DocumentCode :
2343908
Title :
ICA in Image Processing: A Survey
Author :
Goel, Swati ; Verma, Akhilesh ; Goel, Savita ; Juneja, Komal
fYear :
2015
fDate :
13-14 Feb. 2015
Firstpage :
144
Lastpage :
149
Abstract :
Source separation is a problem in which signals are mixed together. It is becoming a tedious task to recuperate original components signal from the signal mixture. Blind Source Separation (BSS) is suggested as a key to the problem aiming at finding the linear representation in such a way that the components are statistically (stochastically) independent. Independent Component Analysis (ICA) is an approach that attained a wider attention and a growing significance in a diverse range of research fields for accomplishing Blind Source Separation. This paper includes preface of ICA, its variants and their list of applications in brief.
Keywords :
blind source separation; image processing; independent component analysis; BSS; ICA; blind source separation; image processing; independent component analysis; linear representation; research fields; Algorithm design and analysis; Classification algorithms; Feature extraction; Filter banks; Image segmentation; Independent component analysis; Kernel; Filter bank; Global features; ICA; Image model; Texture segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on
Conference_Location :
Ghaziabad
Print_ISBN :
978-1-4799-6022-4
Type :
conf
DOI :
10.1109/CICT.2015.91
Filename :
7078684
Link To Document :
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