Unsupervised joint deconvolution and segmentation method for textured images: a Bayesian approach and an advanced sampling algorithm

Unsupervised joint deconvolution and segmentation method for textured images: a Bayesian approach and an advanced sampling algorithm

Abstract The paper tackles the problem of joint deconvolution and segmentation of textured images. The images are composed of regions containing a patch of texture that belongs to a set of K possible classes. Each class is described by a Gaussian random field with parametric power spectral density w...

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Bibliographic Details
Main Authors: Cornelia Vacar, Jean-François Giovannelli
Format: Article
Language:English
Published: SpringerOpen 2019-03-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Segmentation
Deconvolution
Texture
Bayes
Unsupervised learning
Potts
Online Access:http://link.springer.com/article/10.1186/s13634-018-0597-x

Internet

http://link.springer.com/article/10.1186/s13634-018-0597-x

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