Mila Nikolova

发表

A Superresolution Framework for fMRI Sequences and Its Impact on Resulting Activation Maps

Rachid Deriche, Pierre Kornprobst, Ronald R. Peeters, 2003, MICCAI.

Regularisation functions and estimators

Mila Nikolova, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

A Convex Model for Edge-Histogram Specification with Applications to Edge-Preserving Smoothing

Raymond H. Chan, Mila Nikolova, Kelvin C. K. Chan, 2018, Axioms.

Reconstruction of locally homogeneous images

Mila Nikolova, 1998, 9th European Signal Processing Conference (EUSIPCO 1998).

Low cost adaptive algorithm for blind channel identification and symbol estimation

Mila Nikolova, Pierre Duhamel, Florence Alberge, 2000, 2000 10th European Signal Processing Conference.

Restoration of edges by minimizing non-convex cost-functions

Mila Nikolova, M. Nikolova, 2005, IEEE International Conference on Image Processing 2005.

Should We Search for a Global Minimizer of Least Squares Regularized with an ℓ0 Penalty to Get the Exact Solution of an under Determined Linear System?

Mila Nikolova, M. Nikolova, 2011, SSVM.

Below the Surface of the Non-local Bayesian Image Denoising Method

Mila Nikolova, Pablo Arias, M. Nikolova, 2017, SSVM.

Finding the global minimum for binary image restoration

Mila Nikolova, Tony F. Chan, Selim Esedoglu, 2005, IEEE International Conference on Image Processing 2005.

An iterative procedure for removing random-valued impulse noise

Chen Hu, Raymond H. Chan, Mila Nikolova, 2004, IEEE Signal Processing Letters.

Parameter selection for a Markovian signal reconstruction with edge detection

Mila Nikolova, 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

Novel Sparse Recovery Algorithms for 3D Debris Localization using Rotating Point Spread Function Imagery pdf

Raymond H. Chan, Chao Wang, Mila Nikolova, 2018, ArXiv.

Analysis of the Recovery of Edges in Images and Signals by Minimizing Nonconvex Regularized Least-Squares

Mila Nikolova, M. Nikolova, 2005, Multiscale Model. Simul..

Blind identification/equalization using deterministic maximum likelihood and a partial prior on the input

Mila Nikolova, Pierre Duhamel, Florence Alberge, 2006, IEEE Transactions on Signal Processing.

Energy Minimization Methods

Mila Nikolova, M. Nikolova, 2015, Handbook of Mathematical Methods in Imaging.

Fully Smoothed ℓ1-TV Models: Bounds for the Minimizers and Parameter Choice

Mila Nikolova, Gabriele Steidl, F. Baus, 2014, Journal of Mathematical Imaging and Vision.

Alternating Structure-Adapted Proximal Gradient Descent for Nonconvex Nonsmooth Block-Regularized Problems

Mila Nikolova, Pauline Tan, M. Nikolova, 2019, SIAM J. Optim..

Inversion of large-support ill-posed linear operators using a piecewise Gaussian MRF

Ali Mohammad-Djafari, Mila Nikolova, Jérôme Idier, 1998, IEEE Trans. Image Process..

Fast Robust Dejitter and Interslice Discontinuity Removal in MRI Phase Acquisitions: Application to Magnetic Resonance Elastography

Mila Nikolova, Ingolf Sack, Eric Barnhill, 2019, IEEE Transactions on Medical Imaging.

Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction

Mila Nikolova, Michael K. Ng, Chi-Pan Tam, 2010, IEEE Transactions on Image Processing.

Counter-Examples for Bayesian MAP Restoration

Mila Nikolova, M. Nikolova, 2007, SSVM.

Error Indicators for Adaptive Refinement of Singularly Perturbed Convection-Diffusion Problems

Mila Nikolova, 1999, LSSC.

Description of the Minimizers of Least Squares Regularized with 퓁0-norm. Uniqueness of the Global Minimizer

Mila Nikolova, M. Nikolova, 2013, SIAM J. Imaging Sci..

Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients

Mohamed-Jalal Fadili, Mila Nikolova, Sylvain Durand, 2008, Journal of Mathematical Imaging and Vision.

Adaptive solution for blind identification/equalization using deterministic maximum likelihood

Mila Nikolova, Pierre Duhamel, Florence Alberge, 2002, IEEE Trans. Signal Process..

Alternating block coordinate proximal forward-backward descent for nonconvex regularised problems with biconvex terms

Mila Nikolova, Pauline Tan, 2017 .

Locally homogeneous images as minimizers of objective functions

Mila Nikolova, 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models

Mila Nikolova, Tony F. Chan, Selim Esedoglu, 2006, SIAM J. Appl. Math..

Thresholding implied by truncated quadratic regularization

Mila Nikolova, M. Nikolova, 2000, IEEE Trans. Signal Process..

Comparison of the main forms of half-quadratic regularization

Mila Nikolova, Michael K. Ng, 2002, Proceedings. International Conference on Image Processing.

Bounds on the Minimizers of (nonconvex) Regularized Least-Squares

Mila Nikolova, M. Nikolova, 2007, SSVM.

Minimization of Cost-Functions with Non-smooth Data-Fidelity Terms to Clean Impulsive Noise

Mila Nikolova, M. Nikolova, 2003, EMMCVPR.

A Nonlocal Denoising Algorithm for Manifold-Valued Images Using Second Order Statistics

Mila Nikolova, Gabriele Steidl, Johannes Persch, 2016, SIAM J. Imaging Sci..

Disparity and Optical Flow Partitioning Using Extended Potts Priors

Mila Nikolova, Gabriele Steidl, Martin Storath, 2014, 1405.1594.

Eddy current tomography using a binary Markov model

Ali Mohammad-Djafari, Mila Nikolova, M. Nikolova, 1996, Signal Process..

Efficient removing of impulsive noise based on an l/sub 1/-l/sub 2/ cost-function

Mila Nikolova, 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

Scale Space and Variational Methods in Computer Vision

Mila Nikolova, Nicolas Papadakis, Jean-François Aujol, 2015 .

Regularizing Flows for Constrained Matrix-Valued Images

Mila Nikolova, M. Nikolova, D. Tschumperlé, 2004, Journal of Mathematical Imaging and Vision.

Fast Ordering Algorithm for Exact Histogram Specification

Mila Nikolova, Gabriele Steidl, M. Nikolova, 2014, IEEE Transactions on Image Processing.

A Characterization of Proximity Operators

Mila Nikolova, R'emi Gribonval, R. Gribonval, 2018, Journal of Mathematical Imaging and Vision.

A Variational Approach for Exact Histogram Specification

Raymond H. Chan, Mila Nikolova, You-Wei Wen, 2011, SSVM.

Markovian reconstruction in computed imaging and Fourier synthesis

Mila Nikolova, 1994, Proceedings of 1st International Conference on Image Processing.

Assumed and effective priors in Bayesian MAP estimation

Mila Nikolova, 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

A Variational Model for Color Assignment

Mila Nikolova, Gabriele Steidl, Fabien Pierre, 2015, SSVM.

The Equivalence of Half-Quadratic Minimization and the Gradient Linearization Iteration

Raymond H. Chan, Mila Nikolova, R. Chan, 2007, IEEE Transactions on Image Processing.

Minimizers of Cost-Functions Involving Nonsmooth Data-Fidelity Terms. Application to the Processing of Outliers

Mila Nikolova, M. Nikolova, 2002, SIAM J. Numer. Anal..

A two-stage method for spectral–spatial classification of hyperspectral images

Raymond H. Chan, Mila Nikolova, Robert J. Plemmons, 2018, Journal of Mathematical Imaging and Vision.

