A joint multicontext and multiscale approach to Bayesian image segmentation

IEEE Transactions on Geoscience and Remote Sensing

Volumn 39, Issue 12, 2001, Pages 2680-2688

  Fan, Guoliang ^b   Xia, Xiang Gen ^a,b  

^a IEEE   (United States)

^b UNIVERSITY OF DELAWARE   (United States)

Author keywords

Bayesian approach; Boundary localization; Context; Image segmentation

Indexed keywords

BAYESIAN IMAGE SEGMENTATION;

COMPUTATIONAL COMPLEXITY; HEURISTIC METHODS; MARKOV PROCESSES; PROBLEM SOLVING; SYNTHETIC APERTURE RADAR;

IMAGE SEGMENTATION;

EID: 0035691627     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/36.975002     Document Type: Article

References (26)

1. Spatial interation and statistical analysis of lattice systems
2. Modeling and segmentation of noisy and textured images using Gibbs random fields
3. Multiple resolution segmentation of textured images
4. A multiscale random field model for Bayesian image segmentation
5. Multiscale document segmentation
6. Multiscale Bayesian segmentation using a trainable context model
7. Image segmentation using wavelet-domain classification
8. Image classification by a two dimensional hidden Markov model
9. Multiresolution image classification by hierarchical modeling with two dimensional hidden Markov models
10. Parallel image classification using multiscale Markov random fields
11. Segmentation of textured images using a multiresolution Gaussian autoregressive model
12. Locating boundaries of textured regions
13. Supervised segmentation using a multiresolution data representation
14. Multiscale segmentation anomaly enhancement of SAR imagery
15. Refining image segmentation by integration of edge and region data
16. Boundary localization in texture segmentation
17. Multiscale segmentation of unstructured document pages using soft decision integration
18. Multiscale image segmentation using joint texture and shape analysis
19. Wavelet-based statistical signal processing using hidden Markov models
20. Low complexity high-order context modeling of embedded wavelet bit streams
21. Stochastic and deterministic networks for texture segmentation
22. Multiresolution feature extraction and selection for texture segmentation