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ORCIDMila Nikolova
Person information
- affiliation: ENS Cachan, Paris, France
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2020 – today
- 2020
[j43]Rémi Gribonval, Mila Nikolova:
A Characterization of Proximity Operators. J. Math. Imaging Vis. 62(6-7): 773-789 (2020)- [j42]Raymond H. Chan
, Kelvin K. Kan, Mila Nikolova, Robert J. Plemmons:
A two-stage method for spectral-spatial classification of hyperspectral images. J. Math. Imaging Vis. 62(6-7): 790-807 (2020)
2010 – 2019
- 2019
- [j41]Pauline Tan, Fabien Pierre, Mila Nikolova:
Inertial Alternating Generalized Forward-Backward Splitting for Image Colorization. J. Math. Imaging Vis. 61(5): 672-690 (2019) - [j40]Chao Wang, Raymond H. Chan, Mila Nikolova, Robert J. Plemmons, Sudhakar Prasad:
Nonconvex Optimization for 3-Dimensional Point Source Localization Using a Rotating Point Spread Function. SIAM J. Imaging Sci. 12(1): 259-286 (2019) - [j39]Mila Nikolova, Pauline Tan:
Alternating Structure-Adapted Proximal Gradient Descent for Nonconvex Nonsmooth Block-Regularized Problems. SIAM J. Optim. 29(3): 2053-2078 (2019) - [j38]Eric Barnhill, Mila Nikolova, Cemre Ariyurek, Florian Dittmann, Jürgen Braun, Ingolf Sack:
Fast Robust Dejitter and Interslice Discontinuity Removal in MRI Phase Acquisitions: Application to Magnetic Resonance Elastography. IEEE Trans. Medical Imaging 38(7): 1578-1587 (2019) - 2018
- [j37]Kelvin C. K. Chan, Raymond H. Chan, Mila Nikolova:
A Convex Model for Edge-Histogram Specification with Applications to Edge-Preserving Smoothing. Axioms 7(3): 53 (2018) - [i2]Chao Wang, Robert J. Plemmons, Sudhakar Prasad, Raymond H. Chan, Mila Nikolova:
Novel Sparse Recovery Algorithms for 3D Debris Localization using Rotating Point Spread Function Imagery. CoRR abs/1809.10541 (2018) - 2017
- [j36]Xiaohao Cai, Raymond H. Chan, Mila Nikolova, Tieyong Zeng:
A Three-Stage Approach for Segmenting Degraded Color Images: Smoothing, Lifting and Thresholding (SLaT). J. Sci. Comput. 72(3): 1313-1332 (2017) - [j35]Friederike Laus, Mila Nikolova, Johannes Persch, Gabriele Steidl:
A Nonlocal Denoising Algorithm for Manifold-Valued Images Using Second Order Statistics. SIAM J. Imaging Sci. 10(1): 416-448 (2017) - [j34]Daniel-Chen Soncco, Clara Barbanson, Mila Nikolova, Andrés Almansa, Yann Ferrec:
Fast and Accurate Multiplicative Decomposition for Fringe Removal in Interferometric Images. IEEE Trans. Computational Imaging 3(2): 187-201 (2017) - [c34]Pablo Arias, Mila Nikolova:
Below the Surface of the Non-local Bayesian Image Denoising Method. SSVM 2017: 208-220 - 2016
- [j33]Jean-François Aujol, Mila Nikolova, Nicolas Papadakis:
Guest Editorial: Scale-Space and Variational Methods. J. Math. Imaging Vis. 56(2): 173-174 (2016) - 2015
- [c33]Jérôme Fehrenbach, Mila Nikolova, Gabriele Steidl, Pierre Weiss:
Bilevel Image Denoising Using Gaussianity Tests. SSVM 2015: 117-128 - [c32]Jan Henrik Fitschen, Mila Nikolova, Fabien Pierre, Gabriele Steidl:
A Variational Model for Color Assignment. SSVM 2015: 437-448 - [e1]Jean-François Aujol, Mila Nikolova, Nicolas Papadakis:
Scale Space and Variational Methods in Computer Vision - 5th International Conference, SSVM 2015, Lège-Cap Ferret, France, May 31 - June 4, 2015, Proceedings. Lecture Notes in Computer Science 9087, Springer 2015, ISBN 978-3-319-18460-9 [contents] - [r1]Mila Nikolova:
