Optimization Algorithms
A. Journal Articles
[35] M. Nikolova, M. Ng and C.
P. Tam, "A Fast Nonconvex
Nonsmooth Minimization Method for Image Restoration and Reconstruction", IEEE
Trans. on ImageProcessing, Vol. 19, .n 12, Dec. 2010 (pdf).
[34] Durand S., J. Fadili and
M. Nikolova, "Multiplicative
noise removal using L1 fidelity on frame coefficients", , to appear in Journal of Mathematical Imaging and Vision, 2009 (pdf).
[29] Nikolova, M. "Semi-explicit solution and
fast minimization scheme for an energy with L1-fitting and Tikhonov-like
regularization ", to appear in Journal of Mathematical
Imaging and Vision, (pdf)
Report CMLA n.2008-06.
[27] Nikolova M., M. Ng, S.
Zhang and W-K. Ching, "Efficient reconstruction of
piecewise constant images using nonsmooth nonconvex minimization", SIAM
Journal on Imaging Sciences, vol. 1, n. 1, Mar. 2008, pp. 2-25.
(pdf)
[22] Chan Tony, Selim
Esedoglu and Mila Nikolova, "Algorithms for
Finding Global Minimizers of Image Segmentation and Denoising Models, SIAM J. on
Applied Mathematics, vol. 66, n. 5, 2006, pp.1632-1648. (pdf)
[23] Nikolova M. and R.
Chan, "The equivalence of Half-Quadratic Minimization and the
Gradient Linearization Iteration'', IEEE Trans. on Image
Processing, June 2007, vol. 16, n. 6, pp. 1623-1627 (pdf).
[19] Haoying Fu H., M. Ng,
M. Nikolova and J. Barlow, "Efficient
minimization methods of mixed ℓ1 - ℓ1 and ℓ2
- ℓ1 norms for image restoration",
[17] Nikolova M. and M. Ng,
"Analysis of Half-Quadratic Minimization Methods for
Signal and Image Recovery'',
[13] Chan R., C.W. Ho and
M. Nikolova, "Convergence of
[11] Nikolova M., ''A
variational approach to remove outliers and impulse noise'', Journal of
Mathematical Imaging and Vision, vol. 20, no. 1-2, 2004, pp. 99-120. (pdf)
[10] Nikolova M., ''Weakly
constrained minimization. Application to the estimation of images and signals
involving constant regions'', Journal of Mathematical Imaging and Vision,
no. 2, vol. 21, Sep. 2004, pp. 155-175. (pdf)
[4] Nikolova M., "Markovian
reconstruction using a GNC approach'', IEEE Trans. on Image
Processing , vol. 8, no. 9, Sept. 1999, pp. 1204-1220. (pdf)
[3] Nikolova M., Idier J.
and Mohammad-Djafari A., "Inversion of large-support
ill-posed linear operators using a piecewise Gaussian MRF'', IEEE Trans. On
Image Processing, vol. 8, no. 4, pp. 571-585, April 1998. (pdf)
B. Peer Reviewed Proceedings Papers
[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)
[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.
[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)
[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.
[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.
[3] Nikolova M., ``Markovian
reconstruction in computed imaging and Fourier synthesis'', IEEE Int. Conf.
on Image Processing (ICIP), Nov. 1994, pp. 690-694.
[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),
C. Reports
Cai J-F., R. Chan and M.
Nikolova, "Fast two-stage image deblurring
under impulse noise", submitted (pdf). Report
CMLA n.2008-09
M.
Nikolova, "One-iteration dejittering of digital video images ", revised
version: (pdf).
Report CMLA n. 2008-20.
Durand S., J. Fadili and
M. Nikolova, "Multiplicative noise removal
using L1 fidelity on frame coefficients", submitted (pdf). Report CMLA
n.2008-40