Affiliations: [a] Department of Computer Science, Loughborough University, Loughborough, UK | [b] Institute of Electronics, Communications and Information Technology, Queen's University Belfast, Belfast, UK | [c] Department of Computer Science, Louisiana State University in Shreveport, Shreveport, USA | [d] Information Technology Department, Cairo University, Giza, Egypt | [v] Cairo University, Egypt | [w] Kyushu Institute of Technology, Japan | [x] University of Warsaw & Infobright Inc., Poland | [y] University of Calcutta, India | [z] UESTC, Chengdu, China
Abstract: Colour quantisation algorithms are essential for displaying true colour images using a limited palette of distinct colours. The choice of a good colour palette is crucial as it directly determines the quality of the resulting image. Colour quantisation can also be seen as a clustering problem where the task is to identify those clusters that best represent the colours in an image. In this paper, we use a rough c-means clustering algorithm for colour quantisation of images. Experimental results on a standard set of images show that this rough colour quantisation approach performs significantly better than other, purpose built colour reduction algorithms.
