Allocation of three brightness levels on a noisy image

Authors

DOI:

https://doi.org/10.26089/NumMet.v21r216

Keywords:

image reconstruction, verification of statistical hypotheses, binary classification

Abstract

A new recovery method for images with three unknown brightness levels is proposed. In order to determine these levels, we use the image fragments whose histograms correspond to a given noise distribution.  All pixels are distributed over the found brightness levels by a binary classification. The numerical results show the error in the estimate of the original brightnesses is no more than 3%. When the noise level is relatively low, the fraction of wrong classified pixels in their total amount is less than 0.006.

Author Biography

A.V. Likhachov

References

  1. A. A. Potapov, A. A. Pakhomov, S. A. Nikitov, and Yu. V. Gulyaev, Novel Methods of Image Processing (Fizmatlit, Moscow, 2008) [in Russian].
  2. A. R. Dabagov, I. A. Malyutina, and S. A. Filist, Artificial Intelligence Systems for X-Ray Examinations in Digital Medicine (Universitetskaya Kniga, Kursk, 2019).
  3. A. M. Golubkov, “Face Recognition Using Images Binary Classification Methods,” Izv. Saint Petersburg Eletrotekh. Univ., No. 7, 26-30 (2018).
  4. A. Rumyantsev, R. Minyazev, S. Dyganov, et al., “Assessment of the Influence of the Neural Network Architecture Size on the Training Rate in the Problem of Binary Classification,” Vestn. Tekhnol. Univ. 21 (8), 124-127 (2018).
  5. S. A. Aivazian, V. M. Buchstaber, I. S. Yenyukov, and L. D. Meshalkin, Applied Statistics. Vol. 3: Classification and Reduction of Dimensionality (Financy i Statistika, Moscow, 1989) [in Russian].
  6. I. S. Gruzman, V. S. Kirichuk, V. P. Kosykh, et al., Digital Processing of Images in Information Systems (Novosibirsk Gos. Tekh. Univ., Novosibirsk, 2002) [in Russian].
  7. V. S. Pugachev, Theory of Probability and Mathematical Statistics (Nauka, Moscow, 2002) [in Russian].
  8. M. E. Karasikov and Y. V. Maximov, “Dimensionality Reduction for Multi-Class Learning Problems Reduced to Multiple Binary Problems,” Mashinnoe Obuchenie Analiz Dannykh 1 (9), 1273-1290 (2014).
  9. A. V. Likhachov, “Tomographic Reconstruction of a Region with a Given Density Value,” Vychisl. Metody Programm. 19, 516-521 (2018).
  10. A. V. Likhachev, “Modified Method for Detecting Small Structures in Noisy Images,” Avtometriya 55 (6), 55-63 (2019) [Optoelectr., Instrum. Data Process. 55 (6), 580-586 (2019)].

Published

03-07-2020

How to Cite

Лихачев А.В. Allocation of Three Brightness Levels on a Noisy Image // Numerical Methods and Programming (Vychislitel’nye Metody i Programmirovanie). 2020. 21. 180-186. doi 10.26089/NumMet.v21r216

Issue

Section

Section 1. Numerical methods and applications