We present a Markov random field (MRF) model for digital images capable
of representing anisotropic textures with arbitrary orientations. The
discrete Hamiltonian is obtained through finite difference
discretization of a continuous elliptic operator on R-2, together with a
polynomial perturbation.
We present the solution of a non-linear system of algebraic equations
that estimates the orientation angle and the elliptic operator
parameters in terms of the estimated discrete Hamiltonian parameters.
We perform experiments of simulation and retrieval of parameters using,
respectively, the Gibbs sampler algorithm and the variational estimators
for MRF. We use also the estimation algorithm to identify relative
rotation of digital images of the same realistic picture scanned at
various different orientations.
%0 Journal Article
%1 WOS:A1997XK42300004
%A Almeida, MP
%C SPUIBOULEVARD 50, PO BOX 17, 3300 AA DORDRECHT, NETHERLANDS
%D 1997
%I KLUWER ACADEMIC PUBL
%J JOURNAL OF MATHEMATICAL IMAGING AND VISION
%K Markov anisotropy; estimation} field; parameter random {texture;
%N 3
%P 241-251
%R 10.1023/A:1008278411855
%T Anisotropic textures with arbitrary orientation
%V 7
%X We present a Markov random field (MRF) model for digital images capable
of representing anisotropic textures with arbitrary orientations. The
discrete Hamiltonian is obtained through finite difference
discretization of a continuous elliptic operator on R-2, together with a
polynomial perturbation.
We present the solution of a non-linear system of algebraic equations
that estimates the orientation angle and the elliptic operator
parameters in terms of the estimated discrete Hamiltonian parameters.
We perform experiments of simulation and retrieval of parameters using,
respectively, the Gibbs sampler algorithm and the variational estimators
for MRF. We use also the estimation algorithm to identify relative
rotation of digital images of the same realistic picture scanned at
various different orientations.
@article{WOS:A1997XK42300004,
abstract = {We present a Markov random field (MRF) model for digital images capable
of representing anisotropic textures with arbitrary orientations. The
discrete Hamiltonian is obtained through finite difference
discretization of a continuous elliptic operator on R-2, together with a
polynomial perturbation.
We present the solution of a non-linear system of algebraic equations
that estimates the orientation angle and the elliptic operator
parameters in terms of the estimated discrete Hamiltonian parameters.
We perform experiments of simulation and retrieval of parameters using,
respectively, the Gibbs sampler algorithm and the variational estimators
for MRF. We use also the estimation algorithm to identify relative
rotation of digital images of the same realistic picture scanned at
various different orientations.},
added-at = {2022-05-23T20:00:14.000+0200},
address = {SPUIBOULEVARD 50, PO BOX 17, 3300 AA DORDRECHT, NETHERLANDS},
author = {Almeida, MP},
biburl = {https://www.bibsonomy.org/bibtex/2b879f157d50bf4fbbf7e396bb207296e/ppgfis_ufc_br},
doi = {10.1023/A:1008278411855},
interhash = {dd14e0df0e55e29200991b27b7234b7a},
intrahash = {b879f157d50bf4fbbf7e396bb207296e},
issn = {0924-9907},
journal = {JOURNAL OF MATHEMATICAL IMAGING AND VISION},
keywords = {Markov anisotropy; estimation} field; parameter random {texture;},
number = 3,
pages = {241-251},
publisher = {KLUWER ACADEMIC PUBL},
pubstate = {published},
timestamp = {2022-05-23T20:00:14.000+0200},
title = {Anisotropic textures with arbitrary orientation},
tppubtype = {article},
volume = 7,
year = 1997
}