Unsupervised segmentation of hidden Markov fields corrupted by correlated non-Gaussian noise

Abstract Pixel labeling problem stands among the most commonly considered topics in image processing. Many statistical approaches have been developed for this purpose, particularly in the frame of hidden Markov random fields. Such models have been extended in many directions to better fit image data. Our contribution falls under such extensions and consists of introducing two new models allowing one to deal with non-Gaussian correlated noise. The first one is purely probabilistic, whereas the second one calls on Dempster–Shafer theory of evidence, both being particular triplet Markov fields. The interest of the proposed models is assessed in unsupervised segmentation of sampled and real images. While both models exhibit significant improvement with respect to classic models, the evidential model turns out to be of particular interest when the hidden label field presents fine details.

• Publication year

  2018

• Venue

  International Journal of Approximate Reasoning

• Publication date

  2018-11-01

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1016/J.IJAR.2018.08.001
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A Mathematical Theory of Evidence

  2020cited by this paper
• Oriented Triplet Markov Fields

  2018cited by this paper
• Weighted Fuzzy Dempster–Shafer Framework for Multimodal Information Integration

  2018cited by this paper
• Asymmetric hidden Markov models

  2017cited by this paper
• Inference and Learning in Evidential Discrete Latent Markov Models

  2017cited by this paper
• Unsupervised Segmentation of SAR Images Using Gaussian Mixture-Hidden Evidential Markov Fields

  2016cited by this paper
• Discriminative Random Fields Based on Maximum Entropy Principle for Semisupervised SAR Image Change Detection

  2016cited by this paper
• Imprecise continuous-time Markov chains

  2016cited by this paper
• Dempster–Shafer Fusion of Evidential Pairwise Markov Chains

  2016cited by this paper
• Imprecise stochastic processes in discrete time: global models, imprecise Markov chains, and ergodic theorems

  2016cited by this paper
• Dempster-Shafer fusion of evidential pairwise Markov fields

  2016influential reference
• Fast Unsupervised Bayesian Image Segmentation With Adaptive Spatial Regularisation

  2015influential reference
• Deep Reconstruction Models for Image Set Classification

  2015cited by this paper
• Synthetic aperture radar image segmentation using fuzzy label field-based triplet Markov fields model

  2014cited by this paper
• Fuzzy Clustering With a Modified MRF Energy Function for Change Detection in Synthetic Aperture Radar Images

  2014cited by this paper
• Stochastic Relaxation

  2014cited by this paper
• Making Use of Partial Knowledge About Hidden States in HMMs: An Approach Based on Belief Functions

  2014cited by this paper
• A Two-Stage Image Segmentation Method Using a Convex Variant of the Mumford-Shah Model and Thresholding

  2013cited by this paper
• Exploiting Information Geometry to Improve the Convergence of Nonparametric Active Contours

  2013cited by this paper
• Image Segmentation Using a Spatially Correlated Mixture Model with Gaussian Process Priors

  2013cited by this paper
• Markovian modelling and Fisher distribution for unsupervised classification of radar images

  2013cited by this paper
• SAR Image Multiclass Segmentation Using a Multiscale TMF Model in Wavelet Domain

  2012cited by this paper
• Gaussian-Mixture-Model-Based Spatial Neighborhood Relationships for Pixel Labeling Problem

  2012cited by this paper
• Spatial spectral Gaussian mixture model approach for automatic segmentation of multispectral MR brain images

  2011cited by this paper
• Contour Detection and Hierarchical Image Segmentation

  2011cited by this paper
• Markov Random Fields for Vision and Image Processing

  2011cited by this paper
• Supervised High-Resolution Dual-Polarization SAR Image Classification by Finite Mixtures and Copulas

  2011cited by this paper
• Maximum likelihood estimation from fuzzy data using the EM algorithm

  2011cited by this paper
• Operational Performance of an Automatic Preliminary Spectral Rule-Based Decision-Tree Classifier of Spaceborne Very High Resolution Optical Images

  2010cited by this paper
• Inference in hidden Markov models

  2010cited by this paper
• On Evidential Markov Chains

  2010cited by this paper
• Sur la convergence de l'estimation conditionnelle itérative

  2008cited by this paper
• Fuzzy pairwise Markov chain to segment correlated noisy data

  2008cited by this paper
• Unsupervised Statistical Segmentation of Nonstationary Images Using Triplet Markov Fields

  2007cited by this paper
• Fast Global Minimization of the Active Contour/Snake Model

  2007cited by this paper
• Multisensor triplet Markov chains and theory of evidence

  2007cited by this paper
• Non-stationary fuzzy Markov chain

  2007cited by this paper
• A Spatially Constrained Generative Model and an EM Algorithm for Image Segmentation

  2007cited by this paper
• Unsupervised change detection on SAR images using fuzzy hidden Markov chains

  2006cited by this paper
• Multisensor triplet Markov fields and theory of evidence