Energy Minimization Methods. Handbook of Mathematical Methods in Imaging 2015: 157-204 - [i1]Xiaohao Cai, Raymond H. Chan, Mila Nikolova, Tieyong Zeng:
A Three-stage Approach for Segmenting Degraded Color Images: Smoothing, Lifting and Thresholding (SLaT). CoRR abs/1506.00060 (2015) - 2014
- [j32]F. Baus, Mila Nikolova, Gabriele Steidl:
Fully Smoothed ℓ 1-TV Models: Bounds for the Minimizers and Parameter Choice. J. Math. Imaging Vis. 48(2): 295-307 (2014) - [j31]Mila Nikolova, Gabriele Steidl:
Fast Hue and Range Preserving Histogram Specification: Theory and New Algorithms for Color Image Enhancement. IEEE Trans. Image Process. 23(9): 4087-4100 (2014) - [j30]Mila Nikolova, Gabriele Steidl:
Fast Ordering Algorithm for Exact Histogram Specification. IEEE Trans. Image Process. 23(12): 5274-5283 (2014) - 2013
- [j29]Mila Nikolova, You-Wei Wen, Raymond H. Chan:
Exact Histogram Specification for Digital Images Using a Variational Approach. J. Math. Imaging Vis. 46(3): 309-325 (2013) - [j28]Mila Nikolova:
Description of the Minimizers of Least Squares Regularized with 퓁0-norm. Uniqueness of the Global Minimizer. SIAM J. Imaging Sci. 6(2): 904-937 (2013) - [j27]Mila Nikolova, Michael K. Ng, Chi-Pan Tam:
On 퓁1 Data Fitting and Concave Regularization for Image Recovery. SIAM J. Sci. Comput. 35(1) (2013) - [c31]Mila Nikolova:
A Fast Algorithm for Exact Histogram Specification. Simple Extension to Colour Images. SSVM 2013: 174-185 - 2011
- [c30]Raymond H. Chan, Mila Nikolova, You-Wei Wen:
A Variational Approach for Exact Histogram Specification. SSVM 2011: 86-97 - [c29]Mila Nikolova:
Either Fit to Data Entries or Locally to Prior: The Minimizers of Objectives with Nonsmooth Nonconvex Data Fidelity and Regularization. SSVM 2011: 110-121 - [c28]Mila Nikolova:
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? SSVM 2011: 508-519 - 2010
- [j26]Jian-Feng Cai, Raymond H. Chan, Mila Nikolova:
Fast Two-Phase Image Deblurring Under Impulse Noise. J. Math. Imaging Vis. 36(1): 46-53 (2010) - [j25]Sylvain Durand, Jalal Fadili, Mila Nikolova:
Multiplicative Noise Removal Using L1 Fidelity on Frame Coefficients. J. Math. Imaging Vis. 36(3): 201-226 (2010) - [j24]Mila Nikolova, Michael K. Ng, Chi-Pan Tam:
Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction. IEEE Trans. Image Process. 19(12): 3073-3088 (2010)
2000 – 2009
- 2009
- [j23]Mila Nikolova:
Semi-explicit Solution and Fast Minimization Scheme for an Energy with l1-Fitting and Tikhonov-Like Regularization. J. Math. Imaging Vis. 34(1): 32-47 (2009) - [j22]Mila Nikolova:
One-iteration dejittering of digital video images. J. Vis. Commun. Image Represent. 20(4): 254-274 (2009) - [c27]Sylvain Durand, Jalal Fadili, Mila Nikolova:
Multiplicative Noise Cleaning via a Variational Method Involving Curvelet Coefficients. SSVM 2009: 282-294 - [c26]Mila Nikolova:
Fast Dejittering for Digital Video Frames. SSVM 2009: 439-451 - 2008
- [j21]Mila Nikolova, Michael K. Ng, Shuqin Zhang, Wai-Ki Ching:
Efficient Reconstruction of Piecewise Constant Images Using Nonsmooth Nonconvex Minimization. SIAM J. Imaging Sci. 1(1): 2-25 (2008) - 2007
- [j20]Sylvain Durand, Mila Nikolova:
Denoising of Frame Coefficients Using ℓ1 Data-Fidelity Term and Edge-Preserving Regularization. Multiscale Model. Simul. 6(2): 547-576 (2007) - [j19]Mila Nikolova, Raymond H. Chan:
The Equivalence of Half-Quadratic Minimization and the Gradient Linearization Iteration. IEEE Trans. Image Process. 16(6): 1623-1627 (2007) - [c25]Mila Nikolova:
