Fast algorithms for histogram matching: Application to texture synthesis

Texture synthesis is the ability to create ensembles of images of similar s tructures from sample textures that have been photographed. The method we e mploy for texture synthesis is based on histogram matching of images at mul tiple scales and orientations. This paper reports two fast and in one case simple algorithms for histogram matching We show that the sort-matching and the optimal cumulative distribution function (CDF)-matching (OCM) algorith ms provide high computational speed compared to that provided by the conven tional approach. The sort-matching algorithm also provides exact histogram matching. Results of texture synthesis using either method show no subjecti ve perceptual differences. The sort-matching algorithm is attractive becaus e of its simplicity and speed, however as the size of the image increases, the OCM algorithm may be preferred for optimal computational speed. (C) 200 0 SPIE and IS&T. [S1017-9909(00)00601-2].