Representation of Fourier Integral Operators Using Shearlets

Traditional methods of time-frequency and multiscale analysis, such as wavelets and Gabor frames, have been successfully employed for representing most classes of pseudodifferential operators. However, these methods are not equally effective in dealing with Fourier Integral Operators in general. In this article, we show that the shearlets, recently introduced by the authors and their collaborators, provide very efficient representations for a large class of Fourier Integral Operators. The shearlets are an affine-like system of well-localized waveforms at various scales, locations and orientations, which are particularly efficient in representing anisotropic functions. Using this approach, we prove that the matrix representation of a Fourier Integral Operator with respect to a Parseval frame of shearlets is sparse and well-organized. This fact recovers a similar result recently obtained by Candès and Demanet using curvelets, which illustrates the benefits of directional multiscale representations (such as curvelets and shearlets) in the study of those functions and operators where traditional multiscale methods are unable to provide the appropriate geometric analysis in the phase space. The second author was supported in part by a National Science Foundation grant DMS 0604561.     

Directional Haar wavelet frames on triangles

Traditional wavelets are not very effective in dealing with images that contain orientated discontinuities (edges). To achieve a more efficient representation one has to use basis elements with much higher directional sensitivity. In recent years several approaches like curvelets and shearlets have been studied providing essentially optimal approximation properties for images that are piecewise smooth and have discontinuities along C²-curves. While curvelets and shearlets have compact support in frequency domain, we construct directional wavelet frames generated by functions with compact support in time domain. Our Haar wavelet constructions can be seen as special composite dilation wavelets, being based on a generalized multiresolution analysis (MRA) associated with a dilation matrix and a finite collection of ‘shear’ matrices. The complete system of constructed wavelet functions forms a Parseval frame. Based on this MRA structure we provide an efficient filter bank algorithm. The freedom obtained by the redundancy of the applied Haar functions will be used for an efficient sparse representation of piecewise constant images as well as for image denoising.     

Compactly supported shearlets are optimally sparse

Cartoon-like images, i.e., C² functions which are smooth apart from a C² discontinuity curve, have by now become a standard model for measuring sparse (nonlinear) approximation properties of directional representation systems. It was already shown that curvelets, contourlets, as well as shearlets do exhibit sparse approximations within this model, which are optimal up to a log-factor. However, all those results are only applicable to band-limited generators, whereas, in particular, spatially compactly supported generators are of uttermost importance for applications.In this paper, we present the first complete proof of optimally sparse approximations of cartoon-like images by using a particular class of directional representation systems, which indeed consists of compactly supported elements. This class will be chosen as a subset of (non-tight) shearlet frames with shearlet generators having compact support and satisfying some weak directional vanishing moment conditions.     

The curvelet representation of wave propagators is optimally sparse

This paper argues that curvelets provide a powerful tool for representing very general linear symmetric systems of hyperbolic differential equations. Curvelets are a recently developed multiscale system [7, 9] in which the elements are highly anisotropic at fine scales, with effective support shaped according to the parabolic scaling principle width ≈ length² at fine scales. We prove that for a wide class of linear hyperbolic differential equations, the curvelet representation of the solution operator is both optimally sparse and well organized.

• It is sparse in the sense that the matrix entries decay nearly exponentially fast (i.e., faster than any negative polynomial) and
• well organized in the sense that the very few nonnegligible entries occur near a few shifted diagonals.

Indeed, we show that the wave group maps each curvelet onto a sum of curveletlike waveforms whose locations and orientations are obtained by following the different Hamiltonian flows—hence the diagonal shifts in the curvelet representation. A physical interpretation of this result is that curvelets may be viewed as coherent waveforms with enough frequency localization so that they behave like waves but at the same time, with enough spatial localization so that they simultaneously behave like particles. © 2005 Wiley Periodicals, Inc.     

The nonexistence of shearlet scaling functions

Over the past five years, the directional representation system of shearlets has received much attention and has been shown to exhibit many advantageous properties. Over this time period, there have been a number of attempts to associate shearlet systems with a multiresolution analysis (MRA). However, one can argue that, in each of these attempts, the following statement regarding the resulting shearlet MRA notion is inaccurate: “There exist scaling functions satisfying various desirable properties, such as significant amounts of decay or regularity, nonnegativity, or advantageous refinement or representation conditions. Each such scaling function naturally induces an associated shearlet (either traditional or cone-adapted) that satisfies similar desirable properties. Each such scaling function/associated shearlet pair rationally induces a fast decomposition algorithm for discrete data.” In this article, we attempt to provide explanation for this situation by arguing the great difficulty of associating shearlet systems with such an MRA. We do so by considering two very natural and general notions of shearlet MRA—one which leads to traditional shearlets and one which leads to cone-adapted shearlets—each of which seems to be an excellent candidate to satisfy the above quoted statement. For each of these notions, we prove the nonexistence of associated scaling functions satisfying the above mentioned desirable properties.     

