Gram polynomial image decimation and its application to non-rigid registration

Amir Badshah; Paul O'Leary; Matthew Harker

doi:10.1117/12.876665

7 February 2011 Gram polynomial image decimation and its application to non-rigid registration

Amir Badshah, Paul O'Leary, Matthew Harker

Proceedings Volume 7877, Image Processing: Machine Vision Applications IV; 787707 (2011) https://doi.org/10.1117/12.876665
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

This paper presents a new approach to non-rigid registration. A hierarchical subdivision approach is applied, with local normalized phase correlation for patch registration. The major improvement is achieved by implementing a suitable decimation at each level. The decimation is implemented via a Gram polynomial basis. Both global and local polynomial approximation are considered and compared with the use of a Fourier basis. The issue of Gibbs error in polynomial decimation is examined. It is shown that the Gram basis is superior when applied to signals with strong gradient, i.e., a gradient which generates a significant Gibbs error with a Fourier basis. A bivariate Gram polynomial tensor product approximation is used to implement regularization. It is demonstrated that the new method performs well on both synthetic and real image data. The procedure requires approximately 1.3 sec. to register an image with 800 × 500 pixels.

Citation Download Citation

Amir Badshah, Paul O'Leary, and Matthew Harker "Gram polynomial image decimation and its application to non-rigid registration", Proc. SPIE 7877, Image Processing: Machine Vision Applications IV, 787707 (7 February 2011); https://doi.org/10.1117/12.876665

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available