No abstract

A stationary Poisson cylinder process in the d-dimensional Euclidean space is composed of a stationary Poisson process of k-flats (0 ≤ k ≤ d−1) which are dilated by independent and identically distributed random compact cylinder bases taken from the corresponding (d−k)-dimensional orthogonal complement. If the second moment of the (d−k)-volume of the typical cylinder base exists, we prove asymptotic normality of the d-volume of the union set of Poisson cylinders that covers an expanding star-shaped domain ϱ W as ϱ grows unboundedly. Due to the long-range dependencies within the union set of cylinders, the variance of its d-volume in ϱ W increases asymptotically proportional to the (d+k) th power of ϱ. To obtain the exact asymptotic behaviour of this variance, we need a distinction between discrete and continuous directional distributions of the typical k-flat. A corresponding central limit theorem for the surface content is stated at the end.

We consider two integral transforms which are frequently used in integral geometry and related fields, namely the cosine and the spherical Radon transform. Fast algorithms are developed which invert the respective transforms in a numerically stable way. So far, only theoretical inversion formulas or algorithms for atomic measures have been derived, which are not so important for applications. We focus on the two and threedimensional case, where we also show that our method leads to a regularization. Numerical results are presented and show the validity of the resulting algorithms. First, we use synthetic data for the inversion of the Radon transform. Then we apply the algorithm for the inversion of the cosine transform to reconstruct the directional distribution of line processes from finitely many intersections of their lines with test lines (2D) or planes (3D), respectively. Finally we apply our method to analyze a series of microscopic two-and three-dimensional images of a fibre system.

Main characteristics of stationary anisotropic Poisson processes of cylinders (dilated k-dimensional flats) in d-dimensional Euclidean space are studied. Explicit formulae for the capacity functional, the covariance function, the contact distribution function, the volume fraction, and the intensity of the surface area measure are given which can be used directly in applications.

The focus of this paper is on the numerical inversion of two integral transforms, namely the spherical Radon and the cosine transform. Both transforms are frequently used in integral geometry and related fields, and their numerical inversion is needed in several applications. To derive fast regularization schemes, the method of the approximate inverse is utilized. We introduce a new family of mollifiers and calculate the corresponding reconstruction kernels analytically for dimension d D 3 and even dimensions d 4. Numerical results for the three-dimensional case are presented showing that the new class of mollifiers clearly improves the quality of the reconstruction in comparison to the Gaussian mollifier. Moreover, the regularization theory for the method is extended to a framework for arbitrary dimension d 3 (the special case d D 3 was already considered in [21]).