2-D moving average models for texture synthesis and analysis

  • Authors:
  • K. B. Eom

  • Affiliations:
  • Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 1998

Quantified Score

Hi-index 0.01

Visualization

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