Veronique Delouille's homepage: research

Research

Past and Current Research

My current research focusses on solar information processing and machine learning. The goal is to fully exploit the large amounts of available space solar data for an improved understanding of solar physics phenomena. This calls for the development of automated feature recognition tools and more largely for a data science that is grounded in statistics, image processing, observational expertise, and solar physics in order to access physical information in the data that is often hidden due to their dynamical range, noise, or complexity and size of the dataset.

At Rice University, I worked on distributed estimation in sensor network. The aim was to find distributed estimation algorithms that are local, scalable, energy-consumption efficient, and fault-tolerant.

My doctoral research was concerned with the construction of wavelet transforms that automatically adapt to to the design at-hand, be it irregular, stochastic or auto-regressive. This allows to have a fast and efficient denoising method for nonparametric regression. Univariate and bivariate irregular designs were considered.

Publications

Solar physics

Nonparametric monitoring of sunspot number observations.(2022) Mathieu, Sophie; Lefèvre, Laure ; von Sachs, Rainer ; Delouille, Veronique ; Ritter, Christian ; Clette, Frédéric Journal of Quality Technology,
Uncertainty Quantification in sunspot counts (2019) S. Mathieu, R. von Sachs, C. Ritter, V. Delouille, L. Lefèvre V. Delouille, S.J. Hofmeister, M.A. Reiss, B. Mampaey, M. Temmer, A. Veronig, in The Astrophysical Journal, 886
The Observational Uncertainty of Coronal Hole Boundaries in Automated Detection Schemes (2021) Reiss, Martin A.; Muglach, Karin; Moestl, Christian; Arge, Charles N.; Bailey, Rachel ; Delouille, Veronique ; Garton, Tadhg M.; Hamada, Amr; Hofmeister, Stefan; Illarionov, Egor; Jarolim, Robert; Kirk, Michael S.F.; Kosovichev, Alexander; Krista, Larisza ; Lee, Sangwoo; Lowder, Chris; MacNeice, Peter J.; Veronig, Astrid in Astrophysical Journal Letters (ApJL)
Coronal Holes Detection Using Supervised Classification (2018) V. Delouille, S.J. Hofmeister, M.A. Reiss, B. Mampaey, M. Temmer, A. Veronig, in Machine Learning Techniques for Space Weather (31 pages - Sc. Ed. Enrico Camporeale, Simon Wing and Jay R. Johnson - pp. 365-395)
Forecasting the Arrival Time of Coronal Mass Ejections: Analysis of the CCMC CME Scoreboard (2018) P. Riley , M.L. Mays, J. Andries, T. Amerstorfer, D. Biesecker, V. Delouille, M. Dumbovic, X. Feng, E. Henley, J.A. Linker, C. MÖstl, M. Nuñez, V. Pizzo, M. Temmer, W.K. Tobiska, C. Verbeke, M.J. West, X. Zhao. Space Weather, vol. 16, no. 9, pp. 1245-1260
Segmentation of photospheric magnetic elements corresponding to coronal features to understand the EUV and UV irradiance variability (2017) J. Zender, R. Kariyappa, G. Giono, M. Bergmann, V. Delouille, L. Damé, J.F Hochedez, S.T. Kumara, Astronomy & Astrophysics, 605
Image patch analysis of sunspots and active regions. II. Clustering via dictionary learning (2016) K. Moon, V. Delouille, J. Li, R. De Visscher, F. Watson, A.O. Hero III Journal of Space Weather and Space Climate, 6, pp.A3
Image patch analysis of sunspots and active regions. I. Intrinsic dimension and correlation analysis (2016) K. Moon, J. Li, V. Delouille, R. De Visscher, F. Watson, A.O. Hero III, Journal of Space Weather and Space Climate, 6, pp.A2
