Abstract: A method of estimating the chromaticity of illumination of a colored image consisting of a plurality of color-encoded pixels. The image colors are first mapped into an intensity-independent chromaticity space which is then divided into a plurality of separate regions. For each region, a first binary value is assigned to the region if the region contains no chromaticity value; or, a second binary value is assigned to the region if it does contain a chromaticity value. The assigned values are then applied as inputs to a pre-trained neural network having two output ports and at least one intermediate layer containing a plurality rality of ports connectible between selected input ports and the output ports. The chromaticity space values which characterize the input image's chromaticity of illumination are then derived at the output ports. The network is pretrained trained by initially connecting an arbitrary number of the intermediate layer ports to selected input layer ports.