2-D autoregressive, finite support, causal model for texture analysis and synthesis

Joseph M. Francos, A. Zvi Meiri

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations


A 2-D AR (autoregressive), finite-support, half-plane, causal model for homogeneous random fields is developed and applied to the analysis and synthesis of homogeneous random textures. The conditions under which the finite, discontinuous-support, 2-D Levinson type algorithm can be applied to solve the 2-D normal equations are presented. In the texture analysis case, these conditions are met by first removing all periodic components and subsequently applying a 2-D preemphasis filter. These steps also help reduce the required model order. It is shown that the resulting model is very efficient in terms of both the number of parameters required to achieve a good reconstructed texture (which is usually indistinguishable from the original) and good correlation match.

Original languageEnglish
Pages (from-to)1552-1555
Number of pages4
JournalProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
StatePublished - 1 Dec 1989
Externally publishedYes
Event1989 International Conference on Acoustics, Speech, and Signal Processing - Glasgow, Scotland
Duration: 23 May 198926 May 1989

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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