Stacey Levine

Professor of Mathematics/Department Chair
McAnulty College and Graduate School of Liberal Arts
Mathematics

College Hall 440
Phone: 412.396.6467
levines@duq.edu

Education:

B.S., University of Florida
M.S., University of Florida
Ph.D., Mathematics, University of Florida, 2000
Courses
MATH 250: Foundations of Higher Mathematics
MATH 310: Linear Algebra
MATH 314: Differential Equations
MATH 415W: Real Analysis I
MATH 416W: Real Analysis II

CPMA 551: Digital Image Processing
CPMA 571: Optimization
Grants

Principal Investigator: Learning geometry for inverse problems in imaging, NSF-DMS, Computational Data Science and Engineering Program. July 2018-June 2021

Principal Investigator: RUI: New Applications of Curvature in Image Processing, NSF-DMS, Computational Mathematics, RUI Program. June 2013-May 2017

Principal Investigator: RUI: New Variational Models for Denoising, Decomposition, and Deblurring, NSF-DMS, Computational Mathematics, RUI Program. July 2009-June 2013

Principal Investigator: RUI: Variational and PDE-based methods for image processing, Source: NSF-DMS, Applied Mathematics, RUI Program. August 2005-July 2009

Selected Publications

Buzzard, G., Chambolle, A., Cohen, J.*, Levine, S., & Lucier, B. Pointwise Besov Space Smoothing of Images. Journal of Mathematical Imaging and Vision, 61 (1), pp. 1-20, 2019.

Sajewski, A.*, & Levine, S. (2019). Quantifying Iron Overload using MRI, Active Contours, and Convolutional Neural Networks. 11th Annual Undergraduate Research & Scholarship Symposium, pp. 1-10, 2019.

Gabriela Ghimpeteanu, Thomas Batard, Stacey Levine and Marcelo Bertalmío, “Three Approaches to Improve Denoising that Do Not Involve Developing New Denoising Methods,” in Denoising of Photographic Images and Video. Springer International Publishing, pp. 295-329, 2018.

G. Ghimpeteanu, T. Batard, M. Bertalmío, and S. Levine, “A decomposition framework for image denoising algorithms,” Image Processing, IEEE Transactions on, vol. 25, no. 1, pp. 388–399, Jan 2016.

G. Ghimpeteanu, D. Kane, T. Batard, S. Levine, M. Bertalmío, “Local denoising based on curvature smoothing can visually outperform non-local methods on photographs with actual noise,” Image Processing (ICIP), IEEE International Conference on, 3111-3115, 2016.

J. Matuk*, S. Levine, and M. Bertalmío. The Curvature Noise Distribution and Applications.In Midstates Conference for Undergraduate Research in Computer Science and Mathematics,pages M1-M4. http://www.cs.bgsu.edu/MCURCSM/proceedings/A-3.pdf, 2015.

G. Ghimpeteanu, T. Batard, M. Bertalmío, S. Levine, Denoising an Image by Denoising its Components in a Moving Frame, Proceedings of the International Conference on Image and Signal Processing, p. 375-383, 2014. Best Paper Award.

M. Bertalmío and S. Levine, Denoising an Image by Denoising its Curvature Image. SIAM Journal of Imaging Science, 7, no.1, p.187-211, 2014.

K. Heaps*, J. Koslosky*, S. Levine, and G. Sidle*, Image Fusion using Gaussian Mixture Models. Proceedings of the British Machine Vision Conference, p. 89.1-89.11, 2013.

M. Bertalmío and S. Levine, Color matching for stereoscopic cinema, Proceedings of the International Conference on Computer Vision / Computer Graphics Collaboration Techniques and Applications: MIRAGE, 6 p. 1-6, 2013.

M. Bertalmío and S. Levine, A Variational Approach for Fusing Exposure Bracketed Images. IEEE Transactions on Image Processing, 22:2, p. 712-723, 2013.

A. Chambolle, S. Levine, and B. Lucier, An upwind finite-difference method for total variation-based image smoothing, SIAM Journal on Imaging Science, 4, no.1, p. 277-299, 2011.

