Abstract—The representation of spatially inhomogeneous images using double stochastic autoregressive models is considered. The possibility of synthesizing semicausal double stochastic image filtering algorithms based on such models is shown. Variants for reducing the computational costs required to implement double stochastic filters using cascades of moving windows are considered. A comparative analysis of the proposed algorithms with well-known counterparts is carried out, confirming the practical possibility of using double stochastic filters for processing real two-dimensional images.
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The study was financially supported by the Russian Foundation for Basic Research (project nos. 18-47-730009 and 19-29-09048).
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Vasiliev, K.K., Dementyev, V.E. Double Stochastic Filtration of Spatially Inhomogeneous Images. J. Commun. Technol. Electron. 65, 524–531 (2020). https://doi.org/10.1134/S1064226920040099
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DOI: https://doi.org/10.1134/S1064226920040099