Motion estimation using ordinal measures

We present a method for motion estimation using ordinal measures. Ordinal measures are based on relative ordering of intensity values in an image region called rank permutation. While popular measures like the sum-of-squared-difference (SSD) and normalized correlation (NCC) rely on linearity between...

Full description

Saved in:
Bibliographic Details
Published inProceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition pp. 982 - 987
Main Authors Bhat, D.N., Nayar, S.K., Gupta, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1997
Subjects
Equations
Image sequences
Imaging phantoms
Linearity
Magnetic properties
Magnetic resonance
Magnetic resonance imaging
Motion estimation
Motion measurement
Tagging
Online AccessGet full text

Cover

More Information
Summary:We present a method for motion estimation using ordinal measures. Ordinal measures are based on relative ordering of intensity values in an image region called rank permutation. While popular measures like the sum-of-squared-difference (SSD) and normalized correlation (NCC) rely on linearity between corresponding intensity values, ordinal measures only require them to be monotonically related so that rank permutations between corresponding regions are presented. This property turns out to be useful for motion estimation in tagged magnetic resonance images. We study the imaging equation involved in two methods of tagging and observe temporal monotonicity in intensity under certain conditions though the tags themselves fade. We compare our method to SSD and NCC in a rotating ring phantom image sequence. We present an experiment on a real heart image sequence which suggests the suitability of our method.
ISBN:9780818678226
0818678224
ISSN:1063-6919
DOI:10.1109/CVPR.1997.609447