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Jean-Francois Aujol's main Publications

Optimization          Inverse Problems          Mathematical Imaging Sciences          Image processing

 

Optimization

 

  1. Parameter-Free FISTA by Adaptive Restart and Backtracking,
    J-F. Aujol, L. Calatroni, C. Dossal, H. Labarriere, and A. Rondepierre, SIAM Journal on Optimization, 2024.
  2. FISTA is an automatic geometrically optimized algorithm for strongly convex functions,
    J-F. Aujol, C. Dossal, and A. Rondepierre, Mathematical Programming, volume 204, issue 1-2, 2024.
  3. Fast convergence of inertial dynamics with Hessian-driven damping under geometry assumptions,
    J-F. Aujol, C. Dossal, Van Hao Hoang, H. Labarriere, and A. Rondepierre, Applied Mathematics and Optimization, volume 88, issue 3, 2023
  4. Convergence rates of the Heavy-Ball method for quasi-strongly convex optimization,
    J-F. Aujol, C. Dossal, and A. Rondepierre, SIAM Journal on Optimization, volume 32, issue 3, 2022.
  5. Convergence rates of the Heavy-Ball method with Lojasiewicz property,
    J-F. Aujol, C. Dossal, and A. Rondepierre, Mathematical Programming, pages 1-60, 2022.
  6. Convergence rates of an inertial gradient descent algorithm under growth and flatness conditions,
    V. Apidopoulos, J-F. Aujol, C. Dossal, and A. Rondepierre, Mathematical Programming, pages 1-43, 2020.
  7. Optimal convergence rates for Nesterov acceleration,
    J-F. Aujol, C. Dossal, and A. Rondepierre, SIAM Journal on Optimization, volume 29, number 4, pages 3131-3153, 2019.
  8. Convergence rate of inertial Forward-Backward algorithm beyond Nesterov's rule ,
    V. Apidopoulos, J-F. Aujol, and C. Dossal, Mathematical Programming, 2018.
  9. The differential inclusion modeling the FISTA algorithm and optimality of convergence rate in the case b<=3,
    V. Apidopoulos, J-F Aujol and C. Dossal, SIAM Journal on Optimization, volume 28, number 1, pages 551-574, 2018.
  10. Stability of over-relaxations for the Forward-Backward algorithm, Application to FISTA,
    J-F. Aujol and C. Dossal, SIAM Journal on Optimization, volume 25, number 4, pages 2408-2433, 2015.
  11. Some first-order algorithms for total variation based image restoration
    Jean-Francois Aujol, Journal of Mathematical Imaging and Vision, volume 34, number 3, pages 307-327, July 2009.

 

Inverse Problems

 

  1. Estimation of off-the-grid sparse spikes with over-parametrized projected gradient descent: theory and application,
    P-J. Bénard, Y. Traonmilin, J-F. Aujol, and E. Soubies, Inverse Problems, volume 40, number 5, 2024 .
  2. Sketched over-parametrized projected gradient descent for sparse spike estimation,
    P-J. Bénard, Y. Traonmilin, and J-F. Aujol, IEEE Signal Processing Letters, 2024.
  3. Minimizing Quotient Regularization Model,
    C. Wang, J-F. Aujol, G. Gilboa, and Y. Lou, Inverse Problems and Imaging, 2024.
  4. On strong basins of attractions for non-convex sparse spike estimation: upper and lower bounds,
    Y. Traonmilin, J-F. Aujol, P-J. Bénard, and A. Leclaire, Journal of Mathematical Imaging and Vision, volume 66, issue1, 2023.
  5. The basins of attraction of the global minimizers of non-convex inverse problems with low-dimensional models in infinite dimension,
    Y. Traonmilin, J-F. Aujol, and A. Leclaire, Information and Inference, volume 12, issue 1, 2023.
  6. Image super-resolution with PCA Reduced generalized Gaussian mixture models,
    L. Nguyen, J. Hertrich, J-F. Aujol, Y. Berthoumieu, Inverse Problems and Imaging, volume 17, number 6, pp. 1165-1192, 2023.
  7. PCA Reduced Gaussian Mixture Models with Applications in Superresolution,
    J. Hertrich, L. Nguyen, J-F. Aujol, D. Bernard, Y. Berthoumieu, A. Saadaldin and G. Steidl, Inverse Problems and Imaging, volume 16, number 2, 2022.
  8. Projected Gradient Descent for Non-Convex Sparse Spike Estimation,
    Y. Traonmilin, J.-F. Aujol, and A. Leclaire, IEEE Signal Processing Letters, volume 27, 2020.
  9. The basins of attraction of the global minimizers of the non-convex sparse spike estimation problem,
    Y. Traonmilin and J-F. Aujol, Inverse Problems, volume 36, number 4, 2020.
  10. Some proximal methods for Poisson intensity CBCT and PET
    S. Antoine, J-F. Aujol, Y. Boursier and C. Melot, Inverse Problems and Imaging, volume 6, number 4, 2012.

