Image enhancement via blind decomposition techniques

Author

Polat, Özgür Murat ; Özkazanç, Yakup S.

Author_Institution

TUBITAK- BILGEM, UEKAE, İltaren, Turkey

fYear

2011

fDate

20-22 April 2011

Firstpage

1085

Lastpage

1088

Abstract

Unsupervised learning and blind signal decomposition methods are used for recovering unknown source signals from their linear mixtures using the observed data only. In these methods, a new representation of the data can reveal some hidden information inherent in the data. In this study, principal component analysis, independent component analysis and non-negative matrix factorization methodologies are applied on a single image for extracting information and image enhancement.

Keywords

blind source separation; data structures; image enhancement; principal component analysis; unsupervised learning; blind decomposition technique; blind signal decomposition method; data representation; image enhancement; independent component analysis; information extraction; nonnegative matrix factorization methodology; principal component analysis; unknown source signal; unsupervised learning; Algorithm design and analysis; Conferences; Independent component analysis; Matrix decomposition; Principal component analysis; Signal processing; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications (SIU), 2011 IEEE 19th Conference on

Conference_Location

Antalya

Print_ISBN

978-1-4577-0462-8

Electronic_ISBN

978-1-4577-0461-1

Type

conf

DOI

10.1109/SIU.2011.5929843

Filename

5929843