Abstract
In this report the theory of spectral estimation of signals on based of generalized two-dimensional (2D) Kravchenko-Kotel’nikov-Levitan theorems is considered. In the first part the 2D weight functions with support area of the complex shape on the basis of R-functions are constructed. In the second part the 2D Kravchenko-Kotel’nikov-Levitan theorems are formulated. In the third part it’s application for spectral estimation, filtering and correction of 2D signals and images. As the examples the problems of noise reduction, scaling and also spectral properties improvement of images are submited. The numerical experiment and physical analysis of 2D signal processing results are show efficiency of new 2D kernels construction of sampling theorems.
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