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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Online Access: | https://doi.org/10.1186/s13634-021-00722-w |
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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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