Non-parametric PSF estimation from celestial transit solar images using blind deconvolution (2016) A. Gonzalez, V. Delouille, L. Jacques Journal of Space Weather and Space Climate, 6, pp.A1
Improvements on coronal hole detection in SDO/AIA images using supervised classification (2015) M.A. Reiss, S.J. Hofmeister, R. De Visscher, M. Temmer, A. M. Veronig, V. Delouille, B. Mampaey, H. Ahammer Journal of Space Weather and Space Climate, 5, pp.A23
Supervised classification of solar Features using prior information (2015) R. De Visscher, V. Delouille, P. Dupont, C. Deledalle Journal of Space Weather and Space Climate, 5, pp.A34
Reconstruction of the solar EUV irradiance from 1996 to 2010 based on SOHO/EIT images (2014) M. Haberreiter, B. Mampaey, V. Delouille, C. Verbeeck, S. Wieman, Journal of Space Weather and Space Climate
Solar Spectral Irradiance Variability in November/December 2012: Comparison of Observations by Instruments on the International Space Station and Models (2014) Thuillier, G., Schmidtke, G., Erhardt, C., Nikutowski, B., Shapiro, A. I., Bolduc, C., Lean, J., Krivova, N., Charbonneau, P., Cessateur, G., Haberreiter, M., Melo, S., Delouille, V., Mampaey, B., Yeo, K. L., Schmutz, W, Solar Physics 289(12), pages 4433-4452
Segmentation of coronal features to understand the solar EUV and UV irradiance variability (2014) S.T. Kumara, R. Kariyappa, J. Zender, G. Giono, V. Delouille, L.P. Chitta, L. Damé, J.-F. Hochedez, C. Verbeeck, B. Mampaey, V.H. Doddamani
The SPoCA-suite: software for extraction, characterization, and tracking of Active Regions and Coronal Holes on EUV images (2014) C. Verbeeck, V. Delouille, B. Mampaey, R. De Visscher, Astronomy & Astrophysics, 561
Virtual super resolution of scale invariant textured images using multifractal stochastic processes (2011) P. Chainais, E. Koenig, V. Delouille, J.-F. Hochedez, Journal of Mathematical Imaging and Vision, 39(1)
Computer Vision for the Solar Dynamics Observatory (2011) P.C.H. Martens, G. Attrill, A.R. Davey, S. Farid, P.C. Grigis, J. Kasper, K. Korreck, S.H. Saar, Y. Su, A. Savcheva, P. Testa, M. Wills-Davey, P.N. Bernasconi, M.K. Georgoulis, V. Delouille J.-F. Hochedez, J.W.. Cirtain, C.E,. DeForest, R.A. Angryk, I. De Moortel, T. Wiegelmann, Solar Physics
Fast and robust segmentation of solar EUV images: algorithm and results for solar cycle (2009) V. Barra, V. Delouille, M. Kretzschmar, J.-F. Hochedez, Astronomy & Astrophysics, Volume 505, pages 361-371.
Quantifying and containing the curse of high resolution coronal imaging (2008) V. Delouille, P. Chainais, J.-F. Hochedez , Annales Geophysicae, 26, 3169-3184
Spatial and Temporal Noise in Solar EUV Observations (2008) V. Delouille, P. Chainais, J.-F. Hochedez, Solar Physics, 248, 441-455
Segmentation of Extreme Ultraviolet Solar Images via Multichannel Fuzzy Clustering, (2008) V. Barra, V. Delouille, J.-F. Hochedez, Advances in Space Research, 42(5), 917-925.
GOES-8 X-ray sensor variance stabilization using the multiscale data-driven Haar-Fisz transform (2007) P. Fryzlewicz, V. Delouille, G.P. Nason, Journal of the Royal Statistical Society, Series C, 56, pages 99-116.
Wavelet spectrum analysis of EIT/SoHO images (2005) V. Delouille, J. de Patoul, J.-F. Hochedez, L. Jacques, and J.-P. Antoine, Solar Physics, 228, 301-321 .