Analysis of Half-Quadratic Minimization Methods for Signal and Image Recovery

Mila Nikolova, Michael K. Ng, M. Ng, 2005, SIAM J. Sci. Comput..

Fast Hue and Range Preserving Histogram Specification: Theory and New Algorithms for Color Image Enhancement

Mila Nikolova, Gabriele Steidl, M. Nikolova, 2014, IEEE Transactions on Image Processing.

Adaptive deterministic maximum likelihood using a quasi-discrete prior

Mila Nikolova, Pierre Duhamel, Florence Alberge, 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

Journal of Mathematical Imaging and Vision 2012 1 Exact Histogram Specification for Digital Images Using a Variational Approach

Raymond H. Chan, Mila Nikolova, You-Wei Wen, 2022 .

A Three-Stage Approach for Segmenting Degraded Color Images: Smoothing, Lifting and Thresholding (SLaT)

Raymond H. Chan, Mila Nikolova, Tieyong Zeng, 2015, J. Sci. Comput..

Semi-explicit Solution and Fast Minimization Scheme for an Energy with ℓ1-Fitting and Tikhonov-Like Regularization

Mila Nikolova, M. Nikolova, 2009, Journal of Mathematical Imaging and Vision.

On 퓁1 Data Fitting and Concave Regularization for Image Recovery

Mila Nikolova, Michael K. Ng, Chi-Pan Tam, 2013, SIAM J. Sci. Comput..

Non-convex optimization for 3D point source localization using a rotating point spread function

Raymond H. Chan, Mila Nikolova, Chao Wang, 2018 .

The use of super‐resolution techniques to reduce slice thickness in functional MRI

Rachid Deriche, Olivier D. Faugeras, Pierre Kornprobst, 2004, Int. J. Imaging Syst. Technol..

The Synergy Between Different Colour Spaces For Degraded Colour Images Segmentation

Raymond H. Chan, Mila Nikolova, Tieyong Zeng, 2018 .

Either Fit to Data Entries or Locally to Prior: The Minimizers of Objectives with Nonsmooth Nonconvex Data Fidelity and Regularization

Mila Nikolova, M. Nikolova, 2011, SSVM.

Inversion of large-support ill-conditioned linear operators using a Markov model with a line process

Ali Mohammad-Djafari, Mila Nikolova, Jérôme Idier, 1994, Proceedings of ICASSP '94. IEEE International Conference on Acoustics, Speech and Signal Processing.

Fast Algorithms for l1 Norm/Mixed l1 and l2 Norms for Image Restoration

Mila Nikolova, Michael K. Ng, Wai-Ki Ching, 2005, ICCSA.

Regularized reconstruction of 3D high-resolution magnetic resonance images from acquisitions of anisotropically degraded resolutions

Isabelle Bloch, Élie Mousseaux, Mila Nikolova, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

Raymond H. Chan, Mila Nikolova, Chung-Wa Ho, 2005, IEEE Transactions on Image Processing.

Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration

Mila Nikolova, Michael K. Ng, Jesse L. Barlow, 2005, SIAM J. Sci. Comput..

Bilevel Image Denoising Using Gaussianity Tests

Mila Nikolova, Gabriele Steidl, Pierre Weiss, 2015, SSVM.

Fast Dejittering for Digital Video Frames

Mila Nikolova, 2009, SSVM.

Efficient Reconstruction of Piecewise Constant Images Using Nonsmooth Nonconvex Minimization

Mila Nikolova, Michael K. Ng, Wai-Ki Ching, 2008, SIAM J. Imaging Sci..

Half-quadratic regularization for MRI image restoration

Rachid Deriche, Pierre Kornprobst, Mila Nikolova, 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

Denoising of Frame Coefficients Using ℓ1 Data-Fidelity Term and Edge-Preserving Regularization

Mila Nikolova, Sylvain Durand, M. Nikolova, 2007, Multiscale Model. Simul..

