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Quantum Image Processing Algorithm Using Line Detection Mask Based on NEQR

Line detection is a fundamental technique in image processing. It can extract the required information, while the information that does not need attention can be ignored, thus reducing the amount of data. At the same time, line detection is also the basis of image segmentation and plays an important...

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Detalles Bibliográficos
Autores principales: Li, Tao, Zhao, Pengpeng, Zhou, Yadong, Zhang, Yidai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217526/
https://www.ncbi.nlm.nih.gov/pubmed/37238493
http://dx.doi.org/10.3390/e25050738
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author Li, Tao
Zhao, Pengpeng
Zhou, Yadong
Zhang, Yidai
author_facet Li, Tao
Zhao, Pengpeng
Zhou, Yadong
Zhang, Yidai
author_sort Li, Tao
collection PubMed
description Line detection is a fundamental technique in image processing. It can extract the required information, while the information that does not need attention can be ignored, thus reducing the amount of data. At the same time, line detection is also the basis of image segmentation and plays an important role in this process. In this paper, we implement a quantum algorithm based on a line detection mask for novel enhanced quantum representation (NEQR). We build a quantum algorithm for line detection in different directions and design a quantum circuit for line detection. The detailed module designed is also provided. On a classical computer, we simulate the quantum method, and the simulation results prove the feasibility of the quantum method. By analyzing the complexity of quantum line detection, we find that the computation complexity of the proposed method is improved compared to some similar edge detection algorithms.
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spelling pubmed-102175262023-05-27 Quantum Image Processing Algorithm Using Line Detection Mask Based on NEQR Li, Tao Zhao, Pengpeng Zhou, Yadong Zhang, Yidai Entropy (Basel) Article Line detection is a fundamental technique in image processing. It can extract the required information, while the information that does not need attention can be ignored, thus reducing the amount of data. At the same time, line detection is also the basis of image segmentation and plays an important role in this process. In this paper, we implement a quantum algorithm based on a line detection mask for novel enhanced quantum representation (NEQR). We build a quantum algorithm for line detection in different directions and design a quantum circuit for line detection. The detailed module designed is also provided. On a classical computer, we simulate the quantum method, and the simulation results prove the feasibility of the quantum method. By analyzing the complexity of quantum line detection, we find that the computation complexity of the proposed method is improved compared to some similar edge detection algorithms. MDPI 2023-04-29 /pmc/articles/PMC10217526/ /pubmed/37238493 http://dx.doi.org/10.3390/e25050738 Text en © 2023 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
Li, Tao
Zhao, Pengpeng
Zhou, Yadong
Zhang, Yidai
Quantum Image Processing Algorithm Using Line Detection Mask Based on NEQR
title Quantum Image Processing Algorithm Using Line Detection Mask Based on NEQR
title_full Quantum Image Processing Algorithm Using Line Detection Mask Based on NEQR
title_fullStr Quantum Image Processing Algorithm Using Line Detection Mask Based on NEQR
title_full_unstemmed Quantum Image Processing Algorithm Using Line Detection Mask Based on NEQR
title_short Quantum Image Processing Algorithm Using Line Detection Mask Based on NEQR
title_sort quantum image processing algorithm using line detection mask based on neqr
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217526/
https://www.ncbi.nlm.nih.gov/pubmed/37238493
http://dx.doi.org/10.3390/e25050738
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