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Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution

Differential evolution algorithm (DE) is one of the novel stochastic optimization methods. It has a better performance in the problem of the color image quantization, but it is difficult to set the parameters of DE for users. This paper proposes a color image quantization algorithm based on self-ada...

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Detalles Bibliográficos
Autores principales: Su, Qinghua, Hu, Zhongbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3727189/
https://www.ncbi.nlm.nih.gov/pubmed/23956737
http://dx.doi.org/10.1155/2013/231916
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author Su, Qinghua
Hu, Zhongbo
author_facet Su, Qinghua
Hu, Zhongbo
author_sort Su, Qinghua
collection PubMed
description Differential evolution algorithm (DE) is one of the novel stochastic optimization methods. It has a better performance in the problem of the color image quantization, but it is difficult to set the parameters of DE for users. This paper proposes a color image quantization algorithm based on self-adaptive DE. In the proposed algorithm, a self-adaptive mechanic is used to automatically adjust the parameters of DE during the evolution, and a mixed mechanic of DE and K-means is applied to strengthen the local search. The numerical experimental results, on a set of commonly used test images, show that the proposed algorithm is a practicable quantization method and is more competitive than K-means and particle swarm algorithm (PSO) for the color image quantization.
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spelling pubmed-37271892013-08-16 Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution Su, Qinghua Hu, Zhongbo Comput Intell Neurosci Research Article Differential evolution algorithm (DE) is one of the novel stochastic optimization methods. It has a better performance in the problem of the color image quantization, but it is difficult to set the parameters of DE for users. This paper proposes a color image quantization algorithm based on self-adaptive DE. In the proposed algorithm, a self-adaptive mechanic is used to automatically adjust the parameters of DE during the evolution, and a mixed mechanic of DE and K-means is applied to strengthen the local search. The numerical experimental results, on a set of commonly used test images, show that the proposed algorithm is a practicable quantization method and is more competitive than K-means and particle swarm algorithm (PSO) for the color image quantization. Hindawi Publishing Corporation 2013 2013-07-15 /pmc/articles/PMC3727189/ /pubmed/23956737 http://dx.doi.org/10.1155/2013/231916 Text en Copyright © 2013 Q. Su and Z. Hu. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Su, Qinghua
Hu, Zhongbo
Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution
title Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution
title_full Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution
title_fullStr Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution
title_full_unstemmed Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution
title_short Color Image Quantization Algorithm Based on Self-Adaptive Differential Evolution
title_sort color image quantization algorithm based on self-adaptive differential evolution
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3727189/
https://www.ncbi.nlm.nih.gov/pubmed/23956737
http://dx.doi.org/10.1155/2013/231916
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