195668
20190316235824.0
10.1137/140974559
doi
000346854900033
ISI
ARTICLE
Analysis of Image Registration with Tangent Distance
2014
2014
Journal Articles
The computation of the geometric transformation between a reference and a target image, known as image registration or alignment, corresponds to the projection of the target image onto the transformation manifold of the reference image (the set of images generated by its geometric transformations). It often takes a nontrivial form such that exact computation of projections on the manifold is difficult. The tangent distance method is an effective alignment algorithm that exploits a linear approximation of the transformation manifold of the reference image. As theoretical studies about the tangent distance algorithm have been largely overlooked, we present in this work a detailed performance analysis of this useful algorithm, which can eventually help the selection of algorithm parameters. We consider a popular image registration setting using a multiscale pyramid of lowpass filtered versions of the (possibly noisy) reference and target images, which is particularly useful for recovering large transformations. We first show that the alignment error has a nonmonotonic variation with the filter size, due to the opposing effects of filtering on manifold nonlinearity and image noise. We then study the convergence of the multiscale tangent distance method to the optimal solution. We finally examine the performance of the tangent distance method in image classification applications. Our theoretical findings are confirmed by experiments on image transformation models involving translations, rotations and scalings. Our study is the first detailed study of the tangent distance algorithm that leads to a better understanding of its efficacy and to the proper selection of design parameters.
Image registration
tangent distance
image analysis
hierarchical registration methods
performance analysis
Vural, Elif
185439
242951
Frossard, Pascal
101475
241061
2860-2915
4
SIAM Journal on Imaging Sciences
7
n/a
878391
n/a
http://infoscience.epfl.ch/record/195668/files/TD_analysis.pdf
LTS4
252393
U10851
oai:infoscience.tind.io:195668
article
STI
GLOBAL_SET
185439
101475
101475
253578
EPFL-ARTICLE-195668
EPFL
PUBLISHED
REVIEWED
ARTICLE