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...
Saved in:
Main Authors: | , , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
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 |