Title :
2-D moving average models for texture synthesis and analysis
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC, USA
fDate :
12/1/1998 12:00:00 AM
Abstract :
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
Keywords :
frequency-domain analysis; image texture; maximum likelihood estimation; moving average processes; random processes; time series; 2D moving average models; Cramer-Rao lower bound; MA time-series model; estimated parameters; estimation algorithm; estimator accuracy; frequency domain algorithm; maximum likelihood estimators; moving average time-series model; natural textures; random field model; real textures; texture analysis; texture synthesis; Finite impulse response filter; Frequency domain analysis; Frequency estimation; Image texture analysis; Maximum likelihood estimation; Parameter estimation; Stochastic processes; Time series analysis; Wavelet packets; Wavelet transforms;
Journal_Title :
Image Processing, IEEE Transactions on