Counter-Examples for Bayesian MAP Restoration. SSVM 2007: 140-152 - [c24]Mila Nikolova:
Bounds on the Minimizers of (nonconvex) Regularized Least-Squares. SSVM 2007: 496-507 - 2006
- [j18]Tony F. Chan, Selim Esedoglu, Mila Nikolova:
Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models. SIAM J. Appl. Math. 66(5): 1632-1648 (2006) - [j17]Haoying Fu, Michael K. Ng, Mila Nikolova, Jesse L. Barlow:
Efficient Minimization Methods of Mixed l2-l1 and l1-l1 Norms for Image Restoration. SIAM J. Sci. Comput. 27(6): 1881-1902 (2006) - [j16]Florence Alberge, Mila Nikolova, Pierre Duhamel:
Blind identification/equalization using deterministic maximum likelihood and a partial prior on the input. IEEE Trans. Signal Process. 54(2): 724-737 (2006) - 2005
- [j15]Mila Nikolova:
Analysis of the Recovery of Edges in Images and Signals by Minimizing Nonconvex Regularized Least-Squares. Multiscale Model. Simul. 4(3): 960-991 (2005) - [j14]Mila Nikolova, Michael K. Ng:
Analysis of Half-Quadratic Minimization Methods for Signal and Image Recovery. SIAM J. Sci. Comput. 27(3): 937-966 (2005) - [j13]Raymond H. Chan, Chung-Wa Ho, Mila Nikolova:
Salt-and-Pepper Noise Removal by Median-Type Noise Detectors and Detail-Preserving Regularization. IEEE Trans. Image Process. 14(10): 1479-1485 (2005) - [c23]Haoying Fu, Michael K. Ng, Mila Nikolova, Jesse L. Barlow, Wai-Ki Ching:
Fast Algorithms for l1 Norm/Mixed l1 and l2 Norms for Image Restoration. ICCSA (4) 2005: 843-851 - [c22]Tony F. Chan, Selim Esedoglu, Mila Nikolova:
Finding the global minimum for binary image restoration. ICIP (1) 2005: 121-124 - [c21]Raymond H. Chan, Chung-Wa Ho, Chun-Yee Leung, Mila Nikolova:
Minimization of detail-preserving regularization functional by Newton's method with continuation. ICIP (1) 2005: 125-128 - [c20]Mila Nikolova:
Restoration of edges by minimizing non-convex cost-functions. ICIP (2) 2005: 786-789 - 2004
- [j12]Ronald R. Peeters, Pierre Kornprobst, Mila Nikolova, Stefan Sunaert, Thierry Viéville, Grégoire Malandain, Rachid Deriche, Olivier D. Faugeras, Michael K. P. Ng, Paul Van Hecke:
The use of super-resolution techniques to reduce slice thickness in functional MRI. Int. J. Imaging Syst. Technol. 14(3): 131-138 (2004) - [j11]Mila Nikolova:
A Variational Approach to Remove Outliers and Impulse Noise. J. Math. Imaging Vis. 20(1-2): 99-120 (2004) - [j10]Mila Nikolova:
Weakly Constrained Minimization: Application to the Estimation of Images and Signals Involving Constant Regions. J. Math. Imaging Vis. 21(2): 155-175 (2004) - [j9]Elodie Roullot, Alain Herment, Isabelle Bloch, Alain De Cesare, Mila Nikolova, Élie Mousseaux:
Modeling anisotropic undersampling of magnetic resonance angiographies and reconstruction of a high-resolution isotropic volume using half-quadratic regularization techniques. Signal Process. 84(4): 743-762 (2004) - [j8]Raymond H. Chan, Chen Hu, Mila Nikolova:
An iterative procedure for removing random-valued impulse noise. IEEE Signal Process. Lett. 11(12): 921-924 (2004) - 2003
- [c19]Mila Nikolova:
Minimization of Cost-Functions with Non-smooth Data-Fidelity Terms to Clean Impulsive Noise. EMMCVPR 2003: 391-406 - [c18]Rachid Deriche, Pierre Kornprobst, Mila Nikolova:
Half-quadratic regularization for MRI image restoration. ICASSP (6) 2003: 585-588 - [c17]Mila Nikolova:
Efficient removing of impulsive noise based on an l1-l2 cost-function. ICIP (1) 2003: 121-124 - [c16]Pierre Kornprobst, Ronald R. Peeters, Mila Nikolova, Rachid Deriche, Michael Kwok-Po Ng, Paul Van Hecke:
