Artificial color uses the projection of the spectrum into two or more broad, overlapping spectral bands to discriminate, pixel by pixel, among user-defined classes of objects. As initially practiced, it used a sequence of hyperspherical regions of the decision space to define class membership. Of course, a hypersphere is just a degenerate hyperellipsoid; thus, exploring the effect of loosening that degeneracy seemed appropriate. Initially, we use two-foci hyperellipsoids with a hyperellipsoidal distance metric to classify pixels with dramatic improvement in performance. We explore the work even further by allowing many foci and noting the effects of increased complexity of the decision surfaces. In the example case, three foci gave superior performance to one or two foci, but four added little improvement.