Dualizable Shearlet Frames and Sparse Approximation

Shearlet systems have been introduced as directional representation systems, which provide optimally sparse approximations of a certain model class of functions governed by anisotropic features while allowing faithful numerical realizations by a unified treatment of the continuum and digital realm. They are redundant systems, and their frame properties have been extensively studied. In contrast to certain band-limited shearlets, compactly supported shearlets provide high spatial localization but do not constitute Parseval frames. Thus reconstruction of a signal from shearlet coefficients requires knowledge of a dual frame. However, no closed and easily computable form of any dual frame is known. In this paper, we introduce the class of dualizable shearlet systems, which consist of compactly supported elements and can be proved to form frames for \(L^2({\mathbb {R}}^2)\). For each such dualizable shearlet system, we then provide an explicit construction of an associated dual frame, which can be stated in closed form and is efficiently computed. We also show that dualizable shearlet frames still provide near optimal sparse approximations of anisotropic features.     

Curvelets and Fourier Integral Operators

A recent body of work introduced new tight-frames of curvelets E. Candès, D. Donoho, in: (i) Curvelets – a suprisingly effective nonadaptive representation for objects with edges (A. Cohen, C. Rabut, L. Schumaker (Eds.)), Vanderbilt University Press, Nashville, 2000, pp. 105–120; (ii) http://www.acm.caltech.edu/~emmanuel/publications.html, 2002 to address key problems in approximation theory and image processing. This paper shows that curvelets essentially provide optimally sparse representations of Fourier Integral Operators. To cite this article: E. Candès, L. Demanet, C. R. Acad. Sci. Paris, Ser. I 336 (2003).     

Partial regularity for subquadratic parabolic systems with continuous coefficients

We establish the partial regularity of solutions to quasilinear parabolic systems with elliptic part that grows subquadratically. More precisely, it is shown that there is an open subset with full measure, of the solution’s domain, on which the solution is H?lder continuous. A key feature in this article is that we only require the coefficients of the system to be continuous with respect to the first two arguments. To prove the result, we use the A-caloric approximation method and an intrinsic scaling. To accommodate the subquadratic growth an adaptation of the A-caloric approximation lemma is also provided.     

Detection of Singularities by Discrete Multiscale Directional Representations

One of the most remarkable properties of the continuous curvelet and shearlet transforms is their sensitivity to the directional regularity of functions and distributions. As a consequence of this property, these transforms can be used to characterize the geometry of edge singularities of functions and distributions by their asymptotic decay at fine scales. This ability is a major extension of the conventional continuous wavelet transform which can only describe pointwise regularity properties. However, while in the case of wavelets it is relatively easy to relate the asymptotic properties of the continuous transform to properties of discrete wavelet coefficients, this problem is surprisingly challenging in the case of discrete curvelets and shearlets where one wants to handle also the geometry of the singularity. No result for the discrete case was known so far. In this paper, we derive non-asymptotic estimates showing that discrete shearlet coefficients can detect, in a precise sense, the location and orientation of curvilinear edges. We discuss connections and implications of this result to sparse approximations and other applications.     

New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities

This paper introduces new tight frames of curvelets to address the problem of finding optimally sparse representations of objects with discontinuities along piecewise C² edges. Conceptually, the curvelet transform is a multiscale pyramid with many directions and positions at each length scale, and needle‐shaped elements at fine scales. These elements have many useful geometric multiscale features that set them apart from classical multiscale representations such as wavelets. For instance, curvelets obey a parabolic scaling relation which says that at scale 2^?j, each element has an envelope that is aligned along a “ridge” of length 2^?j/2 and width 2^?j. We prove that curvelets provide an essentially optimal representation of typical objects f that are C² except for discontinuities along piecewise C² curves. Such representations are nearly as sparse as if f were not singular and turn out to be far more sparse than the wavelet decomposition of the object. For instance, the n‐term partial reconstruction f obtained by selecting the n largest terms in the curvelet series obeys This rate of convergence holds uniformly over a class of functions that are C² except for discontinuities along piecewise C² curves and is essentially optimal. In comparison, the squared error of n‐term wavelet approximations only converges as n^?1 as n → ∞, which is considerably worse than the optimal behavior. © 2003 Wiley Periodicals, Inc.     

Bessel变换的一个下界

Bessel逆问题在物理、化学和工程学等诸多领域有重要应用.解决线性逆问题的传统方法不适合处理具有奇异性曲线边缘的二元函数.鉴于切波对这一类函数的最优表示能力,相关文献采用切波方法研究Bessel逆问题,构造了目标函数的切波域值估计器,得到了它在函数空间V中积分均方差收敛阶的上界.在此基础上利用统计理论给出其最小最大风险的一个下界,证明了在估计Bessel逆问题时此估计器是最优的.     

