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Journal of the Optical Society of America A

Journal of the Optical Society of America A

| OPTICS, IMAGE SCIENCE, AND VISION

  • Vol. 18, Iss. 8 — Aug. 1, 2001
  • pp: 1822–1831

Generalized circular autoregressive models for isotropic and anisotropic Gaussian textures

Kie B. Eom  »View Author Affiliations


JOSA A, Vol. 18, Issue 8, pp. 1822-1831 (2001)
http://dx.doi.org/10.1364/JOSAA.18.001822


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Abstract

A new class of random field models, called generalized circular autoregressive (GCAR) models, is introduced. GCAR models have noncausal neighbors that have the same autoregressive parameter values if they are on the same circle or ellipse and that have circular or elliptical correlation structures. This model is better for modeling isotropic or anisotropic natural textures than earlier approaches to modeling of isotropic textures and can represent complex textures with a small number of parameters. Parameter estimation is also considered, and a multistep estimation algorithm is presented. Properties of estimators of GCAR models are also investigated. The efficacy of GCAR models in modeling real textures is demonstrated by synthesizing images resembling real textures by use of parameters estimated from textures selected from the Brodatz texture album. Limitations of GCAR models are also discussed.

© 2001 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.2960) Image processing : Image analysis
(100.5010) Image processing : Pattern recognition
(100.5760) Image processing : Rotation-invariant pattern recognition

Citation
Kie B. Eom, "Generalized circular autoregressive models for isotropic and anisotropic Gaussian textures," J. Opt. Soc. Am. A 18, 1822-1831 (2001)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-18-8-1822


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References

  1. T. R. Reed and J. M. H. du Buf, “A review of recent texture segmentation and feature extraction techniques,” CVGIP Image Understand. 57, 359–372 (1993).
  2. R. L. Kashyap and R. Chellappa, “Estimation and choice of neighbors in spatial-interaction models of images,” IEEE Trans. Inf. Theory 29, 60–69 (1983).
  3. R. L. Kashyap and K. B. Eom, “Texture boundary detection based on long correlation model,” IEEE Trans. Pattern Anal. Mach. Intell. 11, 58–67 (1989).
  4. I. M. Elfadel and R. W. Picard, “Gibbs random fields, co-occurrences, and texture modeling,” IEEE Trans. Pattern Anal. Mach. Intell. 16, 24–37 (1994).
  5. A. Speis and G. Healey, “An analytical and experimental study of the performance of Markov random fields applied to textured images using small samples,” IEEE Trans. Image Process. 5, 447–458 (1996).
  6. J. M. Francos, A. Z. Meiri, and B. Porat, “A unified texture model based on a 2-D Wold-like decomposition,” IEEE Trans. Signal Process. 41, 2665–2677 (1993).
  7. D. J. Heeger and J. R. Bergen, “Pyramid-based texture analysis/synthesis,” Comput. Graph. 229–238 (1995).
  8. R. L. Kashyap and A. Khotanzad, “A model-based method for rotation invariant texture classification,” IEEE Trans. Pattern Anal. Mach. Intell. 8, 472–481 (1986).
  9. K. B. Eom, “2D moving average models for texture synthesis and analysis,” IEEE Trans. Signal Process. 7, 1741–1746 (1998).
  10. P. Brodatz, Textures: A Photographic Album for Artist and Designers (Dover, Mineola, N.Y., 1966).
  11. P. J. Davis, Circulant Matrices (Wiley, New York, 1979), Chap. 5.
  12. A. Rosenfeld and A. Kak, Digital Picture Processing, 2nd ed. (Academic, New York, 1982), Vol. 1.
  13. G. E. P. Box, G. M. Jenkins, and G. C. Reinsel, Time Series Analysis: Forecasting and Control, 3rd ed. (Prentice-Hall, Upper Saddle River, N.J., 1994).
  14. D. R. Brillinger, Time series, Data Analysis and Theory, expanded ed. (Holden Day, San Francisco, Calif., 1981).
  15. P. J. Bickel and K. A. Doksum, Mathematical Statistics: Basic Ideas and Selected Topics (Holden-Day, San Francisco, Calif., 1977).

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