The use of Gibbs random fields for image segmentation

Presents a robust and adaptive technique for segmentation of a noisy image. The original image is modeled by an underlying Gibbs random field, and the noise is the mixture of an additive independent Gaussian noise and a salt or pepper noise. The processes of maximum a posteriori segmentation and max...

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Bibliographic Details
Main Authors: Tao Wang, Xinhua Zhuang, Xiaoliang Xing
Format: Conference Proceeding
Language:English
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Summary:Presents a robust and adaptive technique for segmentation of a noisy image. The original image is modeled by an underlying Gibbs random field, and the noise is the mixture of an additive independent Gaussian noise and a salt or pepper noise. The processes of maximum a posteriori segmentation and maximum-likelihood estimation for the image model parameters are carried out simultaneously.< >
DOI:10.1109/ICPR.1992.201927