Abstract
Many multi-dimensional signal processing problems require the computation of signal gradients or directional derivatives. Traditional derivative estimates based on adjacent or central differences are often inappropriate for multi-dimensional problems. As replacements for these traditional operators, the author designs a set of matched pairs of derivative filters and lowpass prefilters. The author demonstrates the superiority of these filters over simple difference operators.

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