Weak convergence of finite element approximations of linear stochastic evolution equations with additive noise II. Fully discrete schemes

We present an abstract framework for analyzing the weak error of fully discrete approximation schemes for linear evolution equations driven by additive Gaussian noise. First, an abstract representation formula is derived for sufficiently smooth test functions. The formula is then applied to the wave equation, where the spatial approximation is done via the standard continuous finite element method and the time discretization via an I-stable rational approximation to the exponential function. It is found that the rate of weak convergence is twice that of strong convergence. Furthermore, in contrast to the parabolic case, higher order schemes in time, such as the Crank-Nicolson scheme, are worthwhile to use if the solution is not very regular. Finally we apply the theory to parabolic equations and detail a weak error estimate for the linearized Cahn-Hilliard-Cook equation as well as comment on the stochastic heat equation.     

Multiplicative Representation of a Hyperbolic non Distributive Algebra

The multiplicative or polar representation of hyperbolic scator algebra in 1 + n dimensions is introduced. The transformations between additive and multiplicative representations are presented. The addition and product operations are consistently defined in either representation using additive or multiplicative variables. The product is shown to produce a rotation and scaling for equal director components and solely a scaling in the orthogonal components.     

The exponential dichotomy on general approximation scheme

This paper is devoted to the numerical analysis of abstract parabolic problems u′(t) = Au(t), u(0) = u ⁰ with hyperbolic generator A. We develop a general approach to establish a discrete dichotomy in a very general setting in the case of discrete approximation in space and time. It is a well-known fact that the phase space in the neighborhood of the hyperbolic equilibrium can be split in such a way that the original initial value problem is reduced to initial value problems with exponentially decaying solutions in opposite time directions. We use the theory of compact approximation principle and collectively condensing approximation to show that such a decomposition of the flow persists under rather general approximation schemes. The main assumption of our results are naturally satisfied, in particular, for operators with compact resolvents and condensing semigroups and can be verified for the finite element method as well as finite difference methods.     

Blow-up rates for higher-order semilinear parabolic equations and systems and some Fujita-type theorems

In this paper, we derive blow-up rates for higher-order semilinear parabolic equations and systems. Our proof is by contradiction and uses a scaling argument. This procedure reduces the problems of blow-up rate to Fujita-type theorems. In addition, we also give some new Fujita-type theorems for higher-order semilinear parabolic equations and systems with the time variable on R. These results are not restricted to positive solutions.     

Analysis of edge and corner points using parabolic dictionaries

Last decade saw the creation of a number of directional representation dictionaries that desire to address the weaknesses of the classical wavelet transform that arise due to its limited capacity for the analysis of edge-like features of two-dimensional signals. Salient features of these dictionaries are directional selectivity and anisotropic treatment of the axes, achieved through the parabolic scaling law. In this paper we will examine the adequacy of such dictionaries for the analysis of edge- and corner-like features of 2D regions through a comprehensive framework for directional parabolic dictionaries, called the continuous parabolic molecules. This work builds on a family of earlier studies and aims to give a broader perspective through the level of generality.     

A parabolic variant of H-measures

H-measures, as originally introduced by Luc Tartar and Patrick Gérard, are suited to hyperbolic problems. However, they turned out not to be well adjusted to the study of parabolic equations. A variant of H-measures is proposed, which is much better adapted to such kind of problems. We present the new parabolic scaling and the main ingredients for the proof of existence of the new variant. Some applications to the Schrödinger equation and vibrating plate equation are shown, together with an outlook to possible applications in other problems.     

Knapp-Wallach Szegö integrals and generalized principal series representations: The parabolic rank one case

To each discrete series representation of a connected semisimple Lie group G with finite center, a G-equivariant embedding into a generalized principal series representation is given. This representation is induced from specified parameters on a maximal parabolic subgroup of G and the mapping is defined by an integral formula, analogous to the Szegö integral introduced by Knapp and Wallach for a minimal parabolic subgroup. In a limiting case, embeddings of limits of discrete series representations are obtained and used to exhibit a reducibility theorem.     

Inexact constraint preconditioners for linear systems arising in interior point methods

Issues of indefinite preconditioning of reduced Newton systems arising in optimization with interior point methods are addressed in this paper. Constraint preconditioners have shown much promise in this context. However, there are situations in which an unfavorable sparsity pattern of Jacobian matrix may adversely affect the preconditioner and make its inverse representation unacceptably dense hence too expensive to be used in practice. A remedy to such situations is proposed in this paper. An approximate constraint preconditioner is considered in which sparse approximation of the Jacobian is used instead of the complete matrix. Spectral analysis of the preconditioned matrix is performed and bounds on its non-unit eigenvalues are provided. Preliminary computational results are encouraging.     

Totally interpolating biorthogonal multiwavelet systems with approximation order

In this article, compactly supported totally interpolating biorthogonal multiwavelet systems are studied. Necessary and sufficient conditions for such systems to have given approximation orders are stated in simple equations. It is shown that the shorter nontrivial filter component that has the minimum possible length for a given approximation order is uniquely determined up to a discrete parameter. Among systems with such property, we provide all totally interpolating biorthogonal stable multiwavelet systems of approximation orders 2 and 3 with minimal total length whose scaling vectors have minimal lengths as well.