Efficient Gaussian filtering using Cascaded Prefix Sums

This paper introduces a method for multidimensional Gaussian filtering using an efficient one-pass cascade of overlapping local-average windows driven by prefix sums. Each local-average filter is implemented in n dimensions, with non-integer lengths, allowing accurate approximation of Gaussians of any variance. In axis-oriented form the method has a scan-rate hardware realization and fast software implementation using minimal extra memory. In this latter case the new method consistently outperforms the fastest alternative Gaussian filtering method both in accuracy and speed.