On context-based Bayesian image segmentation: Joint multi-context and multiscale approach and wavelet-domain Hidden Markov models

Conference Record of the Asilomar Conference on Signals, Systems and Computers

Volumn 2, Issue , 2001, Pages 1146-1150

  Fan, Guoliang ^a   Xia, Xiang Gen ^b  

^a Oklahoma State University   (United States)

^b UNIVERSITY OF DELAWARE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; FEATURE EXTRACTION; IMAGE ANALYSIS; ITERATIVE METHODS; MARKOV PROCESSES; MATHEMATICAL MODELS; OPTIMIZATION; STATISTICAL METHODS; WAVELET TRANSFORMS;

CONTEXT-BASED BAYESIAN IMAGE SEGMENTATION; CONTEXTUAL MODELLING; HIDDEN MARKOV MODEL; STATISTICAL TEXTURE CHARACTERIZATION;

IMAGE SEGMENTATION;

EID: 0035573174     PISSN: 10586393     EISSN: None     Source Type: Journal    
DOI: 10.1109/ACSSC.2001.987671     Document Type: Article

References (9)

1. A multiscale random field model for bayesian image segmentation
2. Multiscale bayesian segmentation using a trainable context model
3. Multiscale image segmentation using wavelet-domain hidden markov models
4. A joint multi-context and multiscale approach to bayesian image segmentation
5. Wavelet-based statistical signal processing using hidden Markov models
6. Maximum likelihood texture analysis and classification using wavelet-domain hidden Markov models
7. Trainable context model for multiscale segmentation
8. Boundary localization in texture segmentation