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The morphing of geographical features by Fourier transformation

This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a...

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Detalles Bibliográficos
Autores principales: Li, Jingzhong, Liu, Pengcheng, Yu, Wenhao, Cheng, Xiaoqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774720/
https://www.ncbi.nlm.nih.gov/pubmed/29351344
http://dx.doi.org/10.1371/journal.pone.0191136
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author Li, Jingzhong
Liu, Pengcheng
Yu, Wenhao
Cheng, Xiaoqiang
author_facet Li, Jingzhong
Liu, Pengcheng
Yu, Wenhao
Cheng, Xiaoqiang
author_sort Li, Jingzhong
collection PubMed
description This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features’ continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable.
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spelling pubmed-57747202018-01-26 The morphing of geographical features by Fourier transformation Li, Jingzhong Liu, Pengcheng Yu, Wenhao Cheng, Xiaoqiang PLoS One Research Article This paper presents a morphing model of vector geographical data based on Fourier transformation. This model involves three main steps. They are conversion from vector data to Fourier series, generation of intermediate function by combination of the two Fourier series concerning a large scale and a small scale, and reverse conversion from combination function to vector data. By mirror processing, the model can also be used for morphing of linear features. Experimental results show that this method is sensitive to scale variations and it can be used for vector map features’ continuous scale transformation. The efficiency of this model is linearly related to the point number of shape boundary and the interceptive value n of Fourier expansion. The effect of morphing by Fourier transformation is plausible and the efficiency of the algorithm is acceptable. Public Library of Science 2018-01-19 /pmc/articles/PMC5774720/ /pubmed/29351344 http://dx.doi.org/10.1371/journal.pone.0191136 Text en © 2018 Li et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Li, Jingzhong
Liu, Pengcheng
Yu, Wenhao
Cheng, Xiaoqiang
The morphing of geographical features by Fourier transformation
title The morphing of geographical features by Fourier transformation
title_full The morphing of geographical features by Fourier transformation
title_fullStr The morphing of geographical features by Fourier transformation
title_full_unstemmed The morphing of geographical features by Fourier transformation
title_short The morphing of geographical features by Fourier transformation
title_sort morphing of geographical features by fourier transformation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5774720/
https://www.ncbi.nlm.nih.gov/pubmed/29351344
http://dx.doi.org/10.1371/journal.pone.0191136
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