  2006cited by this paper
• Inference in Hidden Markov Models

  2006cited by this paper
• Supervised segmentation of remote sensing images based on a tree-structured MRF model

  2005cited by this paper
• Unsupervised restoration of hidden nonstationary Markov chains using evidential priors

  2005cited by this paper
• 3-D/2-D registration of CT and MR to X-ray images

  2003cited by this paper
• Statistical image segmentation using triplet Markov fields

  2003cited by this paper
• Hidden Markov processes

  2002cited by this paper
• Multisource classification using ICM and Dempster-Shafer theory

  2002cited by this paper
• Markov Random Field Modeling in Image Analysis

  2001cited by this paper
• Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

  2001cited by this paper
• Fast approximate energy minimization via graph cuts

  2001cited by this paper
• Image Segmentation and Compression Using Hidden Markov Models

  2000cited by this paper
• Statistical Pattern Recognition

  1999cited by this paper
• A first step toward automatic interpretation of SAR images using evidential fusion of several structure detectors

  1999cited by this paper
• 3 - Sur le choix de méthode de segmentation statistique d'images

  1998cited by this paper
• Introduction of neighborhood information in evidence theory and application to data fusion of radar and optical images with partial cloud cover

  1998cited by this paper
• An equivalence of the EM and ICE algorithm for exponential family

  1997cited by this paper
• Multiresolution Color Image Segmentation

  1994cited by this paper
• Partial volume tissue classification of multichannel magnetic resonance images-a mixel model.

  1991cited by this paper
• The Transferable Belief Model

  1991cited by this paper
• Probabilistic Solution of Ill-Posed Problems in Computational Vision

  1987cited by this paper
• On the Statistical Analysis of Dirty Pictures

  1986cited by this paper
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images

  1984cited by this paper
• Mixture densities, maximum likelihood, and the EM algorithm

  1984cited by this paper

• Some Results on Specificity of Possibility Distributions

  2025cites this paper
• Contextual Peano Scan and Fast Image Segmentation Using Hidden and Evidential Markov Chains

  2025influential citation
• A comparative analysis of aggregation rules for coherent lower previsions

  2025cites this paper
• Unsupervised segmentation of images using bi-dimensional pairwise Markov chains model

  2024cites this paper
• Complex Evidence Theory for Multisource Data Fusion

  2024cites this paper
• Neighborhood Feature Extraction and Haralick Attributes for Medical Image Analysis: Application to Breast Cancer Mammography Image

  2023cites this paper
• Accurate and fast parameter identification of conditionally Gaussian Markov jump linear system with input control

  2022cites this paper
• Kernel smoothing classification of multiattribute data in the belief function framework: Application to multichannel image segmentation

  2022cites this paper
• Fractal analysis segmentation of medical images: Application to breast cancer mammography image

  2022cites this paper
• Efficient Intrusion Detection Using Evidence Theory

  2021cites this paper
• Pairwise and Hidden Markov Random Fields in Image Segmentation

  2021cites this paper
• Fuzzy Hidden Markov Model in Images Segmentation

  2020cites this paper
• Dempster-Shafer Parzen-Rosenblatt Hidden Markov Fields for Multichannel Image Segmentation

  2020cites this paper
• Remote Sensing Data Fusion: Markov Models and Mathematical Morphology for Multisensor, Multiresolution, and Multiscale Image Classification

  2018cites this paper
• Belief Functions: Theory and Applications

  2018cites this paper
• Multi-Modal Cooperative Spectrum Sensing Based on Dempster-Shafer Fusion in 5G-Based Cognitive Radio

  2018influential citation
• Conflict Evidence Measurement Based on the Weighted Separate Union Kernel Correlation Coefficient

  2018cites this paper
• Uncertainty-Aware Parzen-Rosenblatt Classifier for Multiattribute Data

  2018cites this paper
• Performance evaluation of advanced manufacturing technologies: A De novo approach

  2017cites this paper
• Unsupervised Segmentation of Nonstationary Data using Triplet Markov Chains

  2017cites this paper
• Information fusion and decision-making using belief functions : application to therapeutic monitoring of cancer. (Fusion de l'information et prise de décisions à l'aide des fonctions de croyance : application au suivi thérapeutique du cancer)

  2017cites this paper
• Triplet Markov Chains Based- Estimation of Nonstationary Latent Variables Hidden with Independent Noise

  2017cites this paper
• An evidential Markov decision making model

  2017cites this paper
• A new belief Markov chain model and its application in inventory prediction

  2017cites this paper
• 40 years of Dempster-Shafer theory

  2016cites this paper
• Unsupervised Segmentation of SAR Images Using Gaussian Mixture-Hidden Evidential Markov Fields

  2016cites this paper
• Unsupervised Segmentation of Markov Random Fields Corrupted by Nonstationary Noise

  2016cites this paper
• Evidential Correlated Gaussian Mixture Markov Model for Pixel Labeling Problem

  2016influential citation