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PCA, DWT based fusion as Band Expansion for Blind Source Separation in magnetic resonance images

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3 Author(s)
Kaustubh, V. ; BE (ENTC), MCOE, Pune, India ; Kamathe, R.S. ; Joshi, K.R.

This report describes work done on Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT) based Image Fusion techniques for additional band generation of Brain MR Images and their Blind Source Separation. A technique widely adopted for source separation is Independent Component Analysis (ICA). One of the issues that have been overlooked and not investigated is lack of MR Images to be used to unmix signal sources of interest. Two new methods for generating more images were tried and their impact on the soft tissue contrast were recorded. This paper introduces PCA & DWT based image fusion techniques to generate an additional new set of images from the original MR images. These newly generated images are then combined with the original MR images to provide sufficient MR images for ICA analysis.

Published in:

Signal Processing, Communication, Computing and Networking Technologies (ICSCCN), 2011 International Conference on

Date of Conference:

21-22 July 2011