Multisensor triplet Markov chains and theory of evidence
International Journal of Approximate ReasoningPublished 14 June 2006
Wojciech Pieczynski
Citations77
SJR quartileQ2
SJR score0.73
SNIP1.18
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Different possibilities of using the Dempster-Shafer fusion in the context of different multisensor Markov models are presented and it is shown that the posterior distribution remains calculable in different general situations.
Abstract
International audience
Keywords
Computer Science
IEEE Transactions on Pattern Analysis and Machine IntelligenceStochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
17,980 Citations1984Stuart Geman, Donald Geman
The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
Proceedings of the IEEEThe viterbi algorithm
5,595 Citations1973G. David Forney
This paper gives a tutorial exposition of the Viterbi algorithm and of how it is implemented and analyzed, and increasing use of the algorithm in a widening variety of areas is foreseen.
TechnometricsThe EM Algorithm and Extensions
5,108 Citations1998Debashis Kushary, Geoffrey J. McLachlan +1 more
Artificial IntelligenceThe transferable belief model
2,165 Citations1994Philippe Smets, Robert Kennes
IEEE Signal Processing MagazineHyperspectral image data analysis
1,102 Citations2002D. A. Landgrebe
The article includes an example of an image space representation, using three bands to simulate a color IR photograph of an airborne hyperspectral data set over the Washington, DC, mall.
Institutional Research Information System (Università degli Studi di Trento)Advances in the Dempster-Shafer theory of evidence
1,021 Citations1994Ronald R. Yager, Janusz Kacprzyk +1 more
The Dempster-Shafer Theory of Evidence is applied as a guide for the management of uncertainty in knowledge-based systems.
International Journal of Approximate ReasoningBelief functions: The disjunctive rule of combination and the generalized Bayesian theorem
648 Citations1993Philippe Smets
The Bayes’ theorem is generalized within the transferable belief model framework and the DRC and GBT and their uses for belief propagation in directed belief networks are analysed.
Computational biologyHidden Markov Models for Bioinformatics
230 Citations2001Timo Koski
Prerequisites in probability calculus and the Baum - Welch Learning Algorithm and Hidden Markov Models: an Overview are presented.
Pattern Recognition LettersSome aspects of Dempster-Shafer evidence theory for classification of multi-modality medical images taking partial volume effect into account
230 Citations1996Isabelle Bloch
Examples are provided to show Dempster-Shafer evidence theory's ability to take into account a large variety of situations, which actually often occur and are not always well managed by classical approaches.
IEEE Transactions on Pattern Analysis and Machine IntelligenceOff-line handwritten word recognition using a hidden Markov model type stochastic network
226 Citations1994Mou-Yen Chen, Amlan Kundu +1 more
A complete scheme for totally unconstrained handwritten word recognition based on a single contextual hidden Markov model type stochastic network is presented, which includes a morphology and heuristics based segmentation algorithm, a training algorithm that can adapt itself with the changing dictionary.
Computers & Mathematics with ApplicationsImage analysis, random fields and Markov Chain Monte Carlo methods: A mathematical introduction
223 Citations2004
Evidence Theory and Its Applications
222 Citations1991Jiwen Guan, D. A. Bell
Coarsening mappings and evidential functions, partitioning a frame of discernment, and compositions of coarsening operations and orthogonal sum.
IEEE Transactions on Pattern Analysis and Machine IntelligenceAutomatic segmentation of acoustic musical signals using hidden Markov models
198 Citations1999C. Raphael
This paper addresses an important step toward the goal of automatic musical accompaniment-the segmentation problem, given a score to a piece of monophonic music and a sampled recording of a performance of that score, by designing a hidden Markov model for segmentation.
Pattern RecognitionAnalysis of evidence-theoretic decision rules for pattern classification
174 Citations1997Thierry Denœux
Different strategies that can be applied in this context to reach a decision (e.g. assignment to a class or rejection), provided the possible consequences of each action can be quantified are examined.
International Journal of Approximate ReasoningReasoning with imprecise belief structures
167 Citations1999Thierry Denœux
This paper extends the theory of belief functions by introducing new concepts and techniques, allowing to model the situation in which the beliefs held by a rational agent may only be expressed (or are only known) with some imprecision.
