Publications of Luminita A. Vese

Refereed Journal Publications:
  • A variational method in image recovery
    Aubert G., Vese L., SIAM Journal on Numerical Analysis, 34 (5): 1948-1979, Oct 1997.
  • A method to convexify functions via curve evolution
    Vese L, Communications in Partial Differential Equations, 24 (9-10):1573-1591, 1999.
  • Active contours without edges
    Chan, T.F.; Vese, L.A., IEEE Transactions on Image Processing, 10 (2), Feb. 2001, pp. 266 -277.
  • Active contours without edges for vector-valued images
    Chan T.F., Sandberg B.Y., Vese L.A., Journal of Visual Communication and Image Representation, 11 (2):130-141, June 2000 (Special Issue of "Scale Space Theories in Computer Vision '99").
  • A study in the BV space of a denoising-deblurring variational problem
    Vese L., Applied Mathematics and Optimization, 44 (2):131-161, Sep-Oct 2001.
  • A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
    Luminita A. Vese and Tony F. Chan, International Journal of Computer Vision 50(3), 271-293, 2002.
  • Numerical Methods for $p-harmonic$ Flows and Applications to Image Processing
    L. Vese and S. Osher, SIAM Journal on Numerical Analysis, 40. (6), pp. 2085-2104, 2002.
  • Modeling Textures with Total Variation Minimization and Oscillating Patterns in Image Processing
    Luminita A. Vese and Stanley J. Osher, Journal of Scientific Computing, 19(1-3), 2003, pp. 553-572.
  • Simultaneous Structure and Texture Image Inpainting
    M. Bertalmio, L. Vese, G. Sapiro, S. Osher, IEEE Transactions on Image Processing, 12(8), 2003, pp. 882 -889.
  • Image decomposition and restoration using total variation minimization and the $H^{-1}$ norm
    S. Osher, A. Sole, L. Vese, Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, 1(3), 2003, pp. 349 - 370.
  • Image denoising and decomposition with total variation minimization and oscillatory functions
    L. Vese, S. Osher, Journal of Mathematical Imaging and Vision, 20: 7-18, 2004.
  • A Multiscale Image Representation Using Hierarchical $(BV,L^2)$ Decompositions
    E. Tadmor, S. Nezzar, L. Vese, Multiscale Modeling and Simulation, 2(4), 554-579, 2004.
  • Numerical methods for minimization problems constrained to S-1 and S-2
    T. Cecil, S. Osher, L. Vese, J. of Computational Physics 198 (2): 567-579, 2004.
  • Segmentation under geometrical conditions using geodesic active contours and interpolation using level set methods
    C. Gout, C. Le Guyader, L. Vese, Numerical Algorithms 39 (1-3), 155-173, 2005.
  • Image Decomposition Using Total Variation and div(BMO)
    Triet M. Le and Luminita A. Vese, Multiscale Modeling and Simulation, 4(2): 390-423, 2005.
  • Iteratively solving linear inverse problems under general convex constraints,
    Ingrid Daubechies, Gerd Teschke and Luminita Vese, Inverse Problems and Imaging (IPI), 1(1): 29-46, 2007.
  • A piecewise-constant binary model for electrical impedance tomography,
    Nicolay M. Tanushev and Luminita A. Vese, Inverse Problems and Imaging(IPI), Volume: 1, Number: 2, pp. 423 - 435, May 2007.
  • Image decompositions using bounded variation and generalized homogeneous Besov spaces,
    John B. Garnett, Triet M. Le, Yves Meyer, Luminita A. Vese, Appl. Comput. Harmon. Anal. 23 (2007), pp. 25-56.
  • T. Le and L. Vese, Additive and Multiplicative Piecewise-Smooth segmentation Models in a Functional Minimization Approach, Interpolation Theory and Applications: A conference in honor of Michael Cwikel, Miami, Florida, Editors: Laura De Carli and Mario Milman, Comtemporay Mathematics, vol. 445, pp. 207-223, 2007.
  • Self-Repelling Snakes for Topology-Preserving Segmentation Models,
    Carole Le Guyader and L. Vese, IEEE TIP 17(5), 2008.
  • Multiscale hierarchical decomposition of images with applications to deblurring, denoising and segmentation,
    E. Tadmor, S. Nezzar and L. Vese, Commun. Math. Sci. Vol. 6, No. 2, pp. 281-307, 2008.
  • Image Restoration and Decomposition via Bounded Total Variation and Negative Hilbert-Sobolev Spaces, Linh H. Lieu and Luminita A. Vese, Applied Mathematics & Optimization 58: 167-193, 2008.
  • Image recovery using functions of bounded variation and Sobolev spaces of negative differentiability , Y. Kim, L.A. Vese, Inverse Problems and Imaging, vol 3, 2009, 43 -- 68
  • Enforcing local context into shape statistics, Byung-Woo Hong, Stefano Soatto, and Luminita A. Vese, Advances in Computational Mathematics.
  • JMIV
  • Jason

