A Least Squares based Groupwise Image Registration Technique

Nefeli Lamprinou, Nikolaos Nikolikos, Emmanouil Psarakis

Abstract

Compared with pairwise registration, groupwise registration is capable of handling a large-scale population of images simultaneously in an unbiased way. In this work we improve upon the state-of-the-art pixel-level, Least-Squares (LS) based groupwise image registration methods. Specifically, we propose a new iterative algorithm which outperforms in terms of its computational cost, a recently introduced LS based iterative congealing scheme. Namely, the particle system that was introduced in that work is used and by imposing its “center of mass” to be motionless, during each iteration of the minimization process, a sequence of “centroid” images whose limit is the unknown “mean” image is optimally in closed form defined, thus solving in a reduced computational cost the groupwise problem. Moreover, the registration technique is properly adapted by the use of Self Quotient Images (SQI) in order to become capable for solving the groupwise registration of multimodal images. Since the proposed congealing technique is invariant to the size of the image set, it can be used for the successful solution of the problem on large image sets with low complexity. From the application of the proposed technique on a series of experiments for the groupwise registration of face, unimodal and multimodal magnetic resonance image sets its performance seems to be very good.

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Paper Citation


in Harvard Style

Lamprinou N., Nikolikos N. and Psarakis E. (2020). A Least Squares based Groupwise Image Registration Technique.In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-402-2, pages 120-127. DOI: 10.5220/0009180701200127


in Bibtex Style

@conference{visapp20,
author={Nefeli Lamprinou and Nikolaos Nikolikos and Emmanouil Psarakis},
title={A Least Squares based Groupwise Image Registration Technique},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2020},
pages={120-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009180701200127},
isbn={978-989-758-402-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - A Least Squares based Groupwise Image Registration Technique
SN - 978-989-758-402-2
AU - Lamprinou N.
AU - Nikolikos N.
AU - Psarakis E.
PY - 2020
SP - 120
EP - 127
DO - 10.5220/0009180701200127