Abstract
In this paper we introduce a fractal-based method over (complex-valued) Fourier transforms of functions with compact support \(X \subset \Re\). This method of “iterated Fourier transform systems” (IFTS) has a natural mathematical connection with the fractal-based method of “iterated function systems with greyscale maps” (IFSM) in the spatial domain [6,7]. A major motivation for our formulation is the problem of resolution enhancement of band-limited magnetic resonance images. In an attempt to minimize sampling/transform artifacts, it is our desire to work directly with the raw frequency data provided by an MR imager as much as possible before ‘“returning” to the spatial domain. In this paper, we show that our fractal-based IFTS method can be tailored to perform frequency extrapolation.
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Barnsley, M.F., Ervin, V., Hardin, D., Lancaster, J.: Solution of an inverse problem for fractals and other sets. Proc. Nat. Acad. Sci. 83, 1975–1977 (1986)
Barnsley, M.F., Hurd, L.P.: Fractal Image Compression. A.K. Peters, Wellesley, MA (1993)
Bracewell, R.: The Fourier Transform and its Applications, 2nd edn. McGraw-Hill, New York (1978)
Fisher, Y.: Fractal Image Compression. Springer, New York (1995)
Forte, B., Vrscay, E.R.: Solving the inverse problem for measures using iterated function systems: A new approach. Adv. Appl. Prob. 27, 800–820 (1995)
Forte, B., Vrscay, E.R.: Theory of generalized fractal transforms. In: Fisher, Y. (ed.) Fractal Image Encoding and Analysis. NATO ASI Series F, vol. 159, Springer, New York (1998)
Forte, B., Vrscay, E.R.: Inverse problem methods for generalized fractal transforms, In: Fractal Image Encoding and Analysis, ibid.
Gerchberg, R.W.: Super-resolution through Error Energy Reduction. Optica Acta 21(9), 709–720 (1974)
Haacke, M.E., Brown, R.W., Thompson, M.R., Venkatesan, R.: Magnetic Resonance Imaging: Physical Principles and Sequence Design. John Wiley & Sons, Inc, USA (1999)
Hinshaw, W., Lent, A.: An Introduction to NMR Imaging: From the Bloch Equation to the Imaging Equation. Proceedings of the IEEE 71(3), 338–350 (1983)
Jain, A., Ranganath, S.: Extrapolation Algorithms for Discrete Signals with Application in Spectral Estimation. IEEE Trans. ASSP 29(4), 830–845 (1981)
Liang, Z., Boada, F.E., Constable, R.R., Haacke, M.E., Lauterbur, P.C., Smith, M.R.: Constrained Reconstruction Methods in MR Imaging. Rev. Mag. Res. Med. 4, 67–185 (1992)
Liang, Z., Lauterbur, P.C.: Principles of Magnetic Resonance Imaging, A Signal Processing Perspective. IEEE Press, New York (2000)
Lu, N.: Fractal Imaging. Academic Press, New York (1997)
McGibney, G., Smith, M.R., Nichols, S.T., Crawley, A.: Quantitative Evaluation of Several Partial Fourier Reconstruction Algorithms Used in MRI. Mag. Res. Med. 30, 51–59 (1993)
Papoulis, A.: A New Algorithm in Spectral Analysis and Band-Limited Extrapolation. IEEE Trans. Cir. Sys. 22(9), 735–742 (1975)
Slepian, D., Pollack, H.O.: Prolate Spheroidal Wave Functions, Fourier Analysis and Uncertainty - I. Bell System Tech. J., pp. 43-63 (1961)
Youla, D.: Generalized Image Restoration by the Method of Alternating Orthogonal Projections. IEEE Trans. Cir. Sys. 25(9) (1978)
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Mayer, G.S., Vrscay, E.R. (2007). Iterated Fourier Transform Systems: A Method for Frequency Extrapolation. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_65
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DOI: https://doi.org/10.1007/978-3-540-74260-9_65
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