1,241 research outputs found
Zooming from Global to Local: A Multiscale RBF Approach
Because physical phenomena on Earth's surface occur on many different length
scales, it makes sense when seeking an efficient approximation to start with a
crude global approximation, and then make a sequence of corrections on finer
and finer scales. It also makes sense eventually to seek fine scale features
locally, rather than globally. In the present work, we start with a global
multiscale radial basis function (RBF) approximation, based on a sequence of
point sets with decreasing mesh norm, and a sequence of (spherical) radial
basis functions with proportionally decreasing scale centered at the points. We
then prove that we can "zoom in" on a region of particular interest, by
carrying out further stages of multiscale refinement on a local region. The
proof combines multiscale techniques for the sphere from Le Gia, Sloan and
Wendland, SIAM J. Numer. Anal. 48 (2010) and Applied Comp. Harm. Anal. 32
(2012), with those for a bounded region in from Wendland, Numer.
Math. 116 (2012). The zooming in process can be continued indefinitely, since
the condition numbers of matrices at the different scales remain bounded. A
numerical example illustrates the process
RBF multiscale collocation for second order elliptic boundary value problems
In this paper, we discuss multiscale radial basis function collocation methods for solving elliptic partial differential equations on bounded domains. The approximate solution is constructed in a multi-level fashion, each level using compactly supported radial basis functions of smaller scale on an increasingly fine mesh. On each level, standard symmetric collocation is employed. A convergence theory is given, which builds on recent theoretical advances for multiscale approximation using compactly supported radial basis functions. We are able to show that the convergence is linear in the number of levels. We also discuss the condition numbers of the arising systems and the effect of simple, diagonal preconditioners, now proving rigorously previous numerical observations
Decomposition of Optical Flow on the Sphere
We propose a number of variational regularisation methods for the estimation
and decomposition of motion fields on the -sphere. While motion estimation
is based on the optical flow equation, the presented decomposition models are
motivated by recent trends in image analysis. In particular we treat
decomposition as well as hierarchical decomposition. Helmholtz decomposition of
motion fields is obtained as a natural by-product of the chosen numerical
method based on vector spherical harmonics. All models are tested on time-lapse
microscopy data depicting fluorescently labelled endodermal cells of a
zebrafish embryo.Comment: The final publication is available at link.springer.co
Splines and Wavelets on Geophysically Relevant Manifolds
Analysis on the unit sphere found many applications in
seismology, weather prediction, astrophysics, signal analysis, crystallography,
computer vision, computerized tomography, neuroscience, and statistics.
In the last two decades, the importance of these and other applications
triggered the development of various tools such as splines and wavelet bases
suitable for the unit spheres , and the
rotation group . Present paper is a summary of some of results of the
author and his collaborators on generalized (average) variational splines and
localized frames (wavelets) on compact Riemannian manifolds. The results are
illustrated by applications to Radon-type transforms on and
.Comment: The final publication is available at http://www.springerlink.co
Extending the range of error estimates for radial approximation in Euclidean space and on spheres
We adapt Schaback's error doubling trick [R. Schaback. Improved error bounds
for scattered data interpolation by radial basis functions. Math. Comp.,
68(225):201--216, 1999.] to give error estimates for radial interpolation of
functions with smoothness lying (in some sense) between that of the usual
native space and the subspace with double the smoothness. We do this for both
bounded subsets of R^d and spheres. As a step on the way to our ultimate goal
we also show convergence of pseudoderivatives of the interpolation error.Comment: 10 page
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