Extending Natural Textures with Multi-Scale Synthesis

Abstract

This paper presents a texture synthesis algorithm that was designed for the tile-less generation of large images of arbitrary size from small sample images. The synthesised texture shows features that are visually similar to the sample over a wide frequency range. The development of the algorithm aimed at achieving high quality results for a large range of natural textures, incorporation of the original samples in the synthesis product, ease of use and good texturing speed even with input sample data two magnitudes larger than used by previous techniques. Like other algorithms we utilise an implicit texture model by copying arbitrary shaped texture patches from the sample to the destination over a multi-scale image pyramid. Our method combines the advantages of different previous techniques with respect to quality. A mixture of exhaustive searching, massive parallel computing and the well-known LBG-algorithm ensures a good balance between texturing quality and speed.