Efficient Image Registration using Fast Principal Component Analysis

Reel, Parminder Singh; Dooley, Laurence S. and Wong, Patrick (2012). Efficient Image Registration using Fast Principal Component Analysis. In: IEEE International Conference on Image Processing (ICIP'12), 30th Sept to 3rd Oct 2012, Lake Buena Vista, Orlando, Florida, USA.

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Abstract

Incorporating spatial features with mutual information (MI) has demonstrated superior image registration performance compared with traditional MI-based methods, particularly in the presence of noise and intensity non-uniformities (INU). This paper presents a new efficient MI-based similarity measure which applies Expectation Maximisation for Principal Component Analysis (EMPCA-MI), to afford significantly lower computational complexity, while providing analogous image registration performance with other feature-based MI solutions. Experimental analysis corroborates both the improved robustness and faster runtimes of EMPCA-MI, for different test datasets containing both INU and noise artefacts.

Item Type:	Conference Item
Copyright Holders:	2012 IEEE
Extra Information:	ISBN: 978-1-4673-2532-5, pp. 1661–1664
Academic Unit/Department:	Mathematics, Computing and Technology > Communication and Systems
Interdisciplinary Research Centre:	Centre for Research in Computing (CRC)
Related URLs:	http://icip2012.com/AcceptedPaperList.as...(Other)
Item ID:	33551
Depositing User:	Laurence Dooley
Date Deposited:	08 May 2012 09:51
Last Modified:	24 Oct 2012 04:17
URI:	http://oro.open.ac.uk/id/eprint/33551

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