, |
| keyword |
= |
{Total variation, l1 norm, nesterov scheme, Rudin Osher Fatemi, fast optimization, real time} |
| } |
|
32 - Incorporating generic and specific prior knowledge in a multi-scale phase field model for road extraction from VHR images.
T. Peng and I. H. Jermyn and V. Prinet and J. Zerubia. IEEE Trans. Geoscience and Remote Sensing, 1(2): pages 139--146, June 2008.
Keywords : Dense urban areas, Geographic Information System (GIS), Multiscale, Road network, Variational methods, Very high resolution.
Copyright : ©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
@ARTICLE{Peng08b,
|
| author |
= |
{Peng, T. and Jermyn, I. H. and Prinet, V. and Zerubia, J.}, |
| title |
= |
{Incorporating generic and specific prior knowledge in a multi-scale phase field model for road extraction from VHR images}, |
| year |
= |
{2008}, |
| month |
= |
{June}, |
| journal |
= |
{IEEE Trans. Geoscience and Remote Sensing}, |
| volume |
= |
{1}, |
| number |
= |
{2}, |
| pages |
= |
{139--146}, |
| url |
= |
{http://dx.doi.org/10.1109/JSTARS.2008.922318}, |
| pdf |
= |
{http://www-sop.inria.fr/members/Ian.Jermyn/publications/PengetalTGRS08.pdf}, |
| keyword |
= |
{Dense urban areas, Geographic Information System (GIS), Multiscale, Road network, Variational methods, Very high resolution} |
| } |
Abstract :
This paper addresses the problem of updating digital road maps in dense urban areas by extracting the main road network from very high resolution (VHR) satellite images. Building on the work of Rochery et al. (2005), we represent the road region as a 'phase field'. In order to overcome the difficulties due to the complexity of the information contained in VHR images, we propose a multi-scale statistical data model. It enables the integration of segmentation results from coarse resolution, which furnishes a simplified representation of the data, and fine resolution, which provides accurate details. Moreover, an outdated GIS digital map is introduced into the model, providing specific prior knowledge of the road network. This new term balances the effect of the generic prior knowledge describing the geometric shape of road networks (i.e. elongated and of low-curvature) carried by a 'phase field higher-order active contour' term. Promising results on QuickBird panchromatic images and comparisons with several other methods demonstrate the effectiveness of our approach. |
|
33 - Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling.
F. Lafarge and X. Descombes and J. Zerubia and M. Pierrot-Deseilligny. Journal of Photogrammetry and Remote Sensing, 63(3): pages 365-381, May 2008.
Keywords : Building extraction, 3D reconstruction, Digital Elevation Model, Stochastic geometry.
@ARTICLE{lafarge_jprs08,
|
| author |
= |
{Lafarge, F. and Descombes, X. and Zerubia, J. and Pierrot-Deseilligny, M.}, |
| title |
= |
{Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling}, |
| year |
= |
{2008}, |
| month |
= |
{May}, |
| journal |
= |
{Journal of Photogrammetry and Remote Sensing}, |
| volume |
= |
{63}, |
| number |
= |
{3}, |
| pages |
= |
{365-381}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2008_lafarge_jprs08.pdf}, |
| keyword |
= |
{Building extraction, 3D reconstruction, Digital Elevation Model, Stochastic geometry} |
| } |
Abstract :
In this paper, we present an automatic building extraction method from Digital Elevation Models based on an object approach.
First, a rough approximation of the building footprints is realized by a method based on marked point processes: the building
footprints are modeled by rectangle layouts. Then, these rectangular footprints are regularized by improving the connection
between the neighboring rectangles and detecting the roof height discontinuities. The obtained building footprints are structured
footprints: each element represents a specific part of an urban structure. Results are finally applied to a 3D-city modeling process. |
|
34 - Gap Filling of 3-D Microvascular Networs by Tensor Voting.
