Fast Convolution with Packed Lookup Tables

Convolution plays a central role in many image processing applications including image resizing blurring and sharpening In all such cases each output sample is computed to be a weighted sum of several input pixels This is a computationally expensive operation that is subject to optimization In this gem we describe a novel algorithm to accelerate convolution for those applications that require the same set of lter kernel values to be applied throughout the image The algorithm exploits some nice properties of the convolution summation for this special but common case to minimize the number of pixel fetches and multiply add operations Computational savings are realized by precomputing and packing all necessary products into lookup table elds that are then subjected to simple integer xed point shift add operations