Stochastic texture synthesis for video compression

Low-bitrate digital video often suffers from the artifact of texture flattening. Texture synthesis can be used to revive the removed texture. Patch-based synthesis provides a quite general method for texture synthesis. However, this method still requires a substantial bitrate to transmit example patches. We propose a method for stochastic texture synthesis which requires only a very low bitrate (less than 1 kbit/sec) that can replace patch-based synthesis for random textures. Spatial correlation is modeled as a 2-dimensional Moving Average (MA) process. To achieve a faithful representation of temporal evolution, we use a translation+scaling motion model combined with a finite impulse response (FIR) filter. Experiments show that we can successfully reduce texture flattening for a range of random textures such as grass and roads.