1. A method, comprising: chromatic classifying pixels of a digital image by, transforming a chromatic domain of definition of pixels from a three-dimensional space into a respective two-dimensional normalized space; defining a reference model of classification by analyzing a plurality of images of distinct types of subjects, generating distinct collections of samples with respective coordinates in the normalized two-dimensional space for each of a number of chromatic classes corresponding to real subjects; evaluating, based on the reference model and for each image pixel to be classified: a membership level within each chromatic class of the number of chromatic classes; and a membership class based on the membership levels of the pixel within each chromatic class; classifying pixels based on the evaluation of the membership class and the evaluation of the membership level within each chromatic class; and selectively shifting a color of the pixel while maintaining an intensity of the pixel, wherein said reference model is defined by a parametric membership function continuous on said normalized two-dimensional space for each of said chromatic classes, parameters of which are determined by processing the collection of two-dimensional samples of each of said chromatic classes, said chromatic classifying, transforming, defining and evaluating being performed by one or more configured processing devices, wherein said three-dimensional space is an RGB space and the respective normalized two-dimensional space is an rg space and the selective shifting is according to: 
 R′= 3 I ( r+Δr c ) 
 G′= 3 I ( g+Δg c ) 
 B′= 3 I[ 1−( r+Δr c )−( g+Δg c )] where Δr c and Δg c represent a distance of a chromatic cluster from chromatic targets of the chromatic class, I is a mean intensity of the pixel, and r and g are chromacity components of the pixel.