IEEE Transactions on Medical ImagingBrain tissue classification of magnetic resonance images using partial volume modeling
147 Citations2000Su Ruan, C. Jaggi +3 more
Presents a fully automatic three-dimensional classification of brain tissues for Magnetic Resonance (MR) images using Markov random field (MRF) models and the multifractal dimension, describing the topology of the brain, is added to the MRFs to improve discrimination of the mixclasses.
IEEE Transactions on Image ProcessingEfficient detection in hyperspectral imagery
137 Citations2001S.M. Schweizer, José M. F. Moura
A maximum likelihood detector that successfully confronts both problems: rather than ignoring the spatial and spectral correlations, this detector exploits them to its advantage; and it is computationally expedient, its complexity increasing only linearly with the number of spectral bands available.
IEEE Transactions on Pattern Analysis and Machine IntelligencePairwise markov chains
133 Citations2003Wojciech Pieczynski
An original method of parameter estimation, which generalizes the classical iterative conditional estimation (ICE) valid for a classical hidden Markov chain model, and whose extension to possibly non-Gaussian and correlated noise is briefly treated.
IEEE Transactions on Geoscience and Remote SensingAnalysis of remotely sensed data: the formative decades and the future
121 Citations2005John A. Richards
The treatment concludes by examining the requirements of an operational multisource thematic mapping process, in which it is suggested that the most practical approach is to analyze each data type separately, by techniques optimized to that data's characteristics, and then to fuse at the label level.
Water Resources ResearchModeling long‐term persistence in hydroclimatic time series using a hidden state Markov Model
107 Citations2000Mark Thyer, George Kuczera
IEEE Transactions on Signal ProcessingSignal and Image Segmentation Using Pairwise Markov Chains
102 Citations2004Stéphane Derrode, Wojciech Pieczynski
The recent pairwise Markov chain model is applied to the unsupervised restoration of hidden data to show the advantages of the pairwise Markov chain model with respect to the classical hidden Markov chain one for supervised and unsupervised restorations.
IEEE Transactions on Geoscience and Remote SensingMultisensor image segmentation using Dempster-Shafer fusion in Markov fields context
98 Citations2001A. Bendjebbour, Yves Delignon +3 more
An original variant of generalized mixture estimation, making possible the unsupervised evidential fusion in a Markovian context, is described and is applied to the unsupervised segmentation of real radar and SPOT images showing the relevance of the proposed models and corresponding segmentation methods in real situations.
IEEE Transactions on Geoscience and Remote SensingA first step toward automatic interpretation of SAR images using evidential fusion of several structure detectors
88 Citations1999Florence Tupin, Isabelle Bloch +1 more
A method aiming to characterize the spatial organization of the main cartographic elements of a synthetic aperture radar (SAR) image and thus giving an almost automatic interpretation of the scene is proposed.
Remote Sensing of EnvironmentAutomatic change detection by evidential fusion of change indices
83 Citations2004Sylvie Le Hégarat‐Mascle, R. Seltz
The proposed algorithm is applied to forest fire damage evaluation based on three popular change indices: normalized difference values, texture evolution, and mutual information (MI) and finds that change index fusion is effective at reducing both false alarm and misdetection levels.
Nucleic Acids ResearchMining Bacillus subtilis chromosome heterogeneities using hidden Markov models
80 Citations2002Pierre Nicolas
A new statistical segmentation method is presented on the Bacillus subtilis chromosome sequence, which enables one to segment the DNA sequence according to its local composition using a hidden Markov model based on the expectation-maximization algorithm.
Pattern RecognitionINTRODUCTION OF NEIGHBORHOOD INFORMATION IN EVIDENCE THEORY AND APPLICATION TO DATA FUSION OF RADAR AND OPTICAL IMAGES WITH PARTIAL CLOUD COVER
80 Citations1998Sylvie Le Hégarat‐Mascle, Isabelle Bloch +1 more
Two ways of introducing spatial information in Dempster–Shafer evidence theory are examined: in the definition of the monosource mass functions, and, during data fusion.
