The Modulo Radon Transform and its Inversion
File(s)
Accepted version
Author(s)
Bhandari, Ayush
Beckmann, Matthias
Krahmer, Felix
Type
Conference Paper
Abstract
In this paper, we introduce the Modulo Radon Transform (MRT) which is complemented by an inversion algorithm. The MRT generalizes the conventional Radon Transform and is obtained via computing modulo of the line integral of a two-dimensional function at a given angle. Since the modulo operation has an aliasing effect on the range of a function, the recorded MRT sinograms are always bounded, thus avoiding information loss arising from saturation or clipping effects. This paves a new pathway for imaging applications such as high dynamic range tomography, a topic that is in its early stages of development. By capitalizing on the recent results on Unlimited Sensing architecture, we prove that the Modulo Radon Transform can be inverted when the resultant (discrete/continuous) measurements map to a band-limited function. Thus, the MRT leads to new possibilities for both conceptualization of inversion algorithms as well as development of new hardware, for instance, for single-shot high dynamic range tomography.
Date Issued
2020-12-18
Date Acceptance
2020-12-01
Citation
2020 28th European Signal Processing Conference (EUSIPCO), 2020, pp.770-774
ISSN
2076-1465
Publisher
IEEE
Start Page
770
End Page
774
Journal / Book Title
2020 28th European Signal Processing Conference (EUSIPCO)
Copyright Statement
Copyright © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Identifier
https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000632622300155&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
Source
28th European Signal Processing Conference (EUSIPCO)
Subjects
Acoustics
Computational imaging
Computer Science
Computer Science, Software Engineering
computer tomography
Engineering
Engineering, Electrical & Electronic
filtered back projection
Imaging Science & Photographic Technology
modulo
sampling and Radon transform
Science & Technology
Technology
Publication Status
Published
Start Date
2021-01-18
Finish Date
2021-01-22
Coverage Spatial
Online