Application of Global Optimization for Retrievals from Synthetic Multi-Angle Measurements

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Application of Global Optimization for Retrievals from Synthetic Multi-Angle Measurements

Светотехника (перевод). 2024. Vol. 32. P. 11–19.

Чупров И. А., Gao J., Efremenko D., Buzaev F.

The retrieval of parameters for a turbid medium presents a challenging and ill-posed inverse problem. In this paper, we investigate the effectiveness of utilizing global optimization algorithms to determine optical properties of the medium such as the optical thickness, the single scattering albedo, the single scattering phase function, and the extinction profile from multi-angle radiance measurements. For this purpose, we consider the application of the Differential Evolution, SHGO, and Dual Annealing solvers.
To address the phase function retrieval problem, we introduce an enhanced modification of Differential Evolution capable of handling this complex task. In the context of phase function retrieval, we find that global optimization solvers demonstrate comparable efficiency when compared to the Gauss-Newton method, which requires the computation of Jacobians. In the case of the extinction profile problem, the incorporation of Jacobian estimation, coupled with Tikhonov regularization, leads to significant enhancements in retrieval accuracy.

Language: English

SOLUTION OF THE RADIATIVE TRANSFER EQUATION FOR VERTICALLY INHOMOGENEOUS MEDIA BY NUMERICAL INTEGRATION SOLVERS: COMPARATIVE ANALYSIS

Chuprov, I. A., Konstantinov D. N., Efremenko D. et al., Светотехника (перевод) 2022 Vol. 30 No. 5 P. 21–30

An efficiency of the singular value decomposition (SVD) method and ordinary differential equation (ODE) solvers in finding the reflection matrix are compared. A reflection matrix can be found by solving the one-dimensional radiative transfer equation. The latter’s solution based on the discrete ordinate method leads to the singular value decomposition (SVD) method. Alternative approach consists ...

Added: September 22, 2023

Algorithms for Solving Variational Inequalities and Saddle Point Problems with Some Generalizations of Lipschitz Property for Operators

Titov A., Stonyakin F., Alkousa M. et al., , in: Mathematical Optimization Theory and Operations Research: Recent Trends: 20th International Conference, MOTOR 2021, Irkutsk, Russia, July 5–10, 2021, Revised Selected Papers.: Cham: Springer, 2021. Ch. 6 P. 86–101.

Added: October 26, 2021

Accelerated Gradient-Free Optimization Methods with a Non-Euclidean Proximal Operator

Vorontsova E., Gasnikov A., Dvurechensky P. et al., Automation and Remote Control 2019 Vol. 80 No. 8 P. 1487–1501

We propose an accelerated gradient-free method with a non-Euclidean proximal operator associated with the p-norm (1 ⩽ p ⩽ 2). We obtain estimates for the rate of convergence of the method under low noise arising in the calculation of the function value. We present the results of computational experiments. ...

Added: December 10, 2019