Quasi-tight Framelets with Directionality or High Vanishing Moments Derived from Arbitrary Refinable Functions

Construction of multivariate tight framelets is known to be a challenging problem. Multivariate dual framelets with vanishing moments generalize tight framelets and are not easy to be constructed either. Compactly supported multivariate framelets with directionality or high vanishing moments are of interest and importance in both theory and applications. In this paper we introduce the notion of a quasi-tight framelet, which is a dual framelet, but behaves almost like a tight framelet. Let $\phi\in L_2(R^d)$ be an arbitrary compactly supported $M$-refinable function such that its underlying low-pass filter satisfies the basic sum rule. We first constructively prove by a step-by-step algorithm that we can always easily derive from the arbitrary $M$-refinable function $\phi$ a directional compactly supported quasi-tight $M$-framelet in $L_2(R^d)$ associated with a directional quasi-tight $M$-framelet filter bank, each of whose high-pass filters has only two nonzero coefficients with opposite signs. If in addition all the coefficients of its low-pass filter are nonnegative, such a quasi-tight $M$-framelet becomes a directional tight $M$-framelet in $L_2(R^d)$. Furthermore, we show by a constructive algorithm that we can always derive from the arbitrary $M$-refinable function $\phi$ a compactly supported quasi-tight $M$-framelet in $L_2(R^d)$ with the highest possible order of vanishing moments. We shall also present a result on quasi-tight framelets whose associated high-pass filters are purely differencing filters with the highest order of vanishing moments. Several examples will be provided to illustrate our main theoretical results and algorithms in this paper.

[1]  Maria Charina,et al.  An Algebraic Perspective on Multivariate Tight Wavelet Frames , 2013, Constructive Approximation.

[2]  Zhenpeng Zhao,et al.  Tensor Product Complex Tight Framelets with Increasing Directionality , 2013, SIAM J. Imaging Sci..

[3]  Ming-Jun Lai,et al.  Construction of multivariate compactly supported tight wavelet frames , 2006 .

[4]  E. Candès,et al.  New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities , 2004 .

[5]  R. A. Zalik,et al.  Some Smooth Compactly Supported Tight Wavelet Frames with Vanishing Moments , 2016 .

[6]  I. Daubechies,et al.  Framelets: MRA-based constructions of wavelet frames☆☆☆ , 2003 .

[7]  D. Labate,et al.  Sparse Multidimensional Representations using Anisotropic Dilation and Shear Operators , 2006 .

[8]  Martin Vetterli,et al.  Nonseparable Multidimensional Perfect Reconstruction Filter Banks and , 1992 .

[9]  Gitta Kutyniok,et al.  Shearlets: Multiscale Analysis for Multivariate Data , 2012 .

[10]  B. Han On Dual Wavelet Tight Frames , 1997 .

[11]  Bin Han,et al.  Symmetric canonical quincunx tight framelets with high vanishing moments and smoothness , 2015, Math. Comput..

[12]  B. Han Nonhomogeneous Wavelet Systems in High Dimensions , 2010, 1002.2421.

[13]  Richard Baraniuk,et al.  The Dual-tree Complex Wavelet Transform , 2007 .

[14]  I. Daubechies Ten Lectures on Wavelets , 1992 .

[15]  B. Han,et al.  Smooth affine shear tight frames with MRA structure , 2013, 1308.6205.

[16]  C. Chui,et al.  Compactly supported tight and sibling frames with maximum vanishing moments , 2001 .

[17]  B. Han The Projection Method for Multidimensional Framelet and Wavelet Analysis , 2014 .

[18]  Bin Han,et al.  Algorithm for constructing symmetric dual framelet filter banks , 2014, Math. Comput..

[19]  M. Ehler On Multivariate Compactly Supported Bi-Frames , 2007 .

[20]  M. Skopina C A ] 1 8 A pr 2 00 7 Multivariate Wavelet Frames 1 , 2008 .

[21]  B. Han Compactly supported tight wavelet frames and orthonormal wavelets of exponential decay with a general dilation matrix , 2003 .

[22]  Qingtang Jiang,et al.  Tight wavelet frames in low dimensions with canonical filters , 2015, J. Approx. Theory.

[23]  B. Han,et al.  Pairs of Dual Wavelet Frames from Any Two Refinable Functions , 2004 .

[24]  M. Skopina On construction of multivariate wavelet frames , 2009 .

[25]  Zuowei Shen,et al.  Dual Gramian analysis: Duality principle and unitary extension principle , 2015, Math. Comput..

[26]  I. Daubechies,et al.  PAINLESS NONORTHOGONAL EXPANSIONS , 1986 .

[27]  Charles K. Chui,et al.  Construction of Multivariate Tight Frames via Kronecker Products , 2001 .

[28]  Bin Han,et al.  Vector cascade algorithms and refinable function vectors in Sobolev spaces , 2003, J. Approx. Theory.

[29]  Raymond H. Chan,et al.  An Adaptive Directional Haar Framelet-Based Reconstruction Algorithm for Parallel Magnetic Resonance Imaging , 2016, SIAM J. Imaging Sci..

[30]  Bin Han Framelets and Wavelets , 2017 .

[31]  M. Ehler,et al.  Applied and Computational Harmonic Analysis , 2015 .

[32]  Tao Li,et al.  Directional Compactly supported Box Spline Tight Framelets with Simple Structure , 2017, ArXiv.

[33]  Amos Ron,et al.  L-CAMP: Extremely Local High-Performance Wavelet Representations in High Spatial Dimension , 2008, IEEE Transactions on Information Theory.

[34]  Rong-Qing Jia,et al.  Approximation properties of multivariate wavelets , 1998, Math. Comput..

[35]  Zuowei Shen,et al.  Compactly supported tight affine spline frames in L2(Rd) , 1998, Math. Comput..

[36]  A. Ron,et al.  Affine Systems inL2(Rd): The Analysis of the Analysis Operator , 1997 .