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A true colour digital image requires 24 bits to specify thecolour of each pixel on the screen. It is expensive tohave a high-speed memory to support such a full-colourdisplay on a high resolution display. An alternativesolution is to provide a limited number of bits forspecifying the colour of each pixel. Each of these valuesis then used as an index into a user-defined colour palettetable. The process of carrying out a colour palette tableselection is known as the colour quantization process.The colour quantization is one of the most useful lossycompression methods [1, 2] with the benefit of easyimplementation on the image receiver site. Typically, thecolour quantization attempts to find an acceptable set ofpalette colours that can be used to represent the originalcolours of a digital image [1]. There are two points thatmake this lossy image compression successful. First ofall, it exploits the limited ability of human perceptionwhich is capable of distinguishing less than a thousandcolours. In addition, it exploits the limited capability ofmany display devices to display true colours on manydisplay devices like a billboard [3] or a low quality LCD(Liquid Crystal Display) which have constantly beenused as replacements for text centric display media.Applying the colour quantization to an RGB colourimage frame of size 640 9 480 pixels, the resultingimage with a colour palette size of 256 will have only(640 9 480) ? (256 9 3) = 307,968 bytes which isabout one-third of the original image size. This makesthe colour quantization process widely utilized in many applications especially in computer graphics and imageprocessing.
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