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Methods for image noise level estimation
A.I. Novikov 1, A.V. Pronkin 1

Ryazan State Radio Engineering University named after V.F. Utkin,
390005, Ryazan, Russia, Gagarina 59/1

 PDF, 1595 kB

DOI: 10.18287/2412-6179-CO-894

Pages: 713-720.

Full text of article: Russian language.

Abstract:
The article presents a method for estimating the level of discrete white noise in an image, based on the use of linear difference operators with a vector mask. Two variants of a new method for estimating the noise level are proposed, which differ in the accuracy of the obtained estimates and computational complexity. The first version of the method can be attributed to the class of block methods, whereas the second one is intended for the rapid image analysis and is based on processing a small number of rows or columns of an image.

Keywords:
linear smoothing operators, difference operators, cancellation of the deterministic component of the image, noise suppression, noise dispersion.

Citation:
Novikov AI, Pronkin AV. Methods for image noise level estimation. Computer Optics 2021; 45(5): 713-720. DOI: 10.18287/2412-6179-CO-894.

Acknowledgements:
The work was partly funded by the Russian Foundation for Basic Research under project No 19-31-90113 (“Introduction”, “General method of signal linear super-resolution”, “Continuous-discrete observation model”, “Optimal restoration of discrete values of a continuous signal”, “Optimal restoration of discrete values of a continuous signal – frequency domain analysis”, “Error of the optimal restoration” and  “Optimal restoration of a whole continuous signal”) and research project No 19-07-00474 (“Experimental research of the proposed method”).

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