Mapping textured images on smoothly approximated surfaces is often used to conceal the loss of their real, fine-grained relief. A limitation of mapping a fixed texture in such cases is that it will only be correct for one viewing and one illumination direction. The presence of geometric surface details causes changes that simple foreshortening and global color scaling cannot model well. Hence, one would like to synthesize different textures for different viewing conditions. A texture model is presented that takes account of viewpoint dependent changes in texture appearance. It is highly compact and avoids copy-and-paste like repetitions. The model is learned from example images taken from different viewpoints. It supports texture synthesis for previously unseen conditions.

The formal definition of image homogeneity and texture is proposed. The notion of double-raster characteristic of the piecewise-homogeneous image is used for stating in a general case the problem of generating the image with the given features. The randomized algorithm of solving this problem by using the double-raster probability model of the image is investigated. The possible applications of the proposed theoretical model are pointed out.