Texture synthesis by nonparametric sampling

A non-parametric method for texture synthesis is pro-posed. The texture synthesis process grows a new image outward from an initial seed, one pixel at a time. A Markov random field model is assumed, and the conditional distri-bution of a pixel given all its neighbors synthesized so far is estimated by querying the sample image and finding all sim-ilar neighborhoods. The degree of randomness is controlled by a single perceptually intuitive parameter. The method aims at preserving as much local structure as possible and produces good results for a wide variety of synthetic and real-world textures. 1