1. A method carried out in an electronic data processor, comprising: using an irregular filter tap to produce a prediction of a target image, wherein the irregular filter tap is generated from an irregular pattern of motion vectors and area of influence cells; performing least squared training on the prediction of the target image to produce a set of least squared filter coefficients; generating a classification map by selecting, for each area of influence cell, the filter with smallest prediction error for that area of influence cell; using the classification map to re-train the least squared filter coefficients; and using the re-trained filter coefficients to enhance the prediction of the target image.