Three-dimensional multiscale discrete Radon and John transforms

TL;DR

This paper introduces two efficient algorithms for 3D discrete Radon and John transforms that operate in real-time without interpolation, using integer arithmetic and linearithmic complexity, suitable for applications requiring fast 3D data analysis.

Contribution

The paper presents novel multiscale algorithms for 3D discrete Radon and John transforms that are computationally efficient and exact for discrete data, outperforming Fourier-based methods.

Findings

Algorithms operate in real-time with integer arithmetic.

Transformations have linearithmic computational complexity.

Exact inversion algorithms are available for discrete inputs.

Abstract

Two algorithms are introduced for the computation of discrete integral transforms with a multiscale approach operating in discrete three-dimensional (3D) volumes while considering its real-time implementation. The first algorithm, referred to as 3D discrete Radon transform (DRT) of planes, will compute the summation set of values lying in discrete planes in a cube that imitates, in discrete data, the integrals on two-dimensional planes in a 3D volume similar to the continuous Radon transform. The normals of these planes, equispaced in ascents, cover a quadrilateralized hemisphere and comprise 12 dodecants. The second proposed algorithm, referred to as the 3D discrete John transform (DJT) of lines, will sum elements lying on discrete 3D lines while imitating the behavior of the John or X-ray continuous transform on 3D volumes. These discrete integral transforms do not perform interpolation on input or intermediate data, and they can be computed using only integer arithmetics with linearithmic complexity; thus, outperforming the methods based on the Fourier slice-projection theorem for real-time applications. We briefly prove that these transforms have fast inversion algorithms that are exact for discrete inputs.