    Invited Book Chapters and other Invited Publications:
  • On some iterative concepts for image restoration, Ingrid Daubechies, Gerd Teschke and Luminita Vese, in Advances in Imaging and Electronics, vol. 150, Peter W. Hawkes (Ed.), Elsevier, pp. 2-52, 2008.
  • Active Contour and Segmentation Models Using Geometric PDE's for Medical Imaging
    Tony F. Chan and Luminita A. Vese, in Malladi, R. (Ed.), ``Geometric Methods in Bio-Medical Image Processing'', Series: Mathematics and Visualization, Springer, 2002, pp. 63-75.
  • Multiphase Object Detection and Image Segmentation
    Luminita A. Vese, in "Geometric Level Set Methods in Imaging, Vision and Graphics", S. Osher and N. Paragios (eds), Springer Verlag, 2003, pp. 175-194.
  • Variational PDE models & methods for image processing
    P. Blomgren, T. Chan, P. Mulet, L. Vese and W.L. Wan, in ``Numerical Analysis 1999'', D.F. Griffiths and G.A. Watson (Editors), Chapman & Hall/CRC Research Notes in Mathematics, 420: 43-67, 1999.
  • An Efficient Variational Multiphase Motion for the Mumford-Shah Segmentation Model
    T. Chan and L. Vese, Proceedings of the 34'th Asilomar Conference on Signals, Systems, and Computers, 1: 490-494, 2000.
  • Variational PDE Models in Image Processing ,
    Tony F. Chan, Jianhong (Jackie) Shen, and Luminita Vese, Notices of the American Mathematical Society, January 2003, Volume 50 , Number 1, pp. 14-26.
  • Computational methods for image restoration, image segmentation, and texture modeling ,
    Ginmo Chung, Triet M. Le, Linh H. Lieu, Nicolay M. Tanushev and Luminita A. Vese, Computational Imaging IV, edited by Charles A. Bouman, Eric L. Miller, Ilya Pollak, Proc. of SPIE-IS&T Electronic Imaging, SPIE Vol. 6065, pp. 60650J-1 -- 60650J-15, 2006.
  • Functional minimization problems in image processing ,
    Yunho Kim and Luminita A. Vese, Proc. SPIE Vol. 6814, Charles A. Bouman, Eric L. Miller, Ilya Pollak, Editors , February 2008, pages 68140Q-1 -- 68140Q-11.

