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[Noise image segmentation based on generalized fuzzy Gibbs random field].
Nan Fang Yi Ke Da Xue Xue Bao. 2006 Apr; 26(4):390-3.NF

Abstract

In order to segment the blurred image with large noise, the authors propose a new Bayesian image segmentation method based on generalized fuzzy Gibbs random field. Based on the generalized fuzzy set, the new method introduces generalized fuzzy membership into Gibbs potential function and the potential function is redefined to obtain the new segmentation model. The optimal processing is executed through iterative conditional modes (ICM). The experiment results showed that the new approach could effectively segment the degenerated images.

Authors+Show Affiliations

Gong J
Department of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China.
Zhang Y
No affiliation info available
Chen WF
No affiliation info available

MeSH

AlgorithmsArtificial IntelligenceBayes TheoremComputer SimulationFuzzy LogicHumansImage EnhancementImage Interpretation, Computer-AssistedModels, StatisticalPattern Recognition, Automated

Pub Type(s)

English Abstract
Journal Article
Research Support, Non-U.S. Gov't

Language

chi

PubMed ID

16624734

Citation

Gong, Jian, et al. "[Noise Image Segmentation Based On Generalized Fuzzy Gibbs Random Field]." Nan Fang Yi Ke Da Xue Xue Bao = Journal of Southern Medical University, vol. 26, no. 4, 2006, pp. 390-3.
Gong J, Zhang Y, Chen WF. [Noise image segmentation based on generalized fuzzy Gibbs random field]. Nan Fang Yi Ke Da Xue Xue Bao. 2006;26(4):390-3.
Gong, J., Zhang, Y., & Chen, W. F. (2006). [Noise image segmentation based on generalized fuzzy Gibbs random field]. Nan Fang Yi Ke Da Xue Xue Bao = Journal of Southern Medical University, 26(4), 390-3.
Gong J, Zhang Y, Chen WF. [Noise Image Segmentation Based On Generalized Fuzzy Gibbs Random Field]. Nan Fang Yi Ke Da Xue Xue Bao. 2006;26(4):390-3. PubMed PMID: 16624734.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - [Noise image segmentation based on generalized fuzzy Gibbs random field]. AU - Gong,Jian, AU - Zhang,Yu, AU - Chen,Wu-fan, PY - 2006/4/21/pubmed PY - 2007/4/7/medline PY - 2006/4/21/entrez SP - 390 EP - 3 JF - Nan fang yi ke da xue xue bao = Journal of Southern Medical University JO - Nan Fang Yi Ke Da Xue Xue Bao VL - 26 IS - 4 N2 - In order to segment the blurred image with large noise, the authors propose a new Bayesian image segmentation method based on generalized fuzzy Gibbs random field. Based on the generalized fuzzy set, the new method introduces generalized fuzzy membership into Gibbs potential function and the potential function is redefined to obtain the new segmentation model. The optimal processing is executed through iterative conditional modes (ICM). The experiment results showed that the new approach could effectively segment the degenerated images. SN - 1673-4254 UR - https://www.unboundmedicine.com/medline/citation/16624734/[Noise_image_segmentation_based_on_generalized_fuzzy_Gibbs_random_field]_ DB - PRIME DP - Unbound Medicine ER -