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A Common Assessment Space for Different Sensor Structures

The study of the evolution process of our visual system indicates the existence of variational spatial arrangement; from densely hexagonal in the fovea to a sparse circular structure in the peripheral retina. Today’s sensor spatial arrangement is inspired by our visual system. However, we have not c...

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Autores principales: Wen, Wei, Kajínek, Ondřej, Khatibi, Siamak, Chadzitaskos, Goce
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387182/
https://www.ncbi.nlm.nih.gov/pubmed/30700053
http://dx.doi.org/10.3390/s19030568
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author Wen, Wei
Kajínek, Ondřej
Khatibi, Siamak
Chadzitaskos, Goce
author_facet Wen, Wei
Kajínek, Ondřej
Khatibi, Siamak
Chadzitaskos, Goce
author_sort Wen, Wei
collection PubMed
description The study of the evolution process of our visual system indicates the existence of variational spatial arrangement; from densely hexagonal in the fovea to a sparse circular structure in the peripheral retina. Today’s sensor spatial arrangement is inspired by our visual system. However, we have not come further than rigid rectangular and, on a minor scale, hexagonal sensor arrangements. Even in this situation, there is a need for directly assessing differences between the rectangular and hexagonal sensor arrangements, i.e., without the conversion of one arrangement to another. In this paper, we propose a method to create a common space for addressing any spatial arrangements and assessing the differences among them, e.g., between the rectangular and hexagonal. Such a space is created by implementing a continuous extension of discrete Weyl Group orbit function transform which extends a discrete arrangement to a continuous one. The implementation of the space is demonstrated by comparing two types of generated hexagonal images from each rectangular image with two different methods of the half-pixel shifting method and virtual hexagonal method. In the experiment, a group of ten texture images were generated with variational curviness content using ten different Perlin noise patterns, adding to an initial 2D Gaussian distribution pattern image. Then, the common space was obtained from each of the discrete images to assess the differences between the original rectangular image and its corresponding hexagonal image. The results show that the space facilitates a usage friendly tool to address an arrangement and assess the changes between different spatial arrangements by which, in the experiment, the hexagonal images show richer intensity variation, nonlinear behavior, and larger dynamic range in comparison to the rectangular images.
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spelling pubmed-63871822019-02-26 A Common Assessment Space for Different Sensor Structures Wen, Wei Kajínek, Ondřej Khatibi, Siamak Chadzitaskos, Goce Sensors (Basel) Article The study of the evolution process of our visual system indicates the existence of variational spatial arrangement; from densely hexagonal in the fovea to a sparse circular structure in the peripheral retina. Today’s sensor spatial arrangement is inspired by our visual system. However, we have not come further than rigid rectangular and, on a minor scale, hexagonal sensor arrangements. Even in this situation, there is a need for directly assessing differences between the rectangular and hexagonal sensor arrangements, i.e., without the conversion of one arrangement to another. In this paper, we propose a method to create a common space for addressing any spatial arrangements and assessing the differences among them, e.g., between the rectangular and hexagonal. Such a space is created by implementing a continuous extension of discrete Weyl Group orbit function transform which extends a discrete arrangement to a continuous one. The implementation of the space is demonstrated by comparing two types of generated hexagonal images from each rectangular image with two different methods of the half-pixel shifting method and virtual hexagonal method. In the experiment, a group of ten texture images were generated with variational curviness content using ten different Perlin noise patterns, adding to an initial 2D Gaussian distribution pattern image. Then, the common space was obtained from each of the discrete images to assess the differences between the original rectangular image and its corresponding hexagonal image. The results show that the space facilitates a usage friendly tool to address an arrangement and assess the changes between different spatial arrangements by which, in the experiment, the hexagonal images show richer intensity variation, nonlinear behavior, and larger dynamic range in comparison to the rectangular images. MDPI 2019-01-29 /pmc/articles/PMC6387182/ /pubmed/30700053 http://dx.doi.org/10.3390/s19030568 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wen, Wei
Kajínek, Ondřej
Khatibi, Siamak
Chadzitaskos, Goce
A Common Assessment Space for Different Sensor Structures
title A Common Assessment Space for Different Sensor Structures
title_full A Common Assessment Space for Different Sensor Structures
title_fullStr A Common Assessment Space for Different Sensor Structures
title_full_unstemmed A Common Assessment Space for Different Sensor Structures
title_short A Common Assessment Space for Different Sensor Structures
title_sort common assessment space for different sensor structures
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6387182/
https://www.ncbi.nlm.nih.gov/pubmed/30700053
http://dx.doi.org/10.3390/s19030568
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