Markov iterated function system model of images

Huiguo Luo; Yaoting Zhu; Guang-Xi Zhu; Faguang Wan

doi:10.1117/12.139106

12 January 1993 Markov iterated function system model of images

Huiguo Luo, Yaoting Zhu, Guang-Xi Zhu, Faguang Wan

Proceedings Volume 1771, Applications of Digital Image Processing XV; (1993) https://doi.org/10.1117/12.139106
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

All images have two basic characters: geometry and texture. Basing the two characters, we present Markov Iterated Function System (MIFS) model, consisting of Iterated Function System (IFS) and Markov Random Field (MRF). The fractal images have self-similarities in statistics, especially in geometric topological structure. IFS is useful for discribing the self- similarities. In the meantime, we consider a texture to be a stochastic field and usually it is anisotropic. We choose MRF as the model of the texture. It is convenient to control the geometric characters and texture through changing the parameters of MIFS model. We explored a fast iterated algorithm to realize a MIFS sample and an algorithm to estimate the parameters of MIFS.

Citation Download Citation

Huiguo Luo, Yaoting Zhu, Guang-Xi Zhu, and Faguang Wan "Markov iterated function system model of images", Proc. SPIE 1771, Applications of Digital Image Processing XV, (12 January 1993); https://doi.org/10.1117/12.139106

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