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Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints

Terahertz time domain spectroscopy imaging systems suffer from the problems of long image acquisition time and massive data processing. Reducing the sampling rate will lead to the degradation of the imaging reconstruction quality. To solve this issue, a novel terahertz imaging model, named the dual...

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Detalles Bibliográficos
Autores principales: Ren, Xiaozhen, Jiang, Yuying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232612/
https://www.ncbi.nlm.nih.gov/pubmed/34203842
http://dx.doi.org/10.3390/s21124116
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author Ren, Xiaozhen
Jiang, Yuying
author_facet Ren, Xiaozhen
Jiang, Yuying
author_sort Ren, Xiaozhen
collection PubMed
description Terahertz time domain spectroscopy imaging systems suffer from the problems of long image acquisition time and massive data processing. Reducing the sampling rate will lead to the degradation of the imaging reconstruction quality. To solve this issue, a novel terahertz imaging model, named the dual sparsity constraints terahertz image reconstruction model (DSC-THz), is proposed in this paper. DSC-THz fuses the sparsity constraints of the terahertz image in wavelet and gradient domains into the terahertz image reconstruction model. Differing from the conventional wavelet transform, we introduce a non-linear exponentiation transform into the shift invariant wavelet coefficients, which can amplify the significant coefficients and suppress the small ones. Simultaneously, the sparsity of the terahertz image in gradient domain is used to enhance the sparsity of the image, which has the advantage of edge preserving property. The split Bregman iteration scheme is utilized to tackle the optimization problem. By using the idea of separation of variables, the optimization problem is decomposed into subproblems to solve. Compared with the conventional single sparsity constraint terahertz image reconstruction model, the experiments verified that the proposed approach can achieve higher terahertz image reconstruction quality at low sampling rates.
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spelling pubmed-82326122021-06-26 Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints Ren, Xiaozhen Jiang, Yuying Sensors (Basel) Article Terahertz time domain spectroscopy imaging systems suffer from the problems of long image acquisition time and massive data processing. Reducing the sampling rate will lead to the degradation of the imaging reconstruction quality. To solve this issue, a novel terahertz imaging model, named the dual sparsity constraints terahertz image reconstruction model (DSC-THz), is proposed in this paper. DSC-THz fuses the sparsity constraints of the terahertz image in wavelet and gradient domains into the terahertz image reconstruction model. Differing from the conventional wavelet transform, we introduce a non-linear exponentiation transform into the shift invariant wavelet coefficients, which can amplify the significant coefficients and suppress the small ones. Simultaneously, the sparsity of the terahertz image in gradient domain is used to enhance the sparsity of the image, which has the advantage of edge preserving property. The split Bregman iteration scheme is utilized to tackle the optimization problem. By using the idea of separation of variables, the optimization problem is decomposed into subproblems to solve. Compared with the conventional single sparsity constraint terahertz image reconstruction model, the experiments verified that the proposed approach can achieve higher terahertz image reconstruction quality at low sampling rates. MDPI 2021-06-15 /pmc/articles/PMC8232612/ /pubmed/34203842 http://dx.doi.org/10.3390/s21124116 Text en © 2021 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
Ren, Xiaozhen
Jiang, Yuying
Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints
title Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints
title_full Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints
title_fullStr Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints
title_full_unstemmed Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints
title_short Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints
title_sort spatial domain terahertz image reconstruction based on dual sparsity constraints
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8232612/
https://www.ncbi.nlm.nih.gov/pubmed/34203842
http://dx.doi.org/10.3390/s21124116
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AT jiangyuying spatialdomainterahertzimagereconstructionbasedondualsparsityconstraints