MRF-based texture segmentation using wavelet decomposed images

Pattern Recognition

Volumn 35, Issue 4, 2002, Pages 771-782

  Noda, Hideki ^a   Shirazi, Mahdad N ^b   Kawaguchi, Eiji ^a  

^a KYUSHU INSTITUTE OF TECHNOLOGY   (Japan)

^b NATIONAL INSTITUTE OF INFORMATION AND COMMUNICATIONS TECHNOLOGY   (Japan)

Author keywords

Image segmentation; MRF; Multiresolution; Texture; Unsupervised; Wavelet

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; MARKOV PROCESSES; TEXTURES; WAVELET TRANSFORMS;

MARKOV RANDOM FIELDS (MRF);

IMAGE SEGMENTATION;

ALGORITHM; IMAGE PROCESSING; SEGMENTATION; TEXTURE;

EID: 0036532823     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(01)00077-2     Document Type: Article

References (15)

1. Multiple resolution segmentation of textured images
2. A multiscale random field model for Bayesian image segmentation
3. Segmentation of textured images using a multiresolution Gaussian autoregressive model
4. On the statistical analysis of dirty pictures
5. The Laplacian pyramid as a compact image mode
6. Maximum likelihood from incomplete data via the EM algorithm
7. Mean field decomposition of a posteriori probability for MRF-based unsupervised textured image segmentation
8. Markov random fields and Gibbs ensembles
9. Stochastic relaxation. Gibbs distributions, and the Bayesian restoration of images
10. Data-driven segmentation of textured images using hierarchical Markov random fields
11. Texture analysis and classification with tree-structured wavelet transform
12. Unsupervised segmentation of noisy and textured images using Markov random fields