    Refereed Conference Publications:
  • SSVM 2009
  • SSVM 2009
  • SSVM 2009
  • SPIE MI 2009
  • SPIE EI 2009
  • IPMI 2009
  • Nonlinear Elastic Registration with Unbiased Regularization in Three Dimensions
    Yanovsky I; Le Guyader C; Leow A; Thompson P; Vese L, MICCAI 2008 Workshop Proceedings on Computational Biomechanics for Medicine III, K. Miller, P.M.F. Nielsen (eds.), pp. 56-67, 2008.
  • -Unbiased Volumetric Registration via Nonlinear Elastic Regularization. Igor Yanovsky, Carole Le Guyader, Alex Leow, Arthur Toga, Paul Thompson, Luminita Vese. MICCAI 2008 Workshop on Mathematical Foundations of Computational Anatomy MFCA'08, September '06, 2008, to appear in LNCS, pp. 1-12.
  • A landmark-based nonlinear elasticity model for mouse atlas registration
    T. Lin, E.-F. Lee, I. Dinov, C. Le Guyader, P. Thompson, A.W. Toga, and L.A. Vese, ISBI 2008. 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro. Page(s):788 - 791, 14-17 May 2008.
  • Multiphase Segmentation of Deformation using Logarithmic Priors
    I. Yanovsky, P.M. Thompson, S. Osher, L. Vese, and A.D. Leow, in Proceedings of IEEE Computer Society Workshop on Image Registration and Fusion, June 23, 2007.
  • An image decomposition model using the total variation and the infinity Laplacian
    C. Elion and L. Vese, in Proceedings of Electronic Imaging 2007, Computational Imaging V (C. A. Bouman/ E. L. Miller/I. Pollak, Eds.), Vol. 6498, 2007.
  • Shape Representation based on Integral Kernels: Application to Image Matching and Segmentation
    Byung-Woo Hong; Prados, E.; Soatto, S.; Vese, L.; Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on Volume 1, 17-22 June 2006 Page(s):833 - 840.
  • Color texture modeling and color image decomposition in a variational-PDE approach ,
    L.A. Vese and S.J. Osher, Proceedings of Symbolic and Numeric Algorithms for Scientific Computing, 2006. SYNASC '06. Eighth International Symposium on 26-29 Sept. 2006, pp:103 - 110
  • Energy Minimization Based Segmentation and Denoising Using a Multilayer Level Set Approach,
    Ginmo (Jason) Chung and Luminita A. Vese, in Energy Minimization Methods in Computer Vision and Pattern Recognition: 5th International Workshop, EMMCVPR 2005, St. Augustine, FL, USA, November 9-11, 2005. Proceedings Editors: Anand Rangarajan, Baba Vemuri, Alan L. Yuille, LNCS Vol. 3757/2005, pp. 439 - 455.
  • Linear and non-linear geometric object matching with implicit representation
    Leow, A.; Ming-Chang Chiang; Protas, H.; Thompson, P.; Vese, L.; Huang, H.S.C.; Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on ,Volume: 3 , Aug. 23-26, 2004 Pages:710 - 713
  • Image decomposition, image restoration, and texture modeling using total variation minimization and the $H^{-1}$ norm
    S. Osher, A. Sole, and L. Vese, Proceedings of the 2003 IEEE International Conference in Image Processing, 2003.
  • Image Filling-In in a Decomposition Space,
    M. Bertalmio, L. Vese, G. Sapiro, S. Osher, Proceedings of the 2003 IEEE International Conference on Image Processing, 2003.
  • A new Framework for Object Warping: a Semi-Lagrangian Level Set Approach ,
    W.-H. Liao, H. Protas, M. Bergsneider, L. Vese, S.-H. Huang, S. Osher, Proceedings of the 2003 IEEE International Conference on Image Processing, 2003.
  • Computational Anatomy and Implicit Object Representation: A Level Set Approach
    W.-H. Liao, L. Vese, S.-C. Huang, M. Bergsneider and S. Osher, LNCS Volume 2717 , pp. 40-49, 2003 ( Biomedical Image Registration, Second International Workshop, WBIR 2003, Philadelphia, PA, USA, June 23-24, 2003).
  • A level set algorithm for minimizing the Mumford-Shah functional in image processing
    T. Chan and L. Vese, IEEE/Computer Society Proceedings of the 1st IEEE Workshop on ``Variational and Level Set Methods in Computer Vision'', 2001, 161-168.
  • An active contour model without edges
    T. Chan and L. Vese, Scale-Space Theories in Computer Vision, Lecture Notes in Computer Science, 1682:141-151, 1999.
  • Simultaneous structure and texture image inpainting
    M. Bertalmio, L. Vese, G. Sapiro, S. Osher, Proceedings of 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume: 2, 2003, pp. 707 -712.
  • A variational approach for noise removal of parametric images in tracer kinetic modelling
    W.H. Liao, L. Kashida, L. Vese, M. Bergsneider, S.C. Huang, Neuroimage 16(3), 2002, S68-S69 Part 2 Suppl. S.
  • 3D shape from anisotropic diffusion
    P. Favaro, S. Osher, S. Soatto, L. Vese, Proceedings of 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume: 1, 2003, pp. 179 -186.
  • A new framework of quantifying differences between images by matching gradient fields and its application to image blending
    Wei-Hsun Liao; Chin-Lung Yu; Bergsneider, M.; Vese, L.; Sung-Cheng Huang; Nuclear Science Symposium Conference Record, 2002 IEEE ,Volume: 2 , 10-16 Nov. 2002 Pages:1092 - 1096 vol.2

    Preprints (UCLA CAM Reports):
  • Image Restoration and Decompostion via Bounded Total Variation and Negative Hilbert-Sobolev Spaces
    Linh Lieu and Luminita Vese, UCLA CAM Report 05-33, May 2005, to appear in Applied Mathematics and Optimization.
  • Image Segmentation Using a Multilayer Level-Set Approach
    Jason T. Chung and Luminita A. Vese, UCLA CAM Report 03-53, September 2003.
  • Additive and Multiplicative Piecewise-Smooth Setmentation Models in a Variational Level Set Approach
    Triet Le and Luminita A. Vese, UCLA CAM Report 03-52, September 2003.
  • From Landmark Matching to Shape and Open Curve Matching: A Level Set Approach
    W.-H. Liao, A. Khuu, M. Bergsneider, L. Vese, S.-C. Huang, S. Osher, UCLA CAM Report 02-59, November 2002.
  • A Level-Set and Gabor-Based Active Contour Algorithm for Segmenting Textured Images
    B. Sandberg, T. Chan, L. Vese, UCLA CAM Report 02-39, July 2002.
  • The Level Set Method Links Active Contours, Mumford-Shah Segmentation, and Total Variation Restoration
    Luminita A. Vese and Stanley J. Osher, UCLA CAM Report 02-05, February 2002.
  • Image Segmentation Using Level Sets and the Piecewise-Constant Mumford-Shah Model
    T. Chan and L. Vese, UCLA CAM Report 00-14, April 2000.
  • A Level Set Algorithm for Minimizing the Mumford-Shah Functional in Image Processing
    T. Chan and L. Vese, UCLA CAM Report 00-13, April 2000.
  • Reduced Non-Convex Functional Approximations for Image Restoration and Segmentation
    L. Vese, T. Chan, UCLA CAM Report 97-56, 1997.

    Ph.D. Thesis:
    Abstract    Full Text
    Thesis title: Variational methods and partial differential equations for image analysis and curve evolution.
    Thesis advisors: Professors Gilles Aubert & Michel Rascle
    University of Nice - Sophia Antipolis, France, November 1996.