An iterative method to improve the results of ant-tree algorithm applied to colour quantisation
by María-Luisa Pérez-Delgado
International Journal of Bio-Inspired Computation (IJBIC), Vol. 12, No. 2, 2018

Abstract: Colour quantisation methods attempt to represent a colour image by a palette with fewer colours than the original one. This paper presents a method of this type, based on a previous algorithm called ant-tree for colour quantisation (ATCQ), which applies artificial ants for colour reduction. An important advantage of the new algorithm is that it does not require sorting the input data. Moreover, it applies an iterative process to increase the quality of the quantised image as iterations proceed. The proposed algorithm gives better results than the original one, and it is competitive with other well-known colour quantisation methods, such as Median-cut, Octree, Neuquant, variance-based, binary splitting or Wu's methods.

Online publication date: Wed, 22-Aug-2018

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