A comparison of computations for spatial frequency filtering

Three computational algorithms for performing spatial frequency filtering are compared and tradeoffs developed. Although each method is defined by a convolution relation, the convolution computations are different. Equal filter point-spread functions are assumed to effect the comparison. If the filter point-spread function is nonzero only over a small area, then the computation tradeoff is simply the well-known comparison between direct convolution and the fast Fourier trsnsform (FFT). If the filter point-spread function is nonzero over a large area, then a recursive filter is competitive with the FFT. Core memory requirements for this case are smallest with the recursive filter. Experimental examples are given to illustrate the subjective evaluation problem.