Revisiting the Iterative Ant-tree for color quantization algorithm
[EN] The Iterative Ant-tree for color quantization algorithm has recently been proposed to reduce the colors of an image at a low computational cost. It is a clustering-based method that generates good images compared to several well-known color quantization methods. This article proposes the modifi...
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | España |
| Recursos: | Universidad de Salamanca (USAL) |
| Repositorio: | GREDOS. Repositorio Institucional de la Universidad de Salamanca |
| OAI Identifier: | oai:gredos.usal.es:10366/159366 |
| Acesso em linha: | http://hdl.handle.net/10366/159366 |
| Access Level: | acceso abierto |
| Palavra-chave: | Color quantization Clustering Artificial ants 1203 Ciencia de los ordenadores |
| Resumo: | [EN] The Iterative Ant-tree for color quantization algorithm has recently been proposed to reduce the colors of an image at a low computational cost. It is a clustering-based method that generates good images compared to several well-known color quantization methods. This article proposes the modification of two features of the original algorithm: the value assigned to the parameter associated with the algorithm and the order in which the pixels of the image are processed. As a result, the new variant of the algorithm generates better images than the original and the results are less sensitive to the value selected for the parameter. |
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