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Learning to Sense for Coded Diffraction Imaging
In this paper, we present a framework to learn illumination patterns to improve the quality of signal recovery for coded diffraction imaging. We use an alternating minimization-based phase retrieval method with a fixed number of iterations as the iterative method. We represent the iterative phase re...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9788068/ https://www.ncbi.nlm.nih.gov/pubmed/36560332 http://dx.doi.org/10.3390/s22249964 |
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author | Hyder, Rakib Cai, Zikui Asif, M. Salman |
author_facet | Hyder, Rakib Cai, Zikui Asif, M. Salman |
author_sort | Hyder, Rakib |
collection | PubMed |
description | In this paper, we present a framework to learn illumination patterns to improve the quality of signal recovery for coded diffraction imaging. We use an alternating minimization-based phase retrieval method with a fixed number of iterations as the iterative method. We represent the iterative phase retrieval method as an unrolled network with a fixed number of layers where each layer of the network corresponds to a single step of iteration, and we minimize the recovery error by optimizing over the illumination patterns. Since the number of iterations/layers is fixed, the recovery has a fixed computational cost. Extensive experimental results on a variety of datasets demonstrate that our proposed method significantly improves the quality of image reconstruction at a fixed computational cost with illumination patterns learned only using a small number of training images. |
format | Online Article Text |
id | pubmed-9788068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97880682022-12-24 Learning to Sense for Coded Diffraction Imaging Hyder, Rakib Cai, Zikui Asif, M. Salman Sensors (Basel) Article In this paper, we present a framework to learn illumination patterns to improve the quality of signal recovery for coded diffraction imaging. We use an alternating minimization-based phase retrieval method with a fixed number of iterations as the iterative method. We represent the iterative phase retrieval method as an unrolled network with a fixed number of layers where each layer of the network corresponds to a single step of iteration, and we minimize the recovery error by optimizing over the illumination patterns. Since the number of iterations/layers is fixed, the recovery has a fixed computational cost. Extensive experimental results on a variety of datasets demonstrate that our proposed method significantly improves the quality of image reconstruction at a fixed computational cost with illumination patterns learned only using a small number of training images. MDPI 2022-12-17 /pmc/articles/PMC9788068/ /pubmed/36560332 http://dx.doi.org/10.3390/s22249964 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hyder, Rakib Cai, Zikui Asif, M. Salman Learning to Sense for Coded Diffraction Imaging |
title | Learning to Sense for Coded Diffraction Imaging |
title_full | Learning to Sense for Coded Diffraction Imaging |
title_fullStr | Learning to Sense for Coded Diffraction Imaging |
title_full_unstemmed | Learning to Sense for Coded Diffraction Imaging |
title_short | Learning to Sense for Coded Diffraction Imaging |
title_sort | learning to sense for coded diffraction imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9788068/ https://www.ncbi.nlm.nih.gov/pubmed/36560332 http://dx.doi.org/10.3390/s22249964 |
work_keys_str_mv | AT hyderrakib learningtosenseforcodeddiffractionimaging AT caizikui learningtosenseforcodeddiffractionimaging AT asifmsalman learningtosenseforcodeddiffractionimaging |