An evolving localised learning model for on-line image colour quantisation
Jeremiah D. Deng, Nikola Kirilov Kasabov · 2002
Although widely studied for many years, colour quantisation remains a practical problem in image processing. Unlike previous works where the image can only be quantised after the whole set of image data is acquired, we propose to use an evolving localised learning model for on-line colour quantisation. This approach is compared with some conventional algorithms.