V.R. Krasheninnikov – Dr.Sc.(Eng.), Professor, Head of Department «Applied Mathematics and Informatics», Ulyanovsk State Technical University

E-mail: kvrulstu@mail.ru

A.Yu. Subbotin – Post-graduate Student, Department «Applied Mathematics and Informatics»,  Ulyanovsk State Technical University

E-mail: ashkael@mail.ru

Most of the known models of images describe the images defined on the rectangle. Significantly less work is available on images defined on different surfaces (cylinder, sphere, etc.). In addition, well-known models usually describe images as homogeneous. However, real images often have a significant heterogeneity. In this paper we propose doubly stochastic autoregressive models of inhomogeneous cylindrical images. Heterogeneity is achieved by the fact that random parameters of autoregression of the final image depend on the values of other autoregressive images with the same domain of definition. These models can also be used to describe inhomogeneous quasiperiodic processes.

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