Fast Computation by Subdivision of Multidimensional Splines and Their Applications

We present theory and algorithms for fast explicit computations of uniand multidimensional periodic splines of arbitrary order at triadic rational points and of splines of even order at diadic rational points. The algorithms use the forward and the inverse Fast Fourier transform (FFT). The implementation is as fast as FFT computation. The algorithms are based on binary and ternary subdivision of splines. Interpolating and smoothing splines are used for a sample rate convertor such as resolution upsampling of discrete-time signals and digital images and restoration of decimated images that were contaminated by noise. The performance of the rate conversion based spline is compared with the performance of the rate conversion by prolate spheroidal wave functions. Key words={Periodic splines, interpolating and smoothing splines, subdivision, rate convertor, restoration, upsampling, prolate spheroidal wave functions} AMS subject classification: 41A15, 65D07, 62D05

[1]  I. J. Schoenberg,et al.  SPLINE FUNCTIONS AND THE PROBLEM OF GRADUATION , 1964 .

[2]  J. Zak FINITE TRANSLATIONS IN SOLID-STATE PHYSICS. , 1967 .

[3]  Amir Averbuch,et al.  Spline-based deconvolution , 2009, Signal Process..

[4]  Yoel Shkolnisky,et al.  Approximation of bandlimited functions , 2006 .

[5]  V. Rokhlin,et al.  Prolate spheroidal wavefunctions, quadrature and interpolation , 2001 .

[6]  I. Johnstone,et al.  Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .

[7]  Valery A. Zheludev,et al.  Periodic Splines, Harmonic Analysis, and Wavelets , 1998 .

[8]  A. Averbuch,et al.  Deconvolution by matching pursuit using spline wavelet packets dictionaries , 2011 .

[9]  J. L. Walsh,et al.  The theory of splines and their applications , 1969 .

[10]  Amir Averbuch,et al.  Block Based Deconvolution Algorithm Using Spline Wavelet Packets , 2010, Journal of Mathematical Imaging and Vision.

[11]  D. Donev Prolate Spheroidal Wave Functions , 2017 .

[12]  Mj Martin Bastiaans Gabor's expansion and the Zak transform for continuous-time and discrete-time signals : critical sampling and rational oversampling , 1995 .

[13]  Nira Dyn,et al.  Analysis of uniform binary subdivision schemes for curve design , 1991 .

[14]  Nira Dyn Analysis of Convergence and Smoothness by the Formalism of Laurent Polynomials , 2002, Tutorials on Multiresolution in Geometric Modelling.

[15]  Valery A. Zheludev,et al.  Interpolatory subdivision schemes with infinite masks originated from splines , 2006, Adv. Comput. Math..

[16]  D. Levin,et al.  Subdivision schemes in geometric modelling , 2002, Acta Numerica.

[17]  V. Rokhlin,et al.  Prolate Spheroidal Wave Functions of Order Zero , 2013 .

[18]  Martin Vetterli,et al.  Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..

[19]  D. Slepian,et al.  Prolate spheroidal wave functions, fourier analysis and uncertainty — II , 1961 .

[20]  Neil A. Dodgson,et al.  An interpolating 4-point C2 ternary stationary subdivision scheme , 2002, Comput. Aided Geom. Des..

[21]  D. L. Donoho,et al.  Ideal spacial adaptation via wavelet shrinkage , 1994 .

[22]  Anton,et al.  A Ternary 4-Point Approximating Subdivision Scheme , 2012 .

[23]  Vladimir Rokhlin,et al.  Approximate formulae for certain prolate spheroidal wave functions valid for large values of both order and band-limit , 2007 .

[24]  Ewald Quak,et al.  Tutorials on Multiresolution in Geometric Modelling, Summer School Lecture Notes , 2002 .

[25]  Shang Xiao,et al.  Adaptive Wavelet Thresholding for Image Denoising , 2003 .

[26]  John C. Holladay,et al.  A smoothest curve approximation , 1957 .

[27]  Amir Averbuch,et al.  Ternary interpolatory Subdivision Schemes Originated from splines , 2011, Int. J. Wavelets Multiresolution Inf. Process..