Modeling anisotropic undersampling of magnetic resonance angiographies and reconstruction of a high-resolution isotropic volume using half-quadratic regularization techniques

Isabelle Bloch, Élie Mousseaux, Mila Nikolova, 2004, Signal Process..

Smoothing of outliers in image restoration by minimizing regularized objective functions with nonsmooth data-fidelity terms

Mila Nikolova, 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

Markovian reconstruction using a GNC approach

Mila Nikolova, M. Nikolova, 1999, IEEE Trans. Image Process..

Fast and Accurate Multiplicative Decomposition for Fringe Removal in Interferometric Images

Mila Nikolova, Andrés Almansa, Yann Ferrec, 2017, IEEE Transactions on Computational Imaging.

A Fast Algorithm for Exact Histogram Specification. Simple Extension to Colour Images

Mila Nikolova, M. Nikolova, 2013, SSVM.

Nonconvex Optimization for 3-Dimensional Point Source Localization Using a Rotating Point Spread Function

Mila Nikolova, Chao Wang, Sudhakar Prasad, 2019, SIAM J. Imaging Sci..

Weakly Constrained Minimization: Application to the Estimation of Images and Signals Involving Constant Regions

Mila Nikolova, M. Nikolova, 2004, Journal of Mathematical Imaging and Vision.

Guest Editorial: Scale-Space and Variational Methods

Mila Nikolova, Nicolas Papadakis, Jean-François Aujol, 2016, Journal of Mathematical Imaging and Vision.

Fast image reconstruction algorithms combining half-quadratic regularization and preconditioning

Mila Nikolova, Michael K. Ng, 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

Fast Two-Phase Image Deblurring Under Impulse Noise

Raymond H. Chan, Mila Nikolova, Jian-Feng Cai, 2009, Journal of Mathematical Imaging and Vision.

One-iteration dejittering of digital video images

Mila Nikolova, 2009, J. Vis. Commun. Image Represent..

Minimization of detail-preserving regularization functional by Newton's method with continuation

Raymond H. Chan, Mila Nikolova, Chung-Wa Ho, 2005, IEEE International Conference on Image Processing 2005.

Multiplicative Noise Cleaning via a Variational Method Involving Curvelet Coefficients

Mohamed-Jalal Fadili, Mila Nikolova, Sylvain Durand, 2009, SSVM.

Local Strong Homogeneity of a Regularized Estimator

Mila Nikolova, M. Nikolova, 2000, SIAM J. Appl. Math..

Inertial Alternating Generalized Forward–Backward Splitting for Image Colorization

Mila Nikolova, Fabien Pierre, Pauline Tan, 2019, Journal of Mathematical Imaging and Vision.

HIGH-ORDER TOTAL VARIATION REGULARIZATION APPROACH FOR AXIALLY SYMMETRIC OBJECT TOMOGRAPHY FROM A SINGLE RADIOGRAPH

Raymond H. Chan, Mila Nikolova, Xue-Cheng Tai, 2015 .

Alternating proximal gradient descent for nonconvex regularised problems with multiconvex coupling terms

Mila Nikolova, Pauline Tan, M. Nikolova, 2017 .

Inversion of Large-Support Ill-Posed Linear

Ali Mohammad-Djafari, Mila Nikolova, M. Nikolova, 1998 .

CONVERGENCE OF NEWTON'S METHOD FOR A MINIMIZATION PROBLEM IN IMPULSE NOISE REMOVAL ∗1)

Raymond H. Chan, Mila Nikolova, Chung-Wa Ho, 2004 .

Stability of image restoration by minimizing regularized objective functions

Mila Nikolova, Sylvain Durand, M. Nikolova, 2001, Proceedings IEEE Workshop on Variational and Level Set Methods in Computer Vision.

Blind identification/equalization using deterministic maximum likelihood and a partial information on the input

Mila Nikolova, Pierre Duhamel, Florence Alberge, 1999, 1999 2nd IEEE Workshop on Signal Processing Advances in Wireless Communications (Cat. No.99EX304).