Abstract
Nowadays, image processing problems are becoming increasingly important due to development of the aerospace Earth monitoring systems, medical devices, etc. But 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 or on a circle. The peculiarity of such images requires its consideration in their models. In the early works of the authors, several models of such images were proposed. These models can also describe quasi-periodic processes. However, these models are single-period ones. Some images and processes can have several quasi-periods. For example, seasonal within annuals, annual rings on a tree cut, etc. In the present paper, autoregressive models of multi-quasi-periodic images and processes are considered. The expressions of their covariance functions are given.
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This study was funded by the RFBR, project number 20-01-00613.
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Krasheninnikov, V.R., Kuvayskova, Y.E., Subbotin, A.U. (2021). Multi-quasi-periodic Cylindrical and Circular Images. In: Czarnowski, I., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies. Smart Innovation, Systems and Technologies, vol 238. Springer, Singapore. https://doi.org/10.1007/978-981-16-2765-1_16
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