L. Risser and F. Plouraboue and X. Descombes. IEEE Trans. Medical Imaging, 27(5): pages 674-687, May 2008.
Copyright :
@ARTICLE{xavTMI3,
|
| author |
= |
{Risser, L. and Plouraboue, F. and Descombes, X.}, |
| title |
= |
{Gap Filling of 3-D Microvascular Networs by Tensor Voting}, |
| year |
= |
{2008}, |
| month |
= |
{May}, |
| journal |
= |
{IEEE Trans. Medical Imaging}, |
| volume |
= |
{27}, |
| number |
= |
{5}, |
| pages |
= |
{674-687}, |
| pdf |
= |
{http://ieeexplore.ieee.org/iel5/42/4497376/04389807.pdf?isnumber=4497376&prod=JNL&arnumber=4389807&arSt=674&ared=687&arAuthor=Risser%2C+L.%3B+Plouraboue%2C+F.%3B+Descombes%2C+X.}, |
| keyword |
= |
{} |
| } |
|
35 - A marked point process of rectangles and segments for automatic analysis of Digital Elevation Models..
M. Ortner and X. Descombes and J. Zerubia. IEEE Trans. Pattern Analysis and Machine Intelligence, 2008.
Keywords : Image procressing, Poisson point process, Stochastic geometry, Dense urban area, Digital Elevation Model, land register.
Copyright :
@ARTICLE{ortner08,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{A marked point process of rectangles and segments for automatic analysis of Digital Elevation Models.}, |
| year |
= |
{2008}, |
| journal |
= |
{IEEE Trans. Pattern Analysis and Machine Intelligence}, |
| pdf |
= |
{http://hal.inria.fr/docs/00/27/88/82/PDF/ortner08.pdf}, |
| keyword |
= |
{Image procressing, Poisson point process, Stochastic geometry, Dense urban area, Digital Elevation Model, land register} |
| } |
|
36 - The Gibbs fields approach and related dynamics in image processing.
X. Descombes and E. Zhizhina. Condensed Matter Physics, 11(2(54)): pages 293-312, 2008.
Copyright : Institute for Condensed Matter
@ARTICLE{LNA08,
|
| author |
= |
{Descombes, X. and Zhizhina, E.}, |
| title |
= |
{The Gibbs fields approach and related dynamics in image processing}, |
| year |
= |
{2008}, |
| journal |
= |
{Condensed Matter Physics}, |
| volume |
= |
{11}, |
| number |
= |
{2(54)}, |
| pages |
= |
{293-312}, |
| keyword |
= |
{} |
| } |
|
37 - Higher-Order Active Contour Energies for Gap Closure.
M. Rochery and I. H. Jermyn and J. Zerubia. Journal of Mathematical Imaging and Vision, 29(1): pages 1-20, September 2007.
Keywords : Gap closure, Higher-order, Active contour, Shape, Prior, Road network.
@ARTICLE{Rochery07,
|
| author |
= |
{Rochery, M. and Jermyn, I. H. and Zerubia, J.}, |
| title |
= |
{Higher-Order Active Contour Energies for Gap Closure}, |
| year |
= |
{2007}, |
| month |
= |
{September}, |
| journal |
= |
{Journal of Mathematical Imaging and Vision}, |
| volume |
= |
{29}, |
| number |
= |
{1}, |
| pages |
= |
{1-20}, |
| url |
= |
{http://dx.doi.org/10.1007/s10851-007-0021-x}, |
| pdf |
= |
{ftp://ftp-sop.inria.fr/ariana/Articles/2007_Rochery07.pdf}, |
| keyword |
= |
{Gap closure, Higher-order, Active contour, Shape, Prior, Road network} |
| } |
Abstract :
One of the main difficulties in extracting line networks from images, and in particular road networks from remote sensing images, is the existence of interruptions in the data caused, for example, by occlusions. These can lead to gaps in the extracted network that do not correspond to gaps in the real network. In this paper, we describe a higher-order active contour energy that in addition to favouring network-like regions, includes a prior term penalizing networks containing ‘nearby opposing extremities’, thereby making gaps in the extracted network less likely. The new energy term causes such extremities to attract one another during gradient descent. They thus move towards one another and join, closing the gap. To minimize the energy, we develop specific techniques to handle the high-order derivatives that appear in the gradient descent equation. We present the results of automatic extraction of networks from real remote-sensing images, showing the ability of the model to overcome interruptions. |
|
38 - Gaussian approximations of fluorescence microscope point-spread function models.
