Probabilistic finite modeling of stochastic estimation of image inter-frame geometric deformations

The paper proposes an approach to probabilistic finite modeling of the process of stochastic estimation of the parameters of interframe geometric deformations of images. As the quantities characterizing the state of the stochastic procedure at each iteration of the estimation, the demolition probabi...

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Bibliographic Details
Published in:Journal of physics. Conference series 2019-11, Vol.1368 (3), p.32013
Main Authors: Tashlinskii, A G, Safina, G L, Kovalenko, R O
Format: Article
Language:English
Subjects:
Adequacy
Algorithms
Autocorrelation functions
Deformation
Demolition
Estimates
Iterative methods
Mathematical models
Parameter estimation
Physics
Probability theory
Statistical analysis
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Summary:The paper proposes an approach to probabilistic finite modeling of the process of stochastic estimation of the parameters of interframe geometric deformations of images. As the quantities characterizing the state of the stochastic procedure at each iteration of the estimation, the demolition probabilities of the formed parameter estimates (improvements, deterioration, or no change in the vector of estimates in the parameter space) are used. At the same time, the models of images and noises are given by probability distribution densities and autocorrelation functions. This made it possible to simplify the description of a complex set of factors influencing the formation of estimates. The use of adaptive limitation of the parameter space used for modeling reduces the computational cost several times while maintaining the adequacy of the model. In practice, probabilistic modeling can be used to find the accuracy and probability characteristics of stochastic algorithms for estimating interframe deformations of images for a given number of iterations.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1368/3/032013