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Reduction of Images to the Form Typical for Measuring the Distribution of Object Transparency with Subjective Information about Its Sparsity in a Given Basis

  • THEORETICAL AND MATHEMATICAL PHYSICS
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Moscow University Physics Bulletin Aims and scope

Abstract

Experiments on the study of light-sensitive objects or rapidly evolving objects often employ a small number of photons that interact with the object. This leads to poor quality of the reconstructed image of the object. In this situation, mathematical techniques for processing measurements must not only provide a minimum error, but also use all information available to the researcher about the object to further reduce this error. The source of information used together with the measurement results to construct an estimate of the distribution of the optical characteristics of the object can be a researcher’s ideas about the possible form of the distribution of the optical characteristics of the object and about possible noise. A version of the mathematical method of measuring reduction is considered. It allows one to use such information, which is simulated by the mathematical formalism of subjective modeling, and to verify the agreement of subjective information proposed by the researcher with measurement data.

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ACKNOWLEDGMENTS

I am grateful to my supervisor Professor Yu. P. Pyt’ev and Professor A. V. Belinskii.

Funding

This work was supported by the Russian Foundation for Basic Research (project no. 18-07-00424 A).

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Authors and Affiliations

  1. Department of Physics, Moscow State University, 119991, Moscow, Russia

    D. A. Balakin

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  1. D. A. Balakin
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Corresponding author

Correspondence to D. A. Balakin.

Additional information

Translated by I. P. Obrezanova

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Balakin, D.A. Reduction of Images to the Form Typical for Measuring the Distribution of Object Transparency with Subjective Information about Its Sparsity in a Given Basis. Moscow Univ. Phys. 75, 26–34 (2020). https://doi.org/10.3103/S0027134920010038

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  • DOI: https://doi.org/10.3103/S0027134920010038

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