Thanks. It was unexpected to me as well. The original "magic" kernel was really along the lines of interpolation (particularly by large factors — there were all sorts of algorithms out there, e.g. repeatedly upsizing by small factors, to avoid aliasing ands pixelation artifacts) and wasn't seeking to approximate the properties of the sinc function / rectangular low-pass filter at all. Only after really understanding in practical terms (i.e. on millions of test images) the blurring nature of the continuum generalization of that kernel did I apply sharpening, and that's when it starts to resemble the Lanczos approximations. It's really the properties around harmonics of the sampling frequency that make the big difference — and that's where the high-order zeros come into play, that the Lanczos approximations don't possess.