My previous post explained and provided a very simple method for extracting colours from a BitmapData image, by averaging the colours in specific areas. This can have several applications, for example it features in a large amount of prototypes for the update to my Motion Tracking engine. However, if you want to create an accurate and representative colour palette from an image it has several flaws, the most obvious being that by averaging colours, you are actually removing or diluting the striking but perhaps less frequent colours in the image – the very colours which often make an image’s colour palette so exiting!

So, if we’re to extract an exciting and more representative palette from an image, we need a more intelligent algorithm; one which takes into account what makes a colour palette interesting – the contrasts and juxtapositions of colours within the image. Read : BitmapData Colour Palette »

If you want a very simple way of extracting a colour palette from an image, one technique would be to average the colour values within specific areas. Averaging colour values is almost identical to averaging numbers, except with the added initial step of finding the red, green and blue components of the colour. To do this we can use bitwise operators, in this case bitwise shift, to perform fast operations on each bit inside the unsigned integer returned by getPixel or getPixel32. If you want to know more about bitwise operators, Moock has written a detailed and, as ever, very clear article on where, when and why to use bitewise operations. You can read it here.

So once you’re familiar with how to shift the bits of an integer, you can easily get the RGB values from a 24 bit hexadecimal by moving the bits to the right by a certain amount using the bitwise right shift operator (>>). Read : BitmapData Average Colours »