Search

Your search keyword '"Escande, Paul"' showing total 5 results
Start Over Author "Escande, Paul" Topic [spi.signal]engineering sciences [physics]/signal and image processing
5 results on '"Escande, Paul"'

1. Full inference for the anisotropic fractional Brownian field

Author

Escande, Paul, Richard, Frédéric, Institut de Mathématiques de Marseille (I2M), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), and RICHARD, Frédéric

Subjects
[STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], [STAT.AP] Statistics [stat]/Applications [stat.AP], [STAT.ME]Statistics [stat]/Methodology [stat.ME], [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
Abstract

The anisotropic fractional Brownian field (AFBF) is a non-stationary Gaussian random field which has been used for the modeling of textured images. In this paper, we address the open issue of estimating the functional parameters of this field, namely the topothesy and Hurst functions. We propose an original method which fits the empirical semi-variogram of an image to the semi-variogram of a turning-band field that approximates the AFBF. Expressing the fitting criterion in terms of a separable non-linear least square criterion, we design a minimization algorithm inspired from the variable projection approach. This algorithm also includes a coarse-to-fine multigrid strategy based on approximations of functional parameters. Compared to existing methods, the new method enables to estimate both functional parameters on their whole definition domain. On simulated textures, we show that it has a low estimation error, even when the parameters are approximated with a high precision. We also apply the method to characterize mammograms and sample images with synthetic parenchymal patterns.

Published
2023

2. A scalable estimator of sets of integral operators

Author

Debarnot, Valentin, Escande, Paul, Weiss, Pierre, Institut des Technologies Avancées en sciences du Vivant (ITAV), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Institut de Mathématiques de Marseille (I2M), Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU), FRM grant number ECO20170637521, and ANR-17-CE23-0013,OMS,Optimisation sur des espaces de mesures(2017)

Subjects
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience; The main objective of this work is to estimate a low dimensional subspace of operators in order to improve the identifiability of blind inverse problems.We propose a scalable method to find a subspace $\widehat \H$ of low-rank tensors that simultaneously approximates a set of integral operators. The method can be seen as a generalization of tensor decomposition models, which was never used in this context. In addition, we propose to construct a convex subset of $\widehat \H$ in order to further reduce the search space. We provide theoretical guarantees on the estimators and a few numerical results.

Published
2019

3. Accelerating ℓ 1 − ℓ 2 deblurring using wavelet expansions of operators

Author

Escande, Paul, Weiss, Pierre, Département d'Ingénierie des Systèmes Complexes (DISC), Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO), Institut de Mathématiques de Toulouse UMR5219 (IMT), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), PRIMO (ITAV), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut des Technologies Avancées en sciences du Vivant (ITAV), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Regenerative Medicine and Skeleton research lab (RMeS), Ecole Nationale Vétérinaire, Agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Centre hospitalier universitaire de Nantes (CHU Nantes)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), and Université de Nantes (UN)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
preconditioning, inverse problems, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], image de- blurring, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, GPU programming, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], sparse wavelet expansion, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, ComputingMilieux_MISCELLANEOUS, [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA]
Abstract

International audience; Image deblurring is a fundamental problem in imaging, usually solved with compu-tationally intensive optimization procedures. The goal of this paper is to provide new efficient strategies to reduce computing times for simple 1 − 2 deblurring models. We show that the minimization can be significantly accelerated by leveraging the fact that images and blur operators are compressible in the same orthogonal wavelet basis. The proposed methodology consists of three ingredients: i) a sparse approximation of the blur operator in wavelet bases, ii) a diagonal preconditioner and iii) an implementation on massively parallel architectures. Combing the three ingredients leads to acceleration factors ranging from 30 to 250 on a typical workstation. For instance, a 1024 × 1024 image can be deblurred in 0.15 seconds.

Published
2018

4. Contrast Invariant SNR

Author

Weiss, Pierre, Escande, Paul, Dong, Yiqiu, Institut de Mathématiques de Toulouse UMR5219 (IMT), Centre National de la Recherche Scientifique (CNRS)-PRES Université de Toulouse-Université Toulouse III - Paul Sabatier (UPS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse 1 Capitole (UT1), Institut des Technologies Avancées en sciences du Vivant (ITAV), Université Toulouse III - Paul Sabatier (UPS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Département de Mathématiques, Informatique, Automatique (DMIA), Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO), Department of Applied Mathematics and Computer Science [Lyngby] (DTU Compute), Technical University of Denmark [Lyngby] (DTU), and RITC OPTIMUS

Subjects
convex optimization, topographic map, image quality measure, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], signal-to-noise-ratio, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, isotonic regression, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Local contrast change, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], illumination invariance, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

We design an image quality measure independent of local contrast changes, which constitute simple models of illumination changes. Given two images, the algorithm provides the image closest to the first one with the component tree of the second. This problem can be cast as a specific convex program called isotonic regression. We provide a few analytic properties of the solutions to this problem. We also design a tailored first order optimization procedure together with a full complexity analysis. The proposed method turns out to be practically more efficient and reliable than the best existing algorithms based on interior point methods. The algorithm has potential applications in change detection, color image processing or image fusion. A Matlab implementation is available at http://www.math.univ-toulouse.fr/ ∼ weiss/PageCodes.html.

Published
2016

5. Real-time $\ell^1$ − $\ell^2$ deblurring using wavelet expansions of operators

Author

Escande, Paul, Weiss, Pierre, Département de Mathématiques, Informatique, Automatique (DMIA), Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO), Institut de Mathématiques de Toulouse UMR5219 (IMT), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Institut des Technologies Avancées en sciences du Vivant (ITAV), Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)

Subjects
inverse problems, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Numerical Analysis (math.NA), GPU programming, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Optimization and Control (math.OC), preconditioning, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], FOS: Mathematics, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Mathematics - Numerical Analysis, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], Mathematics - Optimization and Control, sparse wavelet expansion, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA], image de-blurring
Abstract

Image deblurring is a fundamental problem in imaging, usually solved with com-putationally intensive optimization procedures. We show that the minimization can be significantly accelerated by leveraging the fact that images and blur operators are compressible in the same orthogonal wavelet basis. The proposed methodology consists of three ingredients: i) a sparse approximation of the blur operator in wavelet bases, ii) a diagonal preconditioner and iii) an implementation on massively parallel architectures. Combing the three ingredients leads to acceleration factors ranging from 30 to 250 on a typical workstation. For instance, a 1024 x 1024 image can be deblurred in 0.15 seconds, which corresponds to real-time.

Published
2015

Catalog

Books, media, physical & digital resources
See catalog results