IEEE Transactions on Signal ProcessingDouble Markov random fields and Bayesian image segmentation
79 Citations2002D.E. Melas, Simon Wilson
A class of such models (the double Markov random field) for images composed of several textures is described, which is considered to be the natural hierarchical model for such a task.
IEEE Transactions on Geoscience and Remote SensingAn adaptive fuzzy evidential nearest neighbor formulation for classifying remote sensing images
65 Citations2005Hongwei Zhu, Otman Basir
The paper presents a novel adaptive fuzzy evidential nearest neighbor formulation for classifying remotely sensed images that combines the generalized fuzzy version of the Dempster-Shafer evidence theory and the K-nearest neighbor algorithm to achieve the adaptive capability during the classification process.
Ecological ModellingStudying crop sequences with CarrotAge, a HMM-based data mining software
64 Citations2005Florence Le Ber, Marc Benoît +3 more
A knowledge discovery system based on high-order hidden Markov models for analyzing spatio-temporal data bases and can be used to find out and study crop sequences in large territories, that is a main question for agricultural and environmental research.
Pairwise Markov random fields and segmentation of textured images
59 Citations2000Wojciech Pieczynski, Abdel-Nasser Tebbache
Computer Vision and Image UnderstandingHierarchical Markovian segmentation of multispectral images for the reconstruction of water depth maps
56 Citations2003J.-N. Provost, C. Collet +3 more
The designed segmentation method can be extended to images for which it is required to segment a region of interest using an unsupervised approach, and is applied to Satellite Pour l'Observation de la Terre remote multispectral images.
IEEE Transactions on Signal ProcessingUnsupervised restoration of hidden nonstationary Markov chains using evidential priors
55 Citations2005Pierre Lanchantin, Wojciech Pieczynski
This paper shows, via simulations, that the classical restoration results can be improved by the use of the theory of evidence and Dempster-Shafer fusion, and is performed in an entirely unsupervised way using an original parameter estimation method.
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE<title>Statistical image segmentation using triplet Markov fields</title>
55 Citations2003Wojciech Pieczynski, Dalila Benboudjema +1 more
The PMF is generalized to Triplet Markov Fields (TMF) by adding a third random field U=(Us) and considering the Markovianity of (X, U, Y) and it is shown that in TMF X is still estimable from Y by Bayesian methods.
IEEE Transactions on Instrumentation and MeasurementMultisource classification using ICM and Dempster-Shafer theory
52 Citations2002Samuel Foucher, Mickaël Germain +2 more
It is proposed to use evidential reasoning in order to relax Bayesian decisions given by a Markovian classification algorithm, the multiscale iterated conditional mode (ICM) algorithm, to fuse decisions in a local spatial neighborhood which is further extended to be multisource.
Computer Vision and Image UnderstandingUnsupervised image segmentation using triplet Markov fields
51 Citations2005Dalila Benboudjema, Wojciech Pieczynski
The aim of this paper is to propose a new parameter estimation method adapted to TMF, and to study the corresponding unsupervised image segmentation methods.
International Review of Financial AnalysisA hidden Markov chain model for the term structure of bond credit risk spreads
50 Citations2002Lyn C. Thomas, David E. Allen +1 more
IEEE Transactions on Signal ProcessingAn equivalence of the EM and ICE algorithm for exponential family
49 Citations1997Jean‐François Delmas
In case the probability density function belongs to the exponential family, the EM algorithm is one particular case of the ICE algorithm, which was formally introduced in the field of statistical segmentation of images.
Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE<title>Triplet Markov chains in hidden signal restoration</title>
48 Citations2003Wojciech Pieczynski, Cedric Hulard +1 more
This paper presents a short simulation study of image segmentation, where the bi- dimensional set of pixels is transformed into a mono-dimensional set via a Hilbert-Peano scan, that shows that using TMC can improve the results obtained with HMC.
International Journal of Approximate ReasoningTheory of evidence and non-exhaustive frames of discernment: Plausibilities correction methods
41 Citations1998Fabrice Janez, Alain Appriou
Methods mainly based on a technique called “deconditioning” that allow the combination of such sources and that are developed in the theory of evidence's framework are presented, a priori the most appropriate for this problem.
