1. A method for classifying an unknown test image by comparing the unknown test image to a dictionary of example images each of which is associated with an outcome class, comprising the steps of: receiving the unknown test image; projecting the unknown test image onto each one of the example images in the dictionary; identifying a scaling coefficient wherein the scaling coefficient is set to a maximum value produced by the projections of the unknown test image onto the dictionary of example images; generating a residue of the unknown test image based on a difference between the unknown test image and the example image producing the maximum value scaled by the scaling coefficient; refining a linear expansion of the unknown test image by adding the scaled example image to the linear expansion; iteratively using the residue as the unknown test image in projecting, identifying, generating and refining for a selected number of iterations; and classifying the unknown test image by selecting the outcome class within the linear expansion having the largest sum of scaling coefficients for the example images associated with the outcome class.