Measuring image similarity to sub-pixel accuracy

Author

Rohde, G.K. ; Healy, D.M., Jr. ; Berenstein, C.A. ; Aldroubi, A.

Author_Institution

Dept. of Mathematics, Maryland Univ., Baltimore, MD

fYear

2006

fDate

6-9 April 2006

Firstpage

638

Lastpage

641

Abstract

Measuring the similarity between different images is essential for performing registration (alignment) and many related tasks. We show that popular image similarity measures such as the sum of squared differences (SSD), cross correlation (CC), and mutual information (MI), particularly in the presence of noise, may present local optima at half pixel translation intervals when low order interpolators are used to model the discrete images. Several strategies for reducing local optima artifacts during registration are discussed. Results using magnetic resonance image (MRI) data are shown

Keywords

biomedical MRI; image registration; interpolation; medical image processing; MRI; cross correlation; image alignment; image registration; image similarity; interpolators; local optima artifacts; magnetic resonance image; mutual information; noise; subpixel accuracy; sum of squared differences; Biomedical measurements; Educational institutions; Image registration; Interpolation; Low pass filters; Magnetic resonance imaging; Mathematics; Noise measurement; Performance evaluation; Random processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on

Conference_Location

Arlington, VA

Print_ISBN

0-7803-9576-X

Type

conf

DOI

10.1109/ISBI.2006.1624997

Filename

1624997