A Semicausal Model for Recursive Filtering of Two-Dimensional Images

  • Authors:
  • A. K. Jain

  • Affiliations:
  • Department of Electrical Engineering, State University of New York

  • Venue:
  • IEEE Transactions on Computers
  • Year:
  • 1977

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Abstract

A two-dimensional discrete stochastic model for representing images is developed. This representation has lower mean square error, compared to a standard autoregressive Markov representation. Application of the model to linear filtering of images degraded by white noise leads to scalar recursive filtering equations requiring only 0(N2log2N) computations for N x N images. The