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Título
A Hybrid Color Quantization Algorithm That Combines the Greedy Orthogonal Bi-Partitioning Method With Artificial Ants
Autor(es)
Palabras clave
Color image analysis
Quantization
Clustering algorithms
Artificial intelligence
Color quantization
Fecha de publicación
2019
Editor
IEEE
Citación
M. -L. Pérez-Delgado and J. Á. Román Gallego, "A Hybrid Color Quantization Algorithm That Combines the Greedy Orthogonal Bi-Partitioning Method With Artificial Ants," in IEEE Access, vol. 7, pp. 128714-128734, 2019, doi: 10.1109/ACCESS.2019.2937934
Resumen
[EN]A color quantization technique that combines the operations of two existing methods is proposed. The first method considered is the Greedy orthogonal bi-partitioning method. This is a very popular technique in the color quantization field that can obtain a solution quickly. The second method, called Ant-tree for color quantization, was recently proposed and can obtain better images than some other color quantization techniques. The solution described in this article combines both methods to obtain images with good quality at a low computational cost. The resulting images are always better than those generated by each method applied separately. In addition, the results also improve those obtained by other well-known color quantization methods, such as Octree, Median-cut, Neuquant, Binary splitting or Variance-based methods. The features of the proposed method make it suitable for real-time image processing applications, which are related to many practical problems in diverse disciplines, such as medicine and engineering.
URI
ISSN
2169-3536
DOI
10.1109/ACCESS.2019.2937934
Versión del editor
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- CIMET. Artículos [18]













