◄homepage◄ Peer
Reviewed Proceedings Papers
[44] M. Nikolova, "Either fit to data entries
or to locally to prior: the minimizers of energies with nonsmooth
nonconvex data fidelity and regularization ", Scale Space and Variational Methods in Computer Vision, June 2011.
[43] M. 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?", Scale Space and Variational Methods in Computer Vision, June 2011.
[42] R. Chan, M. Nikolova
and Y.-W. Wen, "A variational
approach for exact histogram specification ", Scale Space and Variational
Methods in Computer Vision, June 2011.
[41] Nikolova M., "Fast dejittering for digital video images ", Scale Space and Variational Methods in Computer Vision, Eds. X.-C. Tai, K. Morken, M. Lysaker, K.-A. Lie, LNCS 5567, Springer, pp. 439-451, 2009. (pdf)
[40] Durand S., J. Fadili and M. Nikolova, "Multiplicative noise clearing via a variational method involving curvelet
coefficients ", Scale Space and Variational
Methods in Computer Vision, Eds. X.-C. Tai, K. Morken, M. Lysaker, K.-A. Lie,
LNCS 5567, Springer, pp. 282-294,, 2009. (pdf)
[39] Malgouyres, F. and M. Nikolova, "Average
performance of the sparsest approximation in a dictionary ", Int. Workshop
SPARS’09, April 2009. (pdf)
[38] Nikolova M., "Bounds on the minimizers of (nonconvex)
regularized least-squares", Scale Space and Variational Methods in Computer Vision, Springer –
Lecture notes in Computer science LNCS 4485, ed. F. Sgallary,
A. Murli, N. Paragios,
2007, pp. 496-507.
[37] Nikolova M.,
"Counter-examples for Bayesian MAP restoration", Scale Space and Variational Methods in Computer Vision, Springer
– Lecture notes in Computer science LNCS 4485, ed. F. Sgallary,
A. Murli, N. Paragios,
2007, pp. 140-152.
[36] Nikolova M., "Restoration of
edges by minimizing non-convex cost-functions", IEEE Int. Conf. on Image
Processing (ICIP), vol. II, pp. 786-789, Sept. 2005.
[35] Chan T., S. Esedoglu and M. Nikolova, "Finding the
Global Minimum for Binary Image Restoration", IEEE Int. Conf. on Image
Processing (ICIP), vol. I, pp. 121-124, Sept. 2005.
[34] Chan, R., C. Ho, C.W.
Leung and M. Nikolova, "Minimization of
detail-preserving regularization functional by
[33] Fu H., M. Ng, Mila Nikolova, J. L. Barlow, W.-K. Ching, "Fast
algorithms for ℓ1 norm/mixed ℓ1 and ℓ2
norms for image restoration”. ICCSA, vol. 4, pp. 843-851,
2005.
[32] Durand S. and M. Nikolova, "Restoration of wavelet coefficients by
minimizing a specially designed objective function'', IEEE Int. Conf. on
Computer Vision / Workshop on Variational and
Level-Set Methods, vol. 2, pp. 145-152, Oct. 2003. (pdf)
[31] Nikolova
M.,
``Minimization of cost-functions with non-smooth data-fidelity terms to clean
impulsive noise'', Int. workshop on Energy Minimization Methods in
Computer Vision and Pattern Recognition, Lecture Notes in Computer
Science, Springer-Verlag, pp. 391-406, 2003.
[30] Kornprobst, P., R. Peeters, M. Nikolova, R. Deriche, M. Ng and P. Van Hecke. ``A super-resolution
framework for fMRI
sequences and its impact on resulting activation maps'', Medical Image
Computing and Computer-Assisted Intervention (MICCAI), LNCS 2879, pp.
117-127, 2003.
[29] Nikolova M., ``Efficient removing
of impulsive noise based on an ℓ1-ℓ2
cost-function'', IEEE Int. Conf. on Image Processing (ICIP), vol. 1, pp. 14-17,
Sep. 2003. (pdf)
[28] Deriche, R., P. Kornprobst, M. Nikolova and
Michael Ng. ``Half-quadratic regularization for MRI image restoration'', IEEE Int. Conf.
on Acoustics, Speech and Signal Processing (ICASSP), vol. VI, pp. 585-588,
2003.
[27] Zinger S., M. Nikolova, M. Roux and H. Maitre, ``Rééchantillonnage de données
3D laser aéroporté en milieu urbain'', Congrès
Vision par Ordinateeur ORASIS, pp. 75-82, Mai
2003.
[26] Nikolova M. and M. Ng, ``Comparison of the
main forms of half-quadratic regularization'', IEEE Int. Conf. on Image Processing(ICIP), vol. 1, pp. 349-352, Oct. 2002.
[25] Zinger S., M. Nikolova, M. Roux and H. Maitre, ``3D resampling for airborne lase data
of urban areas'', Proceedings of ISPRS, vol. XXXIV, n. 3A, pp. 418-423, 2002.