M. Bertalmío and S. Levine, Fusion of Bracketing Pictures, Proceedings of the Conference on Visual Media Production, p. 25-34, 2009.

Y. Chen, S. Levine, and M. Rao, Variable Exponent, Linear Growth Functionals in Image Restoration, SIAM Journal of Applied Mathematics, 66(4) p. 1383-1406, 2006.

S. Levine, An Adaptive Variational Approach for Image Decomposition, S. Levine, Energy Minimization Methods in Computer Vision and Pattern Recognition, Springer Verlag LNCS No. 3757, p. 382-397, 2005.

Y. Chen and S. Levine, Image Recovery via Diffusion Tensors and Time-Delay Regularization, Journal of Visual Communication and Image Communication, 13 p. 156-175, 2002.

Y. Chen and S. Levine, The Existence of the Heat Flow of H-systems, Journal of Discrete and Continuous Dynamical Systems, 8:1 p. 219-236, 2002.

Y. Chen and S. Levine, Anisotropic Diffusion Driven by Diffusion Tensors, in the SPIE Proceedings for the Symposium on Optical Science and Technology, p. 148-157, 2000.

Professional Service

Program Director for SIAM Activity Group on Imaging, January 2018-December 2019.

First Vice Chair, MAA Allegheny Section, May 2019-May 2020.

Second Vice Chair, MAA Allegheny Section, May 2018-May 2019.

Editorial Board for SIAM Journal of Imaging Science, 2012-2018.

Program Director for SIAM Activity Group on Imaging, January 2008-December 2009.

Scientific Program Committee Member

  • International Symposium on Intelligent Computing Systems, Merida, Mexico, March 16-18, 2018.
  • International Symposium on Intelligent Computing Systems, Merida, Mexico, March 21-23, 2016.
  • Scale Space and Variational Methods in Computer Vision, Lège Cap Ferret, France, May-June 2015.

Conference Co-organizer

  • SIAM Conference on Imaging Science, Toronto, Cananda, July 2020.
  • SIAM Conference on Imaging Science, Chicago, IL, April 2010.

Workshop Co-organizer

  • Workshop on Geospatial Imaging, Institute for Mathematics and Applications, Minneapolis, MN, September 2013.
  • Workshop on Computing in Image Processing, Computer Graphics, Virtual Surgery, and Sports, Institute for Mathematics and Applications, Minneapolis, MN, March 2011.

SIAM Mini-symposium Co-organizer

  • SIAM Conference on Imaging Science, “Denoising in Photography and Video” Bologna, Italy, May 2018.
  • SIAM Annual Meeting, "Boosting and Learning in Mathematical Imaging Algorithms" Pittsburgh, PA, July 2017.
  • SIAM Conference on Imaging Science, "Differential Geometry-based Models in Image Processing" New Mexico, May, 2016.
  • Recent Trends in Denoising, SIAM Conference on Imaging Science, Hong Kong, May 2014.
  • Multiframe Image Processing, SIAM Conference on Imaging Science, Philadelphia, PA, May 2012.
  • New Trends in Mathematical Methods in Imaging Science , Joint Mathematics Meeting, San Francisco, CA, January 2010.
  • Mathematical Methods in Biomedical Image Analysis, SIAM Conference on Imaging Science, San Diego, CA, July 2008.
  • PDE Based Methods in Image Processing, SIAM Conference on the Analysis of Partial Differential Equations, Phoenix, AZ, December 2007.
  • Variational Methods in Image Decomposition, SIAM Conference on Imaging Science, Minneapolis, MN, May 2006.

AMS (American Mathematical Society) Special Session Co-organizer

  • Mathematical Methods in Image Processing, Joint International AMS-SBM Meeting, Rio de Janeiro, Brazil, June 2008.
  • PDE-Based Methods in Imaging and Vision, AMS Fall Eastern Meeting, University of Pittsburgh, Pittsburgh, PA, November 2004.