Parameter estimation and restoration of noisy images using Gibbs distributions in hidden Markov models

CVGIP: Graphical Models and Image Processing

Volumn 54, Issue 3, 1992, Pages 187-197

  Zhao, Yunxin ^d   Zhuang, Xinhua ^b   Atlas, Les ^c   Anderson, Lars ^a,c  

^a Panasonic Corporation of North America   (United States)

^b UNIVERSITY OF MISSOURI   (United States)

^c UNIVERSITY OF WASHINGTON   (United States)

^d Department of Statistics University of Washington ^*

Author keywords

[No Author keywords available]

Indexed keywords

EID: 18844411030     PISSN: 10499652     EISSN: None     Source Type: Journal    
DOI: 10.1016/1049-9652(92)90050-8     Document Type: Article

References (15)

1. An introduction to hidden Markov models
2. On Stochastic Modeling and Time-Frequency Representation of Signals with Applications to Speech Recognition and Image Restoration
3. An introduction to the application of the theory of probabilistic functions of a Markov process to automatic speech recognition
4. Maximum likelihood from incomplete data via the EM algorithm
5. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
6. On the statistical analysis of dirty pictures
7. Probabilistic solution of illposed problems in computational vision
8. Spatial interactions and the statistical analysis of lattice systems
9. Applications of the Gibbs distributions to hidden Markov modeling for speaker independent isolated word recognition
10. Bayesian image analysis: An application to single photon emission tomography
11. Modeling and segmentation of noisy and textured images using Gibbs random fields
12. Stochastic Inference for Spatial Statistics
13. An inequality with applications to statistical prediction for functions of Markov processes and to a model for ecology
14. A maximization technique occurring in the statistic analysis of probabilistic functions of Markov chains