Doubly stochastic models of cylindrical images
- 1 д.т.н., профессор, зав. кафедрой «Прикладная математика и информатика», Ульяновский государственный технический университет
- 2 аспирант, кафедра «Прикладная математика и информатика», Ульяновский государственный технический университет
Abstract
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.
How to cite
Крашенинников В.Р., Субботин А.Ю. Дважды стохастические модели цилиндрических изображений // Радиотехника. 2018. № 6. С. 5–8.
References
- Gonzales R.C., Woods R.E. Digital Image Processing. Edn. 3th. Prentice-Hall. 2017. 976 p.
- Habibi A. Two-dimensional Bayesian Estimate of Images // Proc. IEEE. 1972. 60(7). P. 878−883.
- Krasheninnikov V.R., Vasiliev K.K. Multidimensional Image Models and Processing // Intelligent Systems Reference Library 135. Springer International Publishing. 2018. P. 11−64.
- Shaly’gin A.S., Palagin Yu.A. Prikladny’e metody’ statisticheskogo modelirovaniya. L.: Mashinostroenie. 1986. 320 s.
- Woods J.W., Dravida S., Mediavilla R. Image Estimation Using Doubly Stochastic Gaussian Random Field Models // Pattern Analysis and Machine Intelligence. 1987. V. 9. № 2. P. 245−253.
- Vasil’ev K.K., Krasheninnikov V.R. Statisticheskij analiz posledovatel’nostej izobrazhenij. M.: Radiotexnika. 2017. 248 s.
- Vasil’ev K.K., Dement’ev V.E. Predstavlenie i obrabotka sputnikovy’x mnogozonal’ny’x izobrazhenij. Ul’yanovsk: Izd-vo UlGTU. 2017. 251 s.
- Vasil’ev K.K., Dement’ev V.E., Andriyanov N.A. Analiz e’ffektivnosti oczenivaniya izmenyayushhixsya parametrov dvazhdy’ stoxasticheskoj modeli // Radiotexnika. 2015. № 6. S. 12−15.
- Vasiliev K.K., Dementiev V.E., Andriyanov N.A. Filtration and Restoration of Satellite Images Using Doubly Stochastic Random Fields // CEUR Workshop Proceedings. 2017. V. 1814. P. 10−20.
- Krasheninnikov V.R., Kuvajskova Yu.E. Prognozirovanie dinamiki ob’‘ekta s ispol’zovaniem avtoregressionny’x modelej na czilindre // Radiotexnika. 2016. № 9. S. 36−39.