IEEE Transactions on Image ProcessingLandcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery
40 Citations2005Arnab Sarkar, Amit Banerjee +5 more
The role of feature-level fusion using the Dempster-Shafer rule and that of data- level fusion in the MRF context is studied and an optimally segmented image is obtained to obtain landcover classification.
Signal ProcessingUnsupervised signal restoration using hidden Markov chains with copulas
40 Citations2005Nicolas Brunel, Wojciech Pieczynski
The aim is to take into account the hidden signal and complex relationships between the noises which can be from different parametric models, non-independent, and of class-varying nature, and apply resulting unsupervised restoration methods in variety of situations.
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)Multisensor Fusion in the Frame of Evidence Theory for Landmines Detection
34 Citations2004Stéphane Perrin, Emmanuel Duflos +2 more
First simulations on a limited set of data show that an improvement in detection and false alarms rejection, for the GPR as a standalone sensor, could be obtained, and a comparison is made between the two cases: with or without multisensor fusion.
Image and Vision ComputingMultisensor triplet Markov fields and theory of evidence
31 Citations2005Wojciech Pieczynski, Dalila Benboudjema
It is shown that TMF allow one to perform the Dempster-Shafer fusion in different general situations, possibly involving several sensors, as a consequence, Bayesian segmentation strategies remain applicable.
An evidential Markovian model for data fusion and unsupervised image classification
28 Citations2000Laurent Fouque, Alain Appriou +1 more
Two models for merging available information are presented, a non contextual and a vectorial model which is defined by using a Markov chain structure to represent a priori knowledge associated to labelling image, and the Markovian property is preserved after fusion, which enables us to apply standard classification algorithms.
IEEE Transactions on Image ProcessingEstimation of generalized mixture in the case of correlated sensors
26 Citations2000Wojciech Pieczynski, J. Bouvrais +1 more
An extension of a previous method of generalized mixture estimation to the correlated sensors case is proposed, valid in the independent data case, as well as in the hidden Markov chain or field model case, with known applications in signal processing, particularly speech or image processing.
Triplet Markov Chain for 3D MRI Brain Segmentation Using a Probabilistic Atlas
24 Citations2006Stéphanie Bricq, C. Collet +1 more
A new Markovian scheme for MRI segmentation using a priori knowledge obtained from probability maps to segment the brain in gray matter, white matter and cerebro-spinal fluid in an unsupervised way using a probabilistic atlas.
Unsupervised Dempster-Shafer fusion of dependent sensors
19 Citations2002Wojciech Pieczynski
It is shown how a recent parameter estimation of probabilistic models, valid in the dependent and possible non-Gaussian sensors case, can be extended to situations in which some of the sensors can be evidential.
Image and signal restoration using pairwise Markov trees
15 Citations2003Emmanuel Monfrini, Jean Lecomte +2 more
Image and signal restoration using pairwise markov trees
10 Citations2004Emmanuel Monfrini, Jean Lecomte +2 more
It is shown that PMT can perform better than the classical hidden Markov trees (HMT) when applied to unsupervised image segmentation and formulas of an original extension of the classical Kalman filter are given.
IEEE/SP 13th Workshop on Statistical Signal Processing, 2005Modeling non stationary hidden semi-markov chains with triplet markov chains and theory of evidence
8 Citations2005Wojciech Pieczynski
It is shown that it is possible to consider two auxiliary random chains in such a way that unsupervised segmentation of non stationary hidden semi-Markov chains is workable.
Segmenting non stationary images with triplet Markov fields
8 Citations2005Dalila Benboudjema, W. Pieczy
This paper proposes an original approach, based on the recent triplet Markov field (TMF) model, to segment non stationary images, and experiments indicate that the new algorithm performs better than the classical one.
DSpace (Centre National De La Recherche Scientifique)03 - Chaînes et arbres de Markov évidentiels avec applications à la segmentation des processus non stationnaires
7 Citations2005Pierre Lanchantin, Wojciech Pieczynski
