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Spline-Based Dense Medial Descriptors for Lossy Image Compression

Medial descriptors are of significant interest for image simplification, representation, manipulation, and compression. On the other hand, B-splines are well-known tools for specifying smooth curves in computer graphics and geometric design. In this paper, we integrate the two by modeling medial des...

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Detalles Bibliográficos
Autores principales: Wang, Jieying, Kosinka, Jiří, Telea, Alexandru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404928/
https://www.ncbi.nlm.nih.gov/pubmed/34460789
http://dx.doi.org/10.3390/jimaging7080153
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author Wang, Jieying
Kosinka, Jiří
Telea, Alexandru
author_facet Wang, Jieying
Kosinka, Jiří
Telea, Alexandru
author_sort Wang, Jieying
collection PubMed
description Medial descriptors are of significant interest for image simplification, representation, manipulation, and compression. On the other hand, B-splines are well-known tools for specifying smooth curves in computer graphics and geometric design. In this paper, we integrate the two by modeling medial descriptors with stable and accurate B-splines for image compression. Representing medial descriptors with B-splines can not only greatly improve compression but is also an effective vector representation of raster images. A comprehensive evaluation shows that our Spline-based Dense Medial Descriptors (SDMD) method achieves much higher compression ratios at similar or even better quality to the well-known JPEG technique. We illustrate our approach with applications in generating super-resolution images and salient feature preserving image compression.
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spelling pubmed-84049282021-10-28 Spline-Based Dense Medial Descriptors for Lossy Image Compression Wang, Jieying Kosinka, Jiří Telea, Alexandru J Imaging Article Medial descriptors are of significant interest for image simplification, representation, manipulation, and compression. On the other hand, B-splines are well-known tools for specifying smooth curves in computer graphics and geometric design. In this paper, we integrate the two by modeling medial descriptors with stable and accurate B-splines for image compression. Representing medial descriptors with B-splines can not only greatly improve compression but is also an effective vector representation of raster images. A comprehensive evaluation shows that our Spline-based Dense Medial Descriptors (SDMD) method achieves much higher compression ratios at similar or even better quality to the well-known JPEG technique. We illustrate our approach with applications in generating super-resolution images and salient feature preserving image compression. MDPI 2021-08-19 /pmc/articles/PMC8404928/ /pubmed/34460789 http://dx.doi.org/10.3390/jimaging7080153 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
Wang, Jieying
Kosinka, Jiří
Telea, Alexandru
Spline-Based Dense Medial Descriptors for Lossy Image Compression
title Spline-Based Dense Medial Descriptors for Lossy Image Compression
title_full Spline-Based Dense Medial Descriptors for Lossy Image Compression
title_fullStr Spline-Based Dense Medial Descriptors for Lossy Image Compression
title_full_unstemmed Spline-Based Dense Medial Descriptors for Lossy Image Compression
title_short Spline-Based Dense Medial Descriptors for Lossy Image Compression
title_sort spline-based dense medial descriptors for lossy image compression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404928/
https://www.ncbi.nlm.nih.gov/pubmed/34460789
http://dx.doi.org/10.3390/jimaging7080153
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