We construct frames of wavepackets produced by parabolic dilation, rotation and translation of (a finite sum of) Gaussians and give asymptotics on the analogue of Daubechies frame criterion. We show that the coefficients in the corresponding approximate expansion decay fast away from the wavefront set of the original data.
Closest to our work is the construction of curvelet-type expansions in @cite_36 . Whereas we construct frames by using an analogue of Daubechies criterion for wavelets, the curvelet-type frames for @math in @cite_36 are obtained by using a perturbation argument. The main focus of that work is the production of compactly-supported atoms, but the results also apply to sums of modulated Gaussians. As mentioned in [Section 6] rani12 , the perturbation argument yields a frame where each element is a linear combination of dilated, rotated and translated Gaussians. However, the coefficients in that linear combination depend on the indices of the particular frame element, but the number of terms is proved to be uniformly bounded. By contrast, the packets in consist exactly of parabolic dilations, rotations and translations of a function, which may be taken to be a fixed linear combination of Gaussians.
@cite_36
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We introduce atoms" as a variant of 2D wavelet packets obeying the parabolic scaling wavelength (diameter) 2 . We prove that warped oscillatory functions, a toy model for texture, have a signicantly sparser expansion in wave atoms than in other xed standard representations like wavelets, Gabor atoms, or curvelets. We propose a novel algorithm for a tight frame of wave atoms with redundancy two, directly in the frequency plane, by the " technique. We also propose variants of the basic transform for applications in image processing, including an orthonormal basis, and a shift-invariant tight frame with redundancy four. Sparsity and denoising experiments on both seismic and ngerprint images demonstrate the potential of the tool introduced. We study a flexible method for constructing curvelet-type frames. These curvelet-type systems have the same sparse representation properties as curvelets for appropriate classes of smooth functions, and the flexibility of the method allows us to give a constructive description of how to construct curvelet-type systems with a prescribed nature such as compact support in direct space. The method consists of using the machinery of almost diagonal matrices to show that a system of curvelet molecules which is sufficiently close to curvelets constitutes a frame for curvelet-type spaces. Such a system of curvelet molecules can then be constructed using finite linear combinations of shifts and dilates of a single function with sufficient smoothness and decay. This paper introduces new tight frames of curvelets to address the problem of finding optimally sparse representations of objects with discontinuities along piecewise C 2 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 C 2 except for discontinuities along piecewise C 2 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 C n obtained by selecting the n largest terms in the curvelet series obeys ∥f - f C n ∥ 2 L2 ≤ C . n -2 . (log n) 3 , n → ∞. This rate of convergence holds uniformly over a class of functions that are C 2 except for discontinuities along piecewise C 2 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. In this paper we present a construction of frames generated by a single band-limited function for decomposition smoothness spaces on ( R ^d ) of modulation and Triebel–Lizorkin type. A perturbation argument is then used to construct compactly supported frame generators.