2-D moving average models for texture synthesis and analysis

In this correspondence, a random field model based on moving average (MA) time-series model is proposed for modeling stochastic and structured textures. A frequency domain algorithm to synthesize MA textures is developed, and maximum likelihood estimators are derived. The Cramer–Rao lower bound is also derived for measuring the estimator accuracy. The estimation algorithm is applied to real textures, and images resembling natural textures are synthesized using estimated parameters.