10,087 research outputs found
Introductory clifford analysis
In this chapter an introduction is given to Clifford analysis and the underlying Clifford algebras. The functions under consideration are defined on Euclidean space and take values in the universal real or complex Clifford algebra, the structure and properties of which are also recalled in detail. The function theory is centered around the notion of a monogenic function, which is a null solution of a generalized Cauchy–Riemann operator, which is rotation invariant and factorizes the Laplace operator. In this way, Clifford analysis may be considered as both a generalization to higher dimension of the theory of holomorphic functions in the complex plane and a refinement of classical harmonic analysis. A notion of monogenicity may also be associated with the vectorial part of the Cauchy–Riemann operator, which is called the Dirac operator; some attention is paid to the intimate relation between both notions. Since a product of monogenic functions is, in general, no longer monogenic, it is crucial to possess some tools for generating monogenic functions: such tools are provided by Fueter’s theorem on one hand and the Cauchy–Kovalevskaya extension theorem on the other hand. A corner stone in this function theory is the Cauchy integral formula for representation of a monogenic function in the interior of its domain of monogenicity. Starting from this representation formula and related integral formulae, it is possible to consider integral transforms such as Cauchy, Hilbert, and Radon transforms, which are important both within the theoretical framework and in view of possible applications
A range description for the planar circular Radon transform
The transform considered in the paper integrates a function supported in the
unit disk on the plane over all circles centered at the boundary of this disk.
Such circular Radon transform arises in several contemporary imaging
techniques, as well as in other applications. As it is common for transforms of
Radon type, its range has infinite co-dimension in standard function spaces.
Range descriptions for such transforms are known to be very important for
computed tomography, for instance when dealing with incomplete data, error
correction, and other issues. A complete range description for the circular
Radon transform is obtained. Range conditions include the recently found set of
moment type conditions, which happens to be incomplete, as well as the rest of
conditions that have less standard form. In order to explain the procedure
better, a similar (non-standard) treatment of the range conditions is described
first for the usual Radon transform on the plane.Comment: submitted for publicatio
Scale-discretised ridgelet transform on the sphere
We revisit the spherical Radon transform, also called the Funk-Radon
transform, viewing it as an axisymmetric convolution on the sphere. Viewing the
spherical Radon transform in this manner leads to a straightforward derivation
of its spherical harmonic representation, from which we show the spherical
Radon transform can be inverted exactly for signals exhibiting antipodal
symmetry. We then construct a spherical ridgelet transform by composing the
spherical Radon and scale-discretised wavelet transforms on the sphere. The
resulting spherical ridgelet transform also admits exact inversion for
antipodal signals. The restriction to antipodal signals is expected since the
spherical Radon and ridgelet transforms themselves result in signals that
exhibit antipodal symmetry. Our ridgelet transform is defined natively on the
sphere, probes signal content globally along great circles, does not exhibit
blocking artefacts, supports spin signals and exhibits an exact and explicit
inverse transform. No alternative ridgelet construction on the sphere satisfies
all of these properties. Our implementation of the spherical Radon and ridgelet
transforms is made publicly available. Finally, we illustrate the effectiveness
of spherical ridgelets for diffusion magnetic resonance imaging of white matter
fibers in the brain.Comment: 5 pages, 4 figures, matches version accepted by EUSIPCO, code
available at http://www.s2let.or
On Radon transforms on tori
We show injectivity of the X-ray transform and the -plane Radon transform
for distributions on the -torus, lowering the regularity assumption in the
recent work by Abouelaz and Rouvi\`ere. We also show solenoidal injectivity of
the X-ray transform on the -torus for tensor fields of any order, allowing
the tensors to have distribution valued coefficients. These imply new
injectivity results for the periodic broken ray transform on cubes of any
dimension.Comment: 13 page
Fast hyperbolic Radon transform represented as convolutions in log-polar coordinates
The hyperbolic Radon transform is a commonly used tool in seismic processing,
for instance in seismic velocity analysis, data interpolation and for multiple
removal. A direct implementation by summation of traces with different moveouts
is computationally expensive for large data sets. In this paper we present a
new method for fast computation of the hyperbolic Radon transforms. It is based
on using a log-polar sampling with which the main computational parts reduce to
computing convolutions. This allows for fast implementations by means of FFT.
In addition to the FFT operations, interpolation procedures are required for
switching between coordinates in the time-offset; Radon; and log-polar domains.
Graphical Processor Units (GPUs) are suitable to use as a computational
platform for this purpose, due to the hardware supported interpolation routines
as well as optimized routines for FFT. Performance tests show large speed-ups
of the proposed algorithm. Hence, it is suitable to use in iterative methods,
and we provide examples for data interpolation and multiple removal using this
approach.Comment: 21 pages, 10 figures, 2 table
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