Automatic spatial accuracy estimation for correlation-based image registration

Stephen DelMarco; Helen Webb; Victor Tom

doi:10.1117/12.2518183

13 May 2019 Automatic spatial accuracy estimation for correlation-based image registration

Stephen DelMarco, Helen Webb, Victor Tom

Proceedings Volume 10993, Mobile Multimedia/Image Processing, Security, and Applications 2019; 1099307 (2019) https://doi.org/10.1117/12.2518183
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Accurate and successful image registration is a key enabling technology in applications such as image fusion, matching and pattern recognition. Knowledge of registration solution quality and accuracy can help prevent an inaccurate registration from degrading or corrupting performance of downstream image processing applications. However, estimating the spatial accuracy of image registration solutions can be difficult in the absence of ground-truth information on feature content or fiducial marker correspondences. This paper presents an automated spatial registration accuracy measurement for estimating and quantifying the spatial accuracy of correlation-based image registration in the absence of ground-truth information. For correlation surfaces exhibiting a single dominant peak, the approach consists of fitting an appropriate region of the correlation surface, about the peak coefficient, with a two-dimensional Gaussian. It then uses the covariance of the Gaussian to model the registration spatial error covariance. Use of a fitted Gaussian provides an intuitive probabilistic interpretation to the registration solution; the Gaussian function value at a spatial offset from the Gaussian peak gives the likelihood of that offset value. For more complicated regions containing multiple correlation local peak values, we extend the approach to fit a Gaussian mixture model to the region and use the mixture model covariance for the spatial accuracy metric. We describe an energy-based method for choosing the model region of the correlation surface. We discuss implementation subtleties and provide perturbation methods for handling numerically illconditioned matrices. We present numerical spatial error estimation results generated from registration of real video imagery acquired from a UAV platform.

Conference Presentation

Citation Download Citation

Stephen DelMarco, Helen Webb, and Victor Tom "Automatic spatial accuracy estimation for correlation-based image registration", Proc. SPIE 10993, Mobile Multimedia/Image Processing, Security, and Applications 2019, 1099307 (13 May 2019); https://doi.org/10.1117/12.2518183

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