Abstract
An efficient recursive algorithm for realistic colour texture synthesis is proposed. The algorithm starts with spectral factorization of an input colour texture image using the Karhunen-Loeve decorrelation. Single orthogonal monospectral components are further decomposed into a multi-resolution grid and each resolution data are independently modeled by their dedicated simultaneous causal autoregressive random field model (CAR). We estimate an optimal contextual neighbourhood and parameters for each CAR submodel. Finally single synthesized monospectral texture pyramids are collapsed into the fine resolution images and using the inverse Karhunen-Loeve transformation we obtain the required colour texture. The benefit of the multigrid approach is the replacement of a large neighbourhood CAR model with a set of several simpler CAR models which are easy to synthesize and wider application area of these multigrid models capable of reproducing realistic textures for enhancing realism in texture application areas.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Besag, J.: Spatial Interaction and the Statistical Analysis of Lattice Systems. J. Royal Stat. Soc. B-36 (1974) 192–236
Gidas, B.: A renormalization Group Approach to Image Processing problems. IEEE Trans. Pattern Anal. Mach. Int. 11 (1989) 164–180
Haindl, M.:Texture Synthesis. Research Report no. CS-R9139, Centrum voor Wis-kunde en Informatica, Amsterdam, 1991
Haindl, M.: Texture Synthesis. CWI Quarterly 4 (1991) 305–331
Haindl, M., Havlíček, V.: Multiresolution Colour Texture Synthesis. In: Dobro-vodský, K. (ed.): Proceedings 7th Int. Workshop RAAD’98, ISBN: 80-967962-7-5, ASCO Art & Science, Bratislava (1998) 339–344
Kashyap, R.L.: Analysis and Synthesis of Image Patterns by Spatial Interaction Models. In: Progress in Pattern Recognition 1, (Eds.) L.N. Kanal A. Rosenfeld, Elsevier, North-Holland (1981)
Rosenfeld, A. (ed.): Multiresolution Image Processing and Analysis. Springer-Verlag, Berlin Heidelberg New York (1984)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Haindl, M., Havlíček, V. (2000). A Multiresolution Causal Colour Texture Model. In: Ferri, F.J., Iñesta, J.M., Amin, A., Pudil, P. (eds) Advances in Pattern Recognition. SSPR /SPR 2000. Lecture Notes in Computer Science, vol 1876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44522-6_12
Download citation
DOI: https://doi.org/10.1007/3-540-44522-6_12
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67946-2
Online ISBN: 978-3-540-44522-7
eBook Packages: Springer Book Archive