1. A method of designing filters for filtering digitized images comprising the steps of: using a processor to provide a digitized training image f(x) comprising a plurality of intensities corresponding to a domain of points on a n-dimensional grid; constructing a set of difference-of-Gaussian (DoG) filters {hi (x)} whose frequency responses partition a frequency space u; forming a linear combination of said DoG filters h(x)=Σci hi(x) to form a trial filter, said trial filter being associated with a set of linear combination coefficients {ci} that weight the contribution of each DoG filter to the trial filter; convolving said trial filter with said training image to obtain a trial image ft (x); and summing a square difference |fi (x)−fi (x)| 2 of said trial image and a target image fi (x) wherein if said sum is a minimum, outputting said trial filter as a final filter; and if said sum is not a minimum, forming a new linear combination of said DoG filters, and repeating the steps of convolving said trial filter with said training image, and summing a square difference of said trial image and said training image.