An MRF-ICA Based Algorithm for Image Separation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2005

AUTHORS

Sen Jia , Yuntao Qian

ABSTRACT

Separation of sources from one-dimensional mixture signals such as speech has been largely explored. However, two-dimensional sources (images) separation problem has only been examined to a limited extent. The reason is that ICA is a very general-purpose statistical technique, and it does not take the spatial information into account while separating mixture images. In this paper, we introduce Markov random field model to incorporate the spatial information into ICA. MRF is considered as a powerful tool to model the joint probability distribution of the image pixels in terms of local spatial interactions. An MRF-ICA based algorithm is proposed for image separation. It is successfully demonstrated on artificial and real images. More... »

PAGES

391-395

Book

TITLE

Advances in Natural Computation

ISBN

978-3-540-28325-6
978-3-540-31858-3

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/11539117_57

DOI

http://dx.doi.org/10.1007/11539117_57

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1029343730


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