1997
DOI: 10.1006/jmaa.1997.5299
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Inversion of the Radon Transform on the Laguerre Hypergroup by using Generalized Wavelets

Abstract: We consider the Radon transform R , ␣ G 0, on the Laguerre hypergroup ␣ w w Ks 0, qϱ ‫.ޒ=‬ We characterize a space of infinitely differentiable and rapidly decreasing functions together with their derivatives such that R is a bijection ␣ from this space onto itself. We establish an inversion formula and a Plancherel theorem for the operator R . Finally, by using the continuous wavelet transform

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Cited by 60 publications
(46 citation statements)
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“…As basic references of the Laguerre hypergroup, we refer the reader to (M. Assal & H. Ben Abdallah, 2005; M. M. Nessibi & K. Trimeche, 1997).…”
Section: Preliminariesmentioning
confidence: 99%
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“…As basic references of the Laguerre hypergroup, we refer the reader to (M. Assal & H. Ben Abdallah, 2005; M. M. Nessibi & K. Trimeche, 1997).…”
Section: Preliminariesmentioning
confidence: 99%
“…We recall for (λ, m) ∈K and for a suitable function f : K −→ C, the Fourier-Laguerre transform is defined in (M. M. Nessibi & K. Trimeche, 1997;M. Assal & H. Ben Abdallah, 2005) by:…”
Section: Notationsmentioning
confidence: 99%
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“…In this section we set some notations and we recall some basic results in harmonic analysis related to Laguerre hypergroups (see [4][5][6]). …”
Section: Preliminarymentioning
confidence: 99%
“…Indeed, they have proved the same results given by Ludwig, Helgason and Solmon for the classical Radon transform on R 2 [15,21,26] and for the spherical mean operator in [23], more precisely they have established that the Riemann-Liouville operator and its dual are isomorphisms on some subspaces of S e (R 2 ) and they have provided their inversion formulas in terms of integro-differential operators. Herein, we invert R α and t R α using generalized wavelets associated to the Riemann-Liouville operator and classical wavelets (see [24,29]). These new expressions are advantageous because of the large choice of wavelets, that are recognized as a powerful new mathematical tool in many areas, for example signal and image processing, time series analysis, geophysics ( [8,[11][12][13]).…”
Section: Introductionmentioning
confidence: 99%