Sparse signal recovery from modulo observations

Abstract We consider the problem of reconstructing a signal from under-determined modulo observations (or measurements). This observation model is inspired by a relatively new imaging mechanism called modulo imaging, which can be used to extend the dynamic range of imaging systems; variations of thi...

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Main Authors: Viraj Shah, Chinmay Hegde
Format: Article
Language:English
Published: SpringerOpen 2021-04-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:https://doi.org/10.1186/s13634-021-00722-w
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spelling doaj-29694b86e254449296850ad0a951d2642021-04-11T11:22:17ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61802021-04-012021111710.1186/s13634-021-00722-wSparse signal recovery from modulo observationsViraj Shah0Chinmay Hegde1ECE Department, University of Illinois Urbana-ChampaignTandon School of Engineering, New York UniversityAbstract We consider the problem of reconstructing a signal from under-determined modulo observations (or measurements). This observation model is inspired by a relatively new imaging mechanism called modulo imaging, which can be used to extend the dynamic range of imaging systems; variations of this model have also been studied under the category of phase unwrapping. Signal reconstruction in the under-determined regime with modulo observations is a challenging ill-posed problem, and existing reconstruction methods cannot be used directly. In this paper, we propose a novel approach to solving the signal recovery problem under sparsity constraints for the special case to modulo folding limited to two periods. We show that given a sufficient number of measurements, our algorithm perfectly recovers the underlying signal. We also provide experiments validating our approach on toy signal and image data and demonstrate its promising performance.https://doi.org/10.1186/s13634-021-00722-wSparse recoveryHigh dynamic range imagingModulo sensing
collection DOAJ
language English
format Article
sources DOAJ
author Viraj Shah
Chinmay Hegde
spellingShingle Viraj Shah
Chinmay Hegde
Sparse signal recovery from modulo observations
EURASIP Journal on Advances in Signal Processing
Sparse recovery
High dynamic range imaging
Modulo sensing
author_facet Viraj Shah
Chinmay Hegde
author_sort Viraj Shah
title Sparse signal recovery from modulo observations
title_short Sparse signal recovery from modulo observations
title_full Sparse signal recovery from modulo observations
title_fullStr Sparse signal recovery from modulo observations
title_full_unstemmed Sparse signal recovery from modulo observations
title_sort sparse signal recovery from modulo observations
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6180
publishDate 2021-04-01
description Abstract We consider the problem of reconstructing a signal from under-determined modulo observations (or measurements). This observation model is inspired by a relatively new imaging mechanism called modulo imaging, which can be used to extend the dynamic range of imaging systems; variations of this model have also been studied under the category of phase unwrapping. Signal reconstruction in the under-determined regime with modulo observations is a challenging ill-posed problem, and existing reconstruction methods cannot be used directly. In this paper, we propose a novel approach to solving the signal recovery problem under sparsity constraints for the special case to modulo folding limited to two periods. We show that given a sufficient number of measurements, our algorithm perfectly recovers the underlying signal. We also provide experiments validating our approach on toy signal and image data and demonstrate its promising performance.
topic Sparse recovery
High dynamic range imaging
Modulo sensing
url https://doi.org/10.1186/s13634-021-00722-w
work_keys_str_mv AT virajshah sparsesignalrecoveryfrommoduloobservations
AT chinmayhegde sparsesignalrecoveryfrommoduloobservations
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