A Superresolution Framework for fMRI Sequences and Its Impact on Resulting Activation Maps. MICCAI (2) 2003: 117-125 - 2002
- [j7]Mila Nikolova:
Minimizers of Cost-Functions Involving Nonsmooth Data-Fidelity Terms. Application to the Processing of Outliers. SIAM J. Numer. Anal. 40(3): 965-994 (2002) - [j6]Florence Alberge, Pierre Duhamel, Mila Nikolova:
Adaptive solution for blind identification/equalization using deterministic maximum likelihood. IEEE Trans. Signal Process. 50(4): 923-936 (2002) - [c15]Michael K. Ng, Mila Nikolova:
Comparison of the main forms of half-quadratic regularization. ICIP (1) 2002: 349-352 - 2001
- [c14]Mila Nikolova:
Smoothing of outliers in image restoration by minimizing regularized objective functions with nonsmooth data-fidelity terms. ICIP (1) 2001: 233-236 - [c13]Mila Nikolova, Michael K. Ng:
Fast image reconstruction algorithms combining half-quadratic regularization and preconditioning. ICIP (1) 2001: 277-280 - 2000
- [j5]Mila Nikolova:
Local Strong Homogeneity of a Regularized Estimator. SIAM J. Appl. Math. 61(2): 633-658 (2000) - [j4]Mila Nikolova:
Thresholding implied by truncated quadratic regularization. IEEE Trans. Signal Process. 48(12): 3437-3450 (2000) - [c12]Florence Alberge, Pierre Duhamel, Mila Nikolova:
Low cost adaptive algorithm for blind channel identification and symbol estimation. EUSIPCO 2000: 1-4 - [c11]Mila Nikolova:
Assumed and effective priors in Bayesian MAP estimation. ICASSP 2000: 305-308 - [c10]Florence Alberge, Mila Nikolova, Pierre Duhamel:
Adaptive deterministic maximum likelihood using a quasi-discrete prior. ICASSP 2000: 2745-2748 - [c9]Elodie Roullot, Alain Herment, Isabelle Bloch, Mila Nikolova, Élie Mousseaux:
Regularized Reconstruction of 3D High-Resolution Magnetic Resonance Images from Acquisitions of Anisotropically Degraded Resolutions. ICPR 2000: 3350-3353
1990 – 1999
- 1999
- [j3]Mila Nikolova:
Markovian reconstruction using a GNC approach. IEEE Trans. Image Process. 8(9): 1204-1220 (1999) - [c8]Mila Nikolova:
Locally Homogeneous Images As Minimizers of Objective Functions. ICIP (2) 1999: 11-15 - [c7]Mila Nikolova:
Error Indicators for Adaptive Refinement of Singularly Perturbed Convection-Diffusion Problems. LSSC 1999: 232-240 - 1998
- [j2]Mila Nikolova, Jérôme Idier, Ali Mohammad-Djafari:
Inversion of large-support ill-posed linear operators using a piecewise Gaussian MRF. IEEE Trans. Image Process. 7(4): 571-585 (1998) - [c6]Mila Nikolova:
Reconstruction of locally homogeneous images. EUSIPCO 1998: 1-4 - [c5]Mila Nikolova:
Estimation of Binary Images by Minimizing Convex Criteria. ICIP (2) 1998: 108-112 - 1996
- [j1]Mila Nikolova, Ali Mohammad-Djafari:
Eddy current tomography using a binary Markov model. Signal Process. 49(2): 119-132 (1996) - [c4]Mila Nikolova:
Regularisation functions and estimators. ICIP (2) 1996: 457-460 - 1995
- [c3]Mila Nikolova:
Parameter selection for a Markovian signal reconstruction with edge detection. ICASSP 1995: 1804-1807 - 1994
- [c2]Mila Nikolova, Ali Mohammad-Djafari, Jérôme Idier:
Inversion of large-support ill-conditioned linear operators using a Markov model with a line process. ICASSP (5) 1994: 357-360 - [c1]Mila Nikolova:
Markovian Reconstruction in Computed Imaging and Fourier Synthesis. ICIP (2) 1994: 690-694
Coauthor Index
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