Abstract—In this paper, a class of Random Field model, defined on a multiresolution array is used in the segmentation of gray level and textured images. The novel feature of one form of the model is that it is able to segment images containing unknown numbers of regions, where there may be significant variation of properties within each region. The estimation algorithms used are stochastic, but because of the multiresolution representation, are fast computationally, requiring only a few iterations per pixel to converge to accurate results, with error rates of 1-2 percent across a range of image structures and textures. The addition of a simple boundary process gives accurate results even at low resolutions, and consequently at very low computational cost. Index Terms—Markov random fields, image segmentation, Bayesian estimation. 1
|
2322
|
Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images
– Geman, Geman
- 1984
|
|
615
|
Spatial interaction and the statistical analysis of lattice systems (with discussion
– Besag
- 1974
|
|
552
|
On the statistical analysis of dirty pictures
– Besag
- 1986
|
|
296
|
Statistical and structural approaches to texture
– Haralick
- 1979
|
|
197
|
Markov random field texture models
– Cross, Jain
- 1983
|
|
155
|
Bayesian modeling of uncertainty in low-level vision
– Szeliski
- 1990
|
|
145
|
A multiscale random field model for Bayesian image segmentation
– Bouman, Shapiro
- 1994
|
|
113
|
Boundary detection by constrained optimization
– Geman, Geman, et al.
- 1990
|
|
102
|
Simultaneous parameter estimation and segmentation of Gibbs random fields using simulated annealing
– Lakshmanan, Derin
- 1989
|
|
97
|
Multiple resolution segmentation of textured images
– Bouman, Liu
- 1991
|
|
86
|
Modelling and estimation of multiresolution stochastic processes
– Basseville, Benveniste, et al.
- 1992
|
|
73
|
Unsuperivsed texture segmentation using markov random field models
– Manjunath, Chellappa
- 1991
|
|
70
|
Markov random field models for unsupervised segmentation of textured color images
– Panjwani, Healey
- 1991
|
|
55
|
Multiscale Representations of Markov Random Fields
– Luettgen, Karl, et al.
- 1993
|
|
38
|
Two dimensional discrete markovian fields
– Woods
- 1972
|
|
33
|
randomness: wold features for image modeling and retrieval
– Liu, Picard, et al.
- 1996
|
|
32
|
Texture Synthesis Using 2-D Noncausal Autoregressive Models
– Chellappa, Kashyap
- 1985
|
|
32
|
Discrete Markov image modeling and inference on the quatree
– Laferté, Pérez, et al.
- 2000
|
|
29
|
Markov Random Fields and their Applications
– Kinderman, Snell
- 1980
|
|
28
|
Multiresolution gauss-markov random field models for texture segmentation
– Krishnamachari, Chellappa
- 1997
|
|
28
|
Multiresolution Image Classification by Hierarchical Modeling with Two-Dimensional Hidden Markov Models
– Li, Gray, et al.
- 2000
|
|
26
|
Unsupervised parallel image classification using Markovian models
– Kato, Zerubia, et al.
- 1999
|
|
25
|
A Unified Texture Model Based on a 2-D Wold-Like Decomposition
– Francos, Meiri, et al.
- 1993
|
|
25
|
Sonar image segmentation using an unsupervised hierarchical MRF model
– Mignotte, Collet, et al.
- 2000
|
|
22
|
A Bayesian Segmentation Methodology for Parametric Image Models
– Hutchinson
- 1995
|
|
20
|
Maximum Likelihood Unsupervised Textured Image Segmentation
– Cohen, Fan
- 1992
|
|
18
|
A two-component model of texture for analysis and synthesis
– Hsu, Wilson
- 1998
|
|
17
|
A hierarchical Markov random field model and multitemperature annealing for parallel image classification
– Kato, Berthod, et al.
- 1996
|
|
14
|
Unsupervised Texture Segmentation via Wavelet Transform
– Lu, Chung, et al.
- 1997
|
|
13
|
Restriction of a Markov Random Field on a Graph and Multiresolution Statistical Image Modeling
– Perez, Heitz
- 1996
|
|
12
|
A Generalised Wavelet Transform for Fourier Analysis: The Multiresolution Fourier Transform and Its Application to Image and Audio Signal Analysis
– Wilson, Calway, et al.
- 1992
|
|
8
|
Multiresolution Image Modelling and Estimation
– Clippingdale
- 1988
|
|
8
|
Multiscale Methods for the Segmentation and Reconstruction of Signals and Images
– Schneider, Fieguth, et al.
- 2000
|
|
5
|
Reconstruction and boundary detection of range and intensity images using multiscale
– Gunsel, Jain, et al.
- 1996
|
|
2
|
Unsupervised Image Segmentation Using Multiresolution Markov Random Fields
– Li
- 1998
|
