An evaluation of stochastic models for analysis and synthesis of gray-scale texture

Abstract Five classes of stochastic models for analysis and synthesis of gray-scale texture are evaluated; Markov models, autocorrelation and histogram models, linear autoregressive models, fractal models and spectral models. The autoregressive models seem to reproduce the largest number of textures with the highest compression rates.

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