 

Mathematical Imaging Sciences

 

  1. Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoising,
    H. Shi, Y. Traonmilin, and J-F. Aujol, Journal of Mathematical Imaging and Vision, 2024.
  2. Compressive learning for patch-based image denoising,
    H. Shi, Y. Traonmilin, and J-F. Aujol, SIAM Journal on Imaging Sciences, volume 15, issue 3, 2022.
  3. Recent Approaches for Image Colorization,
    F. Pierre and J-F. Aujol, in Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, 2021.
  4. Rayleigh quotient minimization for absolutely one-homogeneous functionals ,
    T. Feld, J-F. Aujol, G. Gilboa, and N. Papadakis, Inverse Problems, volume 35, number 6, 2019.
  5. Theoretical Analysis of Flows Estimating Eigenfunctions of One-homogeneous Functionals,
    J-F. Aujol, G. Gilboa, and N. Papadakis, SIAM Journal on Imaging Sciences, volume 11, number 2, pages 1416-1440, 2018.
  6. Variational Methods for Normal Integration,
    Y. Queau, J-D Durou and J-F Aujol, Journal of Mathematical Imaging and Vision, volume 60, issue 4, pages 609-632, 2018.
  7. Normal Integration: A Survey,
    Y. Queau, J-D Durou and J-F Aujol, Journal of Mathematical Imaging and Vision, volume 60, issue 4, pages 576-593, 2018.
  8. Interactive Video Colorization within a Variational Framework,
    F. Pierre, J-F. Aujol, A. Bugeau, and V. Ta, SIAM Journal on Imaging Sciences, volume 10, number 4, pages 2293-2325, 2017.
  9. Variational Contrast Enhancement of Gray-Scale and RGB Images,
    F. Pierre, J-F. Aujol, A. Bugeau, G. Steidl, and V. Ta, Journal of Mathematical Imaging and Vision, volume 57, pages 99-116, 2017.
  10. Estimation of the noise level function based on a non-parametric detection of homogeneous image regions,
    C. Sutour, C-A. Deledalle, and J-F. Aujol, SIAM Journal on Imaging Sciences, volume 8, number 4, pages 2622-2661, 2015.
  11. Edge-based multi-modal registration and application for night vision devices,
    C. Sutour, J-F. Aujol, C-A. Deledalle, and B. Denis de Senneville, Journal of Mathematical Imaging and Vision, volume 53, number 2, pages 131-150, 2015.
  12. Luminance-Chrominance Model for Image Colorization,
    F. Pierre, J-F. Aujol, A. Bugeau, N. Papadakis, and V. Ta, SIAM Journal on Imaging Sciences, volume 8, number 1, pages 536-563, 2015.
  13. Regularized Discrete Optimal Transport,
    S. Ferradans, N. Papadakis, G. Peyre, and J-F. Aujol, SIAM Journal on Imaging Sciences, 2014, volume 7, issue 3, pp. 1853-1882, 2014.
  14. Synthesizing and Mixing Stationary Gaussian Texture Models
    G-S. Xia, S. Ferradans, G. Peyre, and J-F. Aujol, SIAM Journal on Imaging Sciences, volume 8, number 1, pp 476-508, 2014.
  15. Poisson Skeleton Revisited: A New Mathematical Perspective
    G. Aubert and J-F. Aujol, Journal of Mathematical Imaging and Vision, volume 48, issue 1, pp 149-159, 2014.
  16. High-dimension multi-label problems: convex or non convex relaxation?
    N. Papadakis, R. Yildizoglu, J-F. Aujol and V. Caselles, SIAM Journal on Imaging Sciences, volume 6, number 4, pp 2603-2639, 2013.
  17. A bias-variance approach for the Non-Local Means
    Vincent Duval, Jean-Francois Aujol and Yann Gousseau, SIAM Journal on Imaging Sciences, volume 4, number 2, pages 760-788, 2011.
  18. Locally parallel texture modeling
