Stochastic texture synthesis for video compression
2008
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.
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