B. Zhang and J. Zerubia and J.C. Olivo-Marin. Applied Optics, 46(10): pages 1819-1829, April 2007.
Copyright : © 2007 Optical Society of America
@ARTICLE{jz_applied_photo,
|
| author |
= |
{Zhang, B. and Zerubia, J. and Olivo-Marin, J.C.}, |
| title |
= |
{Gaussian approximations of fluorescence microscope point-spread function models}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| journal |
= |
{Applied Optics}, |
| volume |
= |
{46}, |
| number |
= |
{10}, |
| pages |
= |
{1819-1829}, |
| keyword |
= |
{} |
| } |
Abstract :
We comprehensively study the least-squares Gaussian approximations of the diffraction-limited 2D-3D paraxial-nonparaxial point-spread functions (PSFs) of the wide field fluorescence microscope (WFFM), the laser scanning confocal microscope (LSCM), and the disk scanning confocal microscope (DSCM). The PSFs are expressed using the Debye integral. Under an L∞ constraint imposing peak matching, optimal and near-optimal Gaussian parameters are derived for the PSFs. With an L1 constraint imposing energy conservation, an optimal Gaussian parameter is derived for the 2D paraxial WFFM PSF. We found that (1) the 2D approximations are all very accurate; (2) no accurate Gaussian approximation exists for 3D WFFM PSFs; and (3) with typical pinhole sizes, the 3D approximations are accurate for the DSCM and nearly perfect for the LSCM. All the Gaussian parameters derived in this study are in explicit analytical form, allowing their direct use in practical applications. |
|
39 - Building Outline Extraction from Digital Elevation Models using Marked Point Processes.
M. Ortner and X. Descombes and J. Zerubia. International Journal of Computer Vision, 72(2): pages 107-132, April 2007.
Keywords : RJMCMC, Buildings, Stochastic geometry, Marked point process, Digital Elevation Model (DEM).
@ARTICLE{ortner_ijcv_05,
|
| author |
= |
{Ortner, M. and Descombes, X. and Zerubia, J.}, |
| title |
= |
{Building Outline Extraction from Digital Elevation Models using Marked Point Processes}, |
| year |
= |
{2007}, |
| month |
= |
{April}, |
| journal |
= |
{International Journal of Computer Vision}, |
| volume |
= |
{72}, |
| number |
= |
{2}, |
| pages |
= |
{107-132}, |
| url |
= |
{http://www.springerlink.com/content/d563v16957427102/?p=873bd324c7c14049a45cc1f2905b5a86&pi=0}, |
| keyword |
= |
{RJMCMC, Buildings, Stochastic geometry, Marked point process, Digital Elevation Model (DEM)} |
| } |
|
40 - ant colony optimization for image regularization based on a non-stationary Markov modeling.
S. Le Hegarat-Mascle and A. Kallel and X. Descombes. IEEE Trans. on Image Processing, 16(3): pages 865-878, March 2007.
Keywords : Markov Random Fields, Ants colonization.
@ARTICLE{Ants07,
|
| author |
= |
{Le Hegarat-Mascle, S. and Kallel, A. and Descombes, X.}, |
| title |
= |
{ant colony optimization for image regularization based on a non-stationary Markov modeling}, |
| year |
= |
{2007}, |
| month |
= |
{March}, |
| journal |
= |
{IEEE Trans. on Image Processing}, |
| volume |
= |
{16}, |
| number |
= |
{3}, |
| pages |
= |
{865-878}, |
| keyword |
= |
{Markov Random Fields, Ants colonization} |
| } |
Abstract :
Ant colony optimization (ACO) has been proposed as a promising tool for regularization in image classification. The algorithm is applied here in a different way than the classical transposition of the graph color affectation problem. The ants collect information through the image, from one pixel to the others. The choice of the path is a function of the pixel label, favoring paths within the same image segment. We show that this corresponds to an automatic adaptation of the neighborhood to the segment form, and that it outperforms the fixed-form neighborhood used in classical Markov random field regularization techniques. The performance of this new approach is illustrated on a simulated image and on actual remote sensing images |
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