    Pierre Maurel, Jean-Francois Aujol and Gabriel Peyre, SIAM Journal on Imaging Sciences, volume 4, number 1, pages 413-447, 2011.
  19. Exemplar-based inpainting from a variational point of view
    Jean-Francois Aujol , Said Ladjal, and Simon Masnou, SIAM Journal on Mathematical Analysis, volume 42, issue 3, pages 1246-1285, 2010.
  20. Mathematical modeling of textures : application to color image decomposition with a projected gradient algorithm
    Vincent Duval, Jean-Francois Aujol and Luminita Vese, Journal of Mathematical Imaging and Vision, volume 37, issue 3, pages 232-248, 2010.
  21. The TVL1 model: a geometric point of view
    Vincent Duval, Jean-Francois Aujol and Yann Gousseau, SIAM Journal on Multiscale Modeling and Simulation, volume 8, number 1, pages 154-189, November 2009.
  22. Local scale measure from the topographic map and application to remote sensing images
    Bin Luo, Jean-Francois Aujol and Yann Gousseau, SIAM Journal on Multiscale Modeling and Simulation, volume 8, number 1, pages 1-29, September 2009.
  23. Irregular to regular sampling, denoising and deconvolution
    Gabriele Facciolo, Andres Almansa, Jean-Francois Aujol and Vicent Caselles, SIAM Journal on Multiscale Modeling and Simulation, volume 7, number 4, pages 1574-1608, April 2009.
  24. A Variational Approach to removing Multiplicative Noise
    Gilles Aubert and Jean-Francois Aujol, SIAM Journal on Applied Mathematics, volume 68, number 4, pages 925-946, January 2008.
  25. Constrained and SNR-based Solutions for TV-Hilbert Space Image Denoising
    Jean-Francois Aujol and Guy Gilboa, Journal of Mathematical Imaging and Vision, volume 26, numbers 1-2, pages 217-237, November 2006.
  26. Scale recognition, regularization parameter selection, and Meyer's G norm in total variation regularization
    David Strong, Jean-Francois Aujol and Tony Chan, SIAM Journal on Multiscale Modeling and Simulation, volume 5, number 1, pages 273-303, 2006.
  27. Structure-Texture Image Decomposition - Modeling, Algorithms, and Parameter Selection
    Jean-Francois Aujol, Guy Gilboa, Tony Chan, and Stanley Osher, International Journal of Computer Vision, volume 67, number 1, pages 111-136, April 2006.
  28. Detecting codimension-two objects in an image with Ginzburg-Landau models
    Gilles Aubert, Jean-Francois Aujol and Laure Blanc-Feraud, International Journal of Computer Vision, volume 65, numbers 1-2, pages 29-42, November 2005.
  29. Dual norms and image decomposition models
    Jean-Francois Aujol and Antonin Chambolle, International Journal of Computer Vision, volume 63, number 1, pages 85-104, June 2005.
  30. Modeling very oscillating signals. Application to image processing
    Gilles Aubert and Jean-Francois Aujol, Applied Mathematics and Optimization, volume 51, number 2, pages 163-182, March/April 2005.
  31. Image decomposition into a bounded variation component and an oscillating component
    Jean-Francois Aujol, Gilles Aubert, Laure Blanc-Feraud and Antonin Chambolle, Journal of Mathematical Imaging and Vision, volume 22, number 1, pages 71-88, January 2005.
  32. Optimal partitions, regularized solutions, and application to image classification
    Gilles Aubert and Jean-Francois Aujol, Applicable Analysis, volume 84, number 1, pages 15-35, January 2005.

