Re-Ordering of Hadamard Matrix Using Fourier Transform and Gray-Level Co-Occurrence Matrix for Compressive Single-Pixel Imaging in Low Resolution Images

One of the most active research fields in single-pixel imaging is the influence of the sampling basis and its order in the quality of the reconstructed images. This paper presents two new orders, ascending scale (AS) and ascending inertia (AI), of the Hadamard basis and test their performance, using...

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Main Authors: Pedro G. Vaz, Andreia S. Gaudencio, L. F. Requicha Ferreira, Anne Humeau-Heurtier, Miguel Morgado, Joao Cardoso
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9765455/
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author Pedro G. Vaz
Andreia S. Gaudencio
L. F. Requicha Ferreira
Anne Humeau-Heurtier
Miguel Morgado
Joao Cardoso
author_facet Pedro G. Vaz
Andreia S. Gaudencio
L. F. Requicha Ferreira
Anne Humeau-Heurtier
Miguel Morgado
Joao Cardoso
author_sort Pedro G. Vaz
collection DOAJ
description One of the most active research fields in single-pixel imaging is the influence of the sampling basis and its order in the quality of the reconstructed images. This paper presents two new orders, ascending scale (AS) and ascending inertia (AI), of the Hadamard basis and test their performance, using simulation and experimental methods, for low sampling ratios (0.5 to 0.01) in low resolution images (up to <inline-formula> <tex-math notation="LaTeX">$128\,{\times }\,128$ </tex-math></inline-formula>). These orders were compared with two state-of-the-art orders, cake-cutting (CC) and total gradient (TG), using TVAL3 as the reconstruction algorithm and three noise levels. These newly proposed orders have better reconstructed image quality on the simulation data set (110 images) and achieved structure similarity index values higher than CC order. The experimental data set (2 images) showed that the AS and AI orders performed better with a sampling ratio of 0.5, while for lower sampling ratio the performance of AS, AI and CC was similar. The TG order performed worst in the majority of the cases. Finally, the simulation results present clear evidence that peak signal-to-noise ratio (PSNR) is not a reliable image quality assessment (IQA) metric to assess image reconstruction quality in the context of single pixel imaging.
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spelling doaj.art-14a4783f927b493a85d0c997022e97152022-12-22T00:38:48ZengIEEEIEEE Access2169-35362022-01-0110469754698510.1109/ACCESS.2022.31713349765455Re-Ordering of Hadamard Matrix Using Fourier Transform and Gray-Level Co-Occurrence Matrix for Compressive Single-Pixel Imaging in Low Resolution ImagesPedro G. Vaz0https://orcid.org/0000-0003-3490-7789Andreia S. Gaudencio1L. F. Requicha Ferreira2Anne Humeau-Heurtier3https://orcid.org/0000-0002-6289-0040Miguel Morgado4https://orcid.org/0000-0001-9455-1206Joao Cardoso5Department of Physics, Rua Larga, University of Coimbra, Coimbra, LIBPhys-UC, PortugalDepartment of Physics, Rua Larga, University of Coimbra, Coimbra, LIBPhys-UC, PortugalDepartment of Physics, Rua Larga, University of Coimbra, Coimbra, LIBPhys-UC, PortugalLARIS, SFR MATHSTIC, Universit&#x00E9; d&#x2019;Angers, Angers, FranceDepartment of Physics, Rua Larga, University of Coimbra, Coimbra, PortugalDepartment of Physics, Rua Larga, University of Coimbra, Coimbra, LIBPhys-UC, PortugalOne of the most active research fields in single-pixel imaging is the influence of the sampling basis and its order in the quality of the reconstructed images. This paper presents two new orders, ascending scale (AS) and ascending inertia (AI), of the Hadamard basis and test their performance, using simulation and experimental methods, for low sampling ratios (0.5 to 0.01) in low resolution images (up to <inline-formula> <tex-math notation="LaTeX">$128\,{\times }\,128$ </tex-math></inline-formula>). These orders were compared with two state-of-the-art orders, cake-cutting (CC) and total gradient (TG), using TVAL3 as the reconstruction algorithm and three noise levels. These newly proposed orders have better reconstructed image quality on the simulation data set (110 images) and achieved structure similarity index values higher than CC order. The experimental data set (2 images) showed that the AS and AI orders performed better with a sampling ratio of 0.5, while for lower sampling ratio the performance of AS, AI and CC was similar. The TG order performed worst in the majority of the cases. Finally, the simulation results present clear evidence that peak signal-to-noise ratio (PSNR) is not a reliable image quality assessment (IQA) metric to assess image reconstruction quality in the context of single pixel imaging.https://ieeexplore.ieee.org/document/9765455/Compressive sensingFourier transformHadamard orderingsingle pixel imaging
spellingShingle Pedro G. Vaz
Andreia S. Gaudencio
L. F. Requicha Ferreira
Anne Humeau-Heurtier
Miguel Morgado
Joao Cardoso
Re-Ordering of Hadamard Matrix Using Fourier Transform and Gray-Level Co-Occurrence Matrix for Compressive Single-Pixel Imaging in Low Resolution Images
IEEE Access
Compressive sensing
Fourier transform
Hadamard ordering
single pixel imaging
title Re-Ordering of Hadamard Matrix Using Fourier Transform and Gray-Level Co-Occurrence Matrix for Compressive Single-Pixel Imaging in Low Resolution Images
title_full Re-Ordering of Hadamard Matrix Using Fourier Transform and Gray-Level Co-Occurrence Matrix for Compressive Single-Pixel Imaging in Low Resolution Images
title_fullStr Re-Ordering of Hadamard Matrix Using Fourier Transform and Gray-Level Co-Occurrence Matrix for Compressive Single-Pixel Imaging in Low Resolution Images
title_full_unstemmed Re-Ordering of Hadamard Matrix Using Fourier Transform and Gray-Level Co-Occurrence Matrix for Compressive Single-Pixel Imaging in Low Resolution Images
title_short Re-Ordering of Hadamard Matrix Using Fourier Transform and Gray-Level Co-Occurrence Matrix for Compressive Single-Pixel Imaging in Low Resolution Images
title_sort re ordering of hadamard matrix using fourier transform and gray level co occurrence matrix for compressive single pixel imaging in low resolution images
topic Compressive sensing
Fourier transform
Hadamard ordering
single pixel imaging
url https://ieeexplore.ieee.org/document/9765455/
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