Poisson Wavelets on the Sphere

In this article we summarize the basic formulas of wavelet analysis with the help of Poisson wavelets on the sphere. These wavelets have the nice property that all basic formulas of wavelet analysis as reproducing kernels, etc. may be expressed simply with the help of higher degree Poisson wavelets. This makes them numerically attractive for applications in geophysical modeling.     

Biorthogonal Locally Supported Wavelets on the Sphere Based on Zonal Kernel Functions

This article presents a method for approximating spherical functions from discrete data of a block-wise grid structure. The essential ingredients of the approach are scaling and wavelet functions within a biorthogonalisation process generated by locally supported zonal kernel functions. In consequence, geophysically and geodetically relevant problems involving rotationinvariant pseudodifferential operators become attackable. A multiresolution analysis is formulated enabling a fast wavelet transform similar to the algorithms known from classical tensor product wavelet theory.     

Orthogonal Zonal, Tesseral and Sectorial Wavelets on the Sphere for the Analysis of Satellite Data

The spherical harmonics Y _n,k } _{n=0,1,...;k=?n,...,n} represent a standard complete orthonormal system in ?²(Ω), where Ω is the unit sphere. In view of present and future satellite missions (e.g., for the determination of the Earth's gravity field) it is of particular importance to treat the different accuracies and sizes of data in dependence of the index pairs (n,k). It is, e.g., known that the GOCE mission yields essentially less accurate data in the zonal (k=0) case. Therefore, this paper presents new ways of constructing multiresolutions for a Sobolev space of functions on Ω allowing the separate treatment of certain classes of pairs (n,k) and, in particular, the separate treatment of different orders k. Orthogonal bandlimited as well as non-bandlimited detail and scale spaces adapted to certain (geo)scientific problems and to the character of the given data can now be used. Finally, an explicit representation of a non-bandlimited wavelet on Ω yielding an orthogonal decomposition of the function space is calculated for the first time.     

Spline Wavelets on the Unit Circle

An orthonormal wavelet basis on the circle γ is constructed. By estabishing some new theorems on complex spline functions, the $\mathop L\limits^ \circ _2 (I)$ space can be decomposed into different orthogonal subspaces. Formulas of decomposition and reconstruction imply only two terms.     

Rational Points on the Sphere

Using only basic tools from the theory of modular forms, the rational points of bounded height on the sphere are counted and shown to be uniformly distributed. The more difficult case of points with a given height is also treated.     

Polyharmonic Approximation on the Sphere

The purpose of this article is to provide new error estimates for a popular type of spherical basis function (SBF) approximation on the sphere: approximating by linear combinations of Green’s functions of polyharmonic differential operators. We show that the L _p approximation order for this kind of approximation is σ for functions having L _p smoothness σ (for σ up to the order of the underlying differential operator, just as in univariate spline theory). This improves previous error estimates, which penalized the approximation order when measuring error in L _p , p>2 and held only in a restrictive setting when measuring error in L _p , p<2.     

Discrepancy Estimates on the Sphere

 For measures on the unit sphere in ℝ ^d , d≥3, we derive discrepancy estimates in terms of the quality of corresponding quadrature formulas and in terms of bounds for potential differences. (Received 1 August 1998; in revised form 30 December 1998)     

Riemann Localisation on the Sphere

This paper first shows that the Riemann localisation property holds for the Fourier-Laplace series partial sum for sufficiently smooth functions on the two-dimensional sphere, but does not hold for spheres of higher dimension. By Riemann localisation on the sphere \(\mathbb {S}^{d}\subset \mathbb {R}^{d+1}\), \(d\ge 2\), we mean that for a suitable subset X of \(\mathbb {L}_{p}(\mathbb {S}^{d})\), \(1\le p\le \infty \), the \(\mathbb {L}_{p}\)-norm of the Fourier local convolution of \(f\in X\) converges to zero as the degree goes to infinity. The Fourier local convolution of f at \(\mathbf {x}\in \mathbb {S}^{d}\) is the Fourier convolution with a modified version of f obtained by replacing values of f by zero on a neighbourhood of \(\mathbf {x}\). The failure of Riemann localisation for \(d>2\) can be overcome by considering a filtered version: we prove that for a sphere of any dimension and sufficiently smooth filter the corresponding local convolution always has the Riemann localisation property. Key tools are asymptotic estimates of the Fourier and filtered kernels.     

Discrepancy Estimates on the Sphere

 For measures on the unit sphere in ℝ ^d , d≥3, we derive discrepancy estimates in terms of the quality of corresponding quadrature formulas and in terms of bounds for potential differences.     

Wavelets Based on Orthogonal Polynomials

We present a unified approach for the construction of polynomial wavelets. Our main tool is orthogonal polynomials. With the help of their properties we devise schemes for the construction of time localized polynomial bases on bounded and unbounded subsets of the real line. Several examples illustrate the new approach.

     

Wavelets on the Two-Sphere and Other Conic Sections

We survey the construction of the continuous wavelet transform (CWT) on the twosphere. Then we discuss the discretization of the spherical CWT, obtaining various types of discrete frames. Finally, we give some indications on the construction of a CWT on other conic sections.     

Minkowski Circle Packings on the Sphere

We consider n caps on the sphere such that none of them contains in its interior the center of another. We give an upper bound for the total area of the caps, which is sharp for n = 3 , 4, 6, and 12 and is asymptotically sharp for great values of n . Received September 11, 1997, and in revised form March 2, 1998.     

A Note on Wavelets and Diffusions

Motivated by image processing and numerical wavelet methods for partial differential equations, we study the theoretical interactions between wavelets and the diffusion equations. Important properties of wavelets, such as the translation and scaling invariance, the p-vanishing-moment condition, and the atomic decomposition, are integrated into the diffusion process and lead to many interesting results.     

Wavelets on fractals and besov spaces

Wavelets on self-similar fractals are introduced. It is shown that for certain totally disconnected fractals, function spaces may be characterized by means of the magnitude of the wavelet coefficients of the functions.     

Wavelets from the Loop Scheme

Anewwavelet-based geometric mesh compression algorithm was developed recently in the area of computer graphics by Khodakovsky, Schröder, and Sweldens in their interesting article [23]. The new wavelets used in [23] were designed from the Loop scheme by using ideas and methods of [26, 27], where orthogonal wavelets with exponential decay and pre-wavelets with compact support were constructed. The wavelets have the same smoothness order as that of the basis function of the Loop scheme around the regular vertices which has a continuous second derivative; the wavelets also have smaller supports than those wavelets obtained by constructions in [26, 27] or any other compactly supported biorthogonal wavelets derived from the Loop scheme (e.g., [11, 12]). Hence, the wavelets used in [23] have a good time frequency localization. This leads to a very efficient geometric mesh compression algorithm as proposed in [23]. As a result, the algorithm in [23] outperforms several available geometric mesh compression schemes used in the area of computer graphics. However, it remains open whether the shifts and dilations of the wavelets form a Riesz basis of L₂(?²). Riesz property plays an important role in any wavelet-based compression algorithm and is critical for the stability of any wavelet-based numerical algorithms. We confirm here that the shifts and dilations of the wavelets used in [23] for the regular mesh, as expected, do indeed form a Riesz basis of L₂(?²) by applying the more general theory established in this article.     

Isomorphism in Wavelets

Journal of Fourier Analysis and Applications - Two scaling functions $$\varphi _A$$ and $$\varphi _B$$ for Parseval frame wavelets are algebraically isomorphic, $$\varphi _A \simeq \varphi _B$$, if...