[24] Nikolova M., ``Image restoration by
minimizing objective functions with non-smooth data-fidelity terms'', IEEE Int. Conf.
on Computer Vision / Workshop on Variational and
Level-Set Methods, pp. 11-18, Jul. 2001.
[23] Durand S. and M. Nikolova, ``Stability of image restoration by minimizing
regularized objective functions'', IEEE Int. Conf. on Computer Vision / Workshop on Variational and Level-Set Methods, pp. 73-80, Jul.
2001.
[22] Nikolova M., ``Smoothing of
outliers in image restoration by minimizing regularized objective functions
with non-smooth data-fidelity terms'', IEEE Int. Conf. on Image
Processing (ICIP), vol. 1, pp. 233-236n Oct. 2001.
[21] Nikolova M. and M. Ng, ``Fast image
reconstruction algorithms combining half-quadratic regularization and
preconditioning'', IEEE Int. Conf. on Image Processing, vol. 1, pp. 277-280, Oct.
2001.
[20] Nikolova M. and A. Hero III, ``Segmentation of a
road from a vehicle-mounted imaging radar and accuracy of the estimation'', Proc. of IEEE
Intelligent Vehicles Symposium, pp. 284-289, Oct. 2000.
[19] Alberge F., P. Duhamel and M. Nikolova, ``Low cost adaptive
algorithm for blind channel identification and symbol estimation'', EUSIPCO (
[18] Roullot E., A. Herment, I. Bloch, M. Nikolova
and E. Mousseaux, ``Regularized reconstruction of
3D high-resolution magnetic resonance images from acquisitions of anisotropically degraded resolutions'', 15th
Int. Conf. on Pattern Recognition, vol. 3, pp. 346-349, 2000.
[17] Roullot E., A. Herment, I. Bloch, M. Nikolova and E. Mousseaux, ``Reconstruction regularise
d’images de resonance magnétique 3D de haute resolution à partir d’acquisitions anisotropes'', RFIA (Paris, France), vol. II, pp. 59-68, 2000.
[16] Nikolova M., ``Assumed and effective
priors in Bayesian MAP estimation'', IEEE Int. Conf. on
Acoustics, Speech and Signal Processing(ICASSP),
Jun. 2000.
[15] Alberge F., M. Nikolova and P. Duhamel, ``Adaptive
Deterministic Maximum Likelihood using a quasi-discrete prior'', IEEE Int. Conf.
on Acoustics, Speech and Signal Processing (ICASSP), Jun. 2000.
[14] Nikolova
M.,
``Locally homogeneous images as minimizers of an
objective function'', IEEE Int. Conf. on Image Processing, Oct.
1999, vol.2, pp. 11-15, invited paper.
[13] Nikolova M., ``Local continuity and
thresholding using truncated quadratic
regularization'', IEEE Workshop on Higher Order Statistics, pp. 277-280,
June 1999.
[12] Nikolova M. and A. Hero III, ``Noisy word
recognition using denoising and moment matrix discriminants'', IEEE Workshop on Higher
Order Statistics, June 1999.
[11] Alberge F., Duhamel
P. and M. Nikolova, ``Blind identification /
equalization using deterministic maximum likelihood and a partial information
on the input'', IEEE Workshop on Sig. Proc. Advances in Wireless Communications,
May 1999.
[10] Nikolova M., ``Estimation of
binary images using convex criteria'', Proc. of IEEE Int. Conf. on
Image Processing (ICIP), Oct. 1998. (pdf)
[9] Nikolova M. and A. Hero III, ``Segmentation of
road edges from a vehicle-mounted imaging radar'', Proc. of IEEE Stat.
Signal and Array Proc., Sept. 1998. (pdf)
[8] Nikolova M., ``Estimation of
signals containing strongly homogeneous zones'', Proc. of IEEE Stat. Signal
and Array Proc., Sept. 1998.
[7] Nikolova M., ``Reconstruction of
locally homogeneous images'', European Signal Proc. Conf., Sept. 1998.
[6] Nikolova M., ``Regularisation
functions and estimators'', Proc. of IEEE Int. Conf. on Image Processing
(ICIP), Nov. 1996, pp. 457-460.
[5] Nikolova M., ``Non convex
regularization and the recovery of edges'', Proc. IEEE Workshop on Nonlinear
Signal and Image
[4] Nikolova M., ``Parameter selection
for a Markovian signal reconstruction with edge
detection'', Proc. IEEE Int. Conf. Acoust. Speech Signal Process.,
[3] Nikolova M., ``Markovian
reconstruction in computed imaging and Fourier synthesis'', IEEE Int. Conf.
on Image Processing (ICIP), Nov. 1994, pp. 690-694.
[2] Nikolova M. and A. Mohammad-Djafari, ``Discontinuity reconstruction from linear attenuating
operators using the weak-string model'', European Signal Proc. Conf.
(EUSIPCO), Sept. 1994, pp. 1062-1065. (ps)
[1] Nikolova M., A. Mohammad-Djafari and J. Idier, ``Inversion of
large-support ill-conditionned linear operators using
a Markov model with a line process'', Proc. IEEE
Int. . Acoust. Speech Signal Process. (ICASSP),