Sensor Networks

Robust distributed estimation using the embedded subgraphs algorithm (2006) V. Delouille, R. Neelamani, R. G. Baraniuk, IEEE Transactions on Signal Processing, 54(8), pages 2998- 3010

Wavelet methods

Second generation wavelet denoising methods for irregularly spaced data in two dimensions (2006) V. Delouille, M. Jansen, R. von Sachs, Signal Processing, 86(7), pages 1435 - 1450.
Estimation of Nonlinear Autoregressive Models using Design-adapted Wavelets (2004), V. Delouille and R. von Sachs. Annals of the Institute of Mathematical Statistics, 57(2):235-253.
Smooth Design-adapted Wavelets for Nonparametric Stochastic Regression (2004) V. Delouille, J. Simoens, and R. von Sachs. Journal of the American Statistical Association, Volume 99(467): 643-658
Nonparametric stochastic regression with design-adapted wavelets (.ps)
V. Delouille, J. Franke and R. von Sachs. Sankhya: The Indian Journal of Statistics. Special issue on Wavelets, Series A, 63(3):328-366, 2000.

Conference Proceedings

Uncertainty quantification in Sunspots Counts (2018) S. Mathieu, R.V. Sachs, V. Delouille, L. Lefevre, Proceedings of IEEE Data Science Workshop (DSW), 1-5.
Meta learning of bounds on the Bayes classifier error (2015) K. Moon, V. Delouille, A.O. Hero III Proceeding of IEEE Signal Processing and SP Education workshop, Snowbird UT.
Image patch analysis and clustering of sunspots: a dimensionality reduction approach (2014) K. Moon, J. Li, V. Delouille, F. Watson, A.O. Hero III, IEEE International Conference on Image Processing, Paris, France
Segmentation, Tracking and Characterization of Solar Features from EIT Solar Corona Images (2009) V. Barra, V. Delouille, J.-F. Hochedez, Lecture Notes in Computer Science Volume 5575/2009, pages 199-208
Amélioration virtuelle de la résolution d'images du Soleil par augmentation d'information invariante d'échelle (2009) E. Koenig, P. Chainais, V. Delouille, J.F. Hochefez, Proceedings of GRETSI (Dijon)
Modeling images of the Quiet Sun in the extreme ultra-violet (2007), P. Chainais, V. Delouille, J.-F. Hochedez, SPIE meeting, Wavelets XII (San Diego)
Segmentation of Extreme Ultraviolet Solar Images using a Multispectral Data Fusion Process (2007) V. Barra, V. Delouille, J.-F. Hochedez; Proceedings of the IEEE Conference on Fuzzy Systems, (London), pages 211-216.
Segmentation of EIT Images Using Fuzzy Clustering: a Preliminary Study (2005) V. Barra, V. Delouille, J.-F. Hochedez, P. Chainais, Proceedings of the 11th European Solar Physics Meeting 'The Dynamic Sun: Challenges for Theory and 3 Observations' (ESA SP-600), Leuven, Belgium. Editors: D. Danesy, S. Poedts, A. De Groof and J. Andries. Published on CDROM., p.77.1
A data-driven Haar-Fisz transform for multiscale variance stabilization (2005) P. Fryzlewicz, V. Delouille, IEEE/SP 13th Workshop on Statistical Signal Processing, (Bordeaux), pages 539-544.
Robust Distributed Estimation in Sensor Networks using the Embedded Polygons Algorithm
(2004) V. Delouille, R. Neelamani, R. Baraniuk, Third International Symposium on Information Processing in Sensor Networks (IPSN 2004), pages 405-413
The Embedded Triangles Algorithm for Distributed Estimation in Sensor Networks, V. Delouille, R. Neelamani, V. Chandrasekaran, and R. Baraniuk Statistical Signal Processing Workshop, September 2003.
Design-adapted wavelet estimator for two-dimensional tensor product irregular designs, V. Delouille, J. Simoens, and R. von Sachs. In M.A. Unser, A. Aldroubi, and A.F. Laine, eds., Wavelets: Applications in Signal and Image Processing X, Proceedings of SPIE vol. 5207, pp. 880-891, 2003.

PhD Thesis

Nonparametric stochastic regression using design-adapted wavelets
Institut de Statistique, Université catholique de Louvain, Belgium, 2002

Master Thesis

Nonparametric regression estimation using design-adapted wavelets
Mémoire de DEA, Institut de Statistique, Université catholique de Louvain, Belgium, 1999.

Bayesian Variable Selection with related predictors using the Gibbs sampler
MSc thesis, University of Kent at Canterbury, UK, 1998.

Last update: August 2017