Pseudo-gradient algorithm for identification of doubly stochastic cylindrical image model
| Autor: | Alexey U. Subbotin, Yuliya E. Kuvayskova, Victor Krasheninnikov |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION System identification 020206 networking & telecommunications Image processing Statistical model 02 engineering and technology Correlation function (quantum field theory) Sonar Image (mathematics) Dimension (vector space) Autoregressive model Computer Science::Computer Vision and Pattern Recognition 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing Algorithm General Environmental Science |
| Zdroj: | KES |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2020.09.225 |
| Popis: | Nowadays, image processing problems are becoming increasingly important due to development of the aerospace Earth monitoring systems, radio and sonar systems, medical devices for early diagnosis etc. But the most of the image processing works deal with images defined on rectangular two-dimensional grids or grids of higher dimension. In some practical situations, images are set on a cylinder. For example, images of a section of pipelines, worms, blood vessel, parts during turning, etc. The peculiarity of the domain for specifying such images requires its consideration in their models and processing algorithms. In the present paper, autoregressive models of cylindrical images are considered, expressions of the correlation function depending on the autoregression parameters are given. To represent heterogeneous images with random heterogeneities, «doubly stochastic» models are used in which one or more images control the parameters of the resulting image. The spiral scan of a cylindrical image can be considered as a quasiperiodic process due to the correlation of image rows. Pseudo-gradient algorithms for the modal identification are proposed. The statistical modeling showed that these algorithms give good model identification. |
| Databáze: | OpenAIRE |
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