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Frequency algorithms of adaptive nonlinear filtration of image sequences

Keywords:

V.N. Lagutkin


The article is dedicated to questions of expansion of proposed by Bol’shakov I.A. and Repin V.G. method of quasi-linear filtration, based on gauss approximation of posterior distribution of estimated parameters, as applied to new tasks of processing of image sequences. Optimum frequency algorithms of serial processing of images are proposed, which are using two-dimensional Fourier transformation for obtaining of parametric models of observed situation. In the network of common adaptive approach to a problem following algorithms are developed: filtration of variable background and moving objects extraction in images, compensation of random shifts and improvement of image resolution, compensation phase distortions of images and reconstruction of undistorted images of objects, observed through turbulence atmosphere. In article united theoretical foundations of these algorithms are considered, as well as differences, caused by particularities of observation conditions. Results of testing of developed algorithms are presented, which illustrate there efficiency.
References:

 

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May 29, 2020

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