Markov random fields in image segmentation
This monograph gives an introduction to the fundamentals of Markovian modeling in image
segmentation as well as a brief overview of recent advances in the field. Segmentation is …
segmentation as well as a brief overview of recent advances in the field. Segmentation is …
A hierarchical Bayesian model accounting for endmember variability and abrupt spectral changes to unmix multitemporal hyperspectral images
PA Thouvenin, N Dobigeon… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Hyperspectral unmixing is a blind source separation problem that consists in estimating the
reference spectral signatures contained in a hyperspectral image, as well as their relative …
reference spectral signatures contained in a hyperspectral image, as well as their relative …
Bayesian inference for inverse problems
A Mohammad-Djafari - AIP Conference Proceedings, 2002 - pubs.aip.org
Traditionally, the MaxEnt workshops start by a tutorial day. This paper summarizes my talk
during 2001'th workshop at John Hopkins University. The main idea in this talk is to show …
during 2001'th workshop at John Hopkins University. The main idea in this talk is to show …
A 3D Bayesian computed tomography reconstruction algorithm with Gauss-Markov-Potts prior model and its application to real data
C Chapdelaine, A Mohammad-Djafari… - Fundamenta …, 2017 - content.iospress.com
Iterative reconstruction methods in Computed Tomography (CT) are known to provide better
image quality than analytical methods but they are not still applied in many fields because of …
image quality than analytical methods but they are not still applied in many fields because of …
Local autoencoding for parameter estimation in a hidden Potts-Markov random field
A local-autoencoding (LAE) method is proposed for the parameter estimation in a Hidden
Potts-Markov random field model. Due to sampling cost, Markov chain Monte Carlo methods …
Potts-Markov random field model. Due to sampling cost, Markov chain Monte Carlo methods …
Prior parameter estimation for Ising-MRF-based sonar image segmentation by local center-encoding
A prior parameter estimation method based on local center-encoding (LCE) is proposed for
a Markov random field (MRF) model, ie the Ising case, in the task of image segmentation …
a Markov random field (MRF) model, ie the Ising case, in the task of image segmentation …
Ising field parameter estimation from incomplete and noisy data
JF Giovannelli - 2011 18th IEEE International Conference on …, 2011 - ieeexplore.ieee.org
The present paper deals with the estimation problem of the Ising field parameter and
extends a previous one [1]. It proposes an estimate from indirect observation (incomplete …
extends a previous one [1]. It proposes an estimate from indirect observation (incomplete …
Une approche bayésienne de l'inversion. Application à l'imagerie de diffraction dans les domaines micro-onde et optique
H Ayasso - 2010 - theses.hal.science
Dans ce travail, nous nous intéressons à l'imagerie de diffraction dans des configurations à
deux ou trois dimensions avec pour objectif la reconstruction d'une image (fonction …
deux ou trois dimensions avec pour objectif la reconstruction d'une image (fonction …
Potts model parameter estimation in Bayesian segmentation of piecewise constant images
RG Rosu, JF Giovannelli, A Giremus… - 2015 IEEE International …, 2015 - ieeexplore.ieee.org
The paper presents a method for estimating the parameter of a Potts model jointly with the
unknowns of an image segmentation problem. The method addresses piecewise constant …
unknowns of an image segmentation problem. The method addresses piecewise constant …
Modeling spatial and temporal variabilities in hyperspectral image unmixing
PA Thouvenin - 2017 - theses.hal.science
Acquired in hundreds of contiguous spectral bands, hyperspectral (HS) images have
received an increasing interest due to the significant spectral information they convey about …
received an increasing interest due to the significant spectral information they convey about …