The Open UniversitySkip to content
 

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.

Full text available as:
[img]
Preview
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (885Kb)
URL: http://icip2012.com
Google Scholar: Look up in Google Scholar

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 > Computing & Communications
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Related URLs:
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
Share this page:

Actions (login may be required)

View Item
Report issue / request change

Policies | Disclaimer

© The Open University   + 44 (0)870 333 4340   general-enquiries@open.ac.uk