Mathematical Model for Constructing a Map of the Location of Areas that Make Up the Background Environment for Optical-Electronic Systems
https://doi.org/10.35596/1729-7648-2024-22-1-116-124
Abstract
A developed mathematical model is presented for constructing a map of the location of areas that make up the background environment for optical-electronic systems. A feature of the proposed model is that when determining which class a particular pixel belongs to, the class values of neighboring pixels, as well as the spatial position of the pixel, are simultaneously taken into account. Quantitative assessments of the adequacy of this model and existing mathematical image models capable of constructing maps of the location of areas are given. The proposed model was compared with the Markov model, block Markov model, Gibbs model, block Gibbs model and doubly stochastic model with level quantization. Adequacy assessment was carried out using an artificial neural network developed by the authors, which evaluates the similarity of two images using a normalized similarity index ranging from 0.0 to 1.0, and its k-fold cross-validation. The comparison results showed that the developed model, according to the calculated indicator, is at least three times better than the known ones.
About the Authors
А. V. SiarheyenkaBelarus
Siarheyenka Andrey Vladimirovich, Junior Researcher of the 2nd Group of the Research Laboratory at the Department of Communications and Automated Control Systems
220057, Minsk, Nezavisimosti Ave., 220
Tel.: +375 29 652-62-06
A. Y. Liplianin
Belarus
Cand. of Sci., Head of the Cycle at the Department of Automated Control Systems
Minsk
А. V. Khizhniak
Belarus
Cand. of Sci., Associate Professor, Senior Researcher of the 2nd Group of the Research Laboratory at the Department of Communications and Automated Control Systems
Minsk
References
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3. Siarheyenka A. V., Liplianin A. Y., Khizniak A. V. (2023) Method for Calculating the Adequacy Parameters of Image Mathematical Model. Problems of Physics, Mathematics and Engineering. 56 (3), 94–99 (in Russian).
4. TORCH.NN. PyTorch. Available: https://pytorch.org/docs/stable/nn.html (Accessed 1 August 2023).
5. Cross-Validation: Evaluating Estimator Performance. Scikit-Learn. Available: https://scikit-learn.org/stable/ modules/cross_validation.html (Accessed 1 August 2023).
Review
For citations:
Siarheyenka А.V., Liplianin A.Y., Khizhniak А.V. Mathematical Model for Constructing a Map of the Location of Areas that Make Up the Background Environment for Optical-Electronic Systems. Doklady BGUIR. 2024;22(1):116-124. (In Russ.) https://doi.org/10.35596/1729-7648-2024-22-1-116-124