Abstract
The solution of many scientific and technical problems involves the extraction of useful information from multidimensional data (images). Mathematical formalization of the problems that arise includes creating models of these images. Despite the large number of works on image models, significant difficulties arise when an image model with preset properties is constructed. This work proposes the use of random field wave models for correlation analysis and the synthesis of multidimensional image models and their sequences. Essentially, these models also make it possible to imitate images with small computational expenditures, is required for testing of various image processing algorithms.
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