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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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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. |
format | Online Article Text |
id | pubmed-3727189 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT suqinghua colorimagequantizationalgorithmbasedonselfadaptivedifferentialevolution AT huzhongbo colorimagequantizationalgorithmbasedonselfadaptivedifferentialevolution |