 

Image processing

 

  1. Generative Adversarial Network for Pansharpening with Spectral and Spatial Discriminators,
    A. Gastineau, J-F. Aujol, Y. Berthoumieu, and C. Germain, IEEE Transactions on Geoscience and Remote Sensing, volume 60, 2021.
  2. Diffusion and inpainting of reflectance and height LiDAR orthoimages,
    P. Biasutti, J-F Aujol, M. Bredif, and A. Bugeau, Computer Vision and Image Understanding, volume 179, pages 31-40, 2019.
  3. Range-Image: Incorporating sensor topology for LIDAR point clouds processing,
    P. Biasutti, J-F Aujol, M. Bredif and A. Bugeau, Photogrammetric Engineering & Remote Sensing, volume 84, number 6, pages 367-375, 2018.
  4. Joint Inpainting of Depth and Reflectance with Visibility Estimation,
    M. Bevilacqua, P. Biasutti, J-F Aujol, M. Bredif, and A. Bugeau, ISPRS Journal of Photogrammetry and Remote Sensing, volume 125, pages 16-32, 2017.
  5. Texture Reconstruction guided by the Histogram of a High-Resolution patch,
    M. El Gueche, J-F Aujol, Y. Berthoumieu, and C-A. Deledalle, IEEE Transactions on Image Processing, volume 26, number 2, pages 549-560, 2017.
  6. Image Zoom Completion,
    M. Hidane, M. El Gueche, J-F Aujol, Y. Berthoumieu, and C-A. Deledalle, IEEE Transactions on Image Processing, volume 25, number 8, pages 3505-3517, 2016.
  7. Adaptive regularization of the NL-means: Application to image and video denoising,
    C. Sutour, C. Deledalle, and J-F. Aujol, IEEE Transactions on Image Processing, volume 23, number 8, August 2014.
  8. Indexing of satellite images with different resolutions by wavelet features
    Bin Luo, Jean-Francois Aujol, Yann Gousseau and Said Ladjal, IEEE Transactions on Image Processing, volume 17, number 8, pages 1465-1472, August 2008.
  9. Resolution independant characteristic scale dedicated to satellite images
    Bin Luo, Jean-Francois Aujol, Yann Gousseau, Said Ladjal and Henri Maitre, IEEE Transactions on Image Processing, volume 16, number 10, pages 2503-2514, October 2007.
  10. Combining geometrical and textured information to perform image classification
    Jean-Francois Aujol and Tony Chan, Journal of Visual Communication and Image Representation, volume 17, number 5, pages 1004-1023, October 2006.
  11. Color image decomposition and restoration
    Jean-Francois Aujol and Sung H. Kang, Journal of Visual Communication and Image Representation, volume 17, number 4, pages 916-928, August 2006.
  12. Wavelet-based level set evolution for classification of textured images
    Jean-Francois Aujol, Gilles Aubert and Laure Blanc-Feraud, IEEE Transactions on Image Processing, volume 12, number 12, pages 1634-1641, December 2003.

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