1. An automated, computerized method for processing an image, comprising the steps of: providing an image file depicting an image, in a computer memory; assembling a feature vector for the image file, the feature vector containing information regarding a likelihood that a selected pair of regions of the image file are of a same intrinsic characteristic; providing a classifier derived from a computer learning technique; computing a classification score for the selected pair of regions of the image file, as a function of the feature vector and the classifier; classifying the regions as being of the same intrinsic characteristic, as a function of the classification score; when a classification score indicates regions as being of the same intrinsic characteristic, defining a constraint between the regions based upon a spatio-spectral relationship defined by the same intrinsic characteristic; and performing an optimization operation as a function of the constraint to utilize the spatio-spectral relationship defined by the same intrinsic characteristic to generate an intrinsic image corresponding to the image, the intrinsic image comprising a representation of one of material or illumination, expressed as a separate, multi-band representation for the one of material or illumination, independent of the other of the material or illumination, wherein each band corresponds to a segment of the electro-magnetic spectrum, such that when the intrinsic image comprises an illumination image, the illumination image captures the intensity and color of light incident upon each point on the surfaces depicted in the image, and when the intrinsic image comprises a material image, the material image captures reflectance properties of surfaces depicted in the image, including the percentage of each wavelength of light a surface reflects, to segregate the image into an intrinsic component.