Prediction of signal denoising efficiency for DCT-based filter

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Prediction of signal denoising efficiency for DCT-based filter. / Abramov, S. K.; Abramova, V. V.; Lukin, V. V.; Egiazarian, Karen O.

julkaisussa: Telecommunications and Radio Engineering, Vuosikerta 78, Nro 13, 2019, s. 1129-1142.

Tutkimustuotos › › vertaisarvioitu

Harvard

Abramov, SK, Abramova, VV, Lukin, VV & Egiazarian, KO 2019, 'Prediction of signal denoising efficiency for DCT-based filter', Telecommunications and Radio Engineering, Vuosikerta. 78, Nro 13, Sivut 1129-1142. https://doi.org/10.1615/TelecomRadEng.v78.i13.10

APA

Abramov, S. K., Abramova, V. V., Lukin, V. V., & Egiazarian, K. O. (2019). Prediction of signal denoising efficiency for DCT-based filter. Telecommunications and Radio Engineering, 78(13), 1129-1142. https://doi.org/10.1615/TelecomRadEng.v78.i13.10

Vancouver

Abramov SK, Abramova VV, Lukin VV, Egiazarian KO. Prediction of signal denoising efficiency for DCT-based filter. Telecommunications and Radio Engineering. 2019;78(13):1129-1142. https://doi.org/10.1615/TelecomRadEng.v78.i13.10

Author

Abramov, S. K. ; Abramova, V. V. ; Lukin, V. V. ; Egiazarian, Karen O. / Prediction of signal denoising efficiency for DCT-based filter. Julkaisussa: Telecommunications and Radio Engineering. 2019 ; Vuosikerta 78, Nro 13. Sivut 1129-1142.

Bibtex - Lataa

@article{98fb0290a9944188817e322f4223e3c3,

title = "Prediction of signal denoising efficiency for DCT-based filter",

abstract = "Signals acquired by different sensors are often noisy and are subject to filtering aimed to reduce noise and preserve important information. Although a great number of different filters exist, their performance does not always satisfy users. There are practical situations when denoising does not lead to expected positive effect which makes it useless. In this paper, we show that a denoising efficiency can be predicted for DCT-based filters. This can be accurately done by an analysis of statistics of DCT-coefficients in a limited number of blocks without execution of denoising itself. Peculiarities of preliminary analysis needed to carry out prediction are discussed. It is shown that a prediction is able to perform well for a wide range of signals and signal-to-noise ratios.",

keywords = "Efficiency, Prediction, Signal denoising",

author = "Abramov, {S. K.} and Abramova, {V. V.} and Lukin, {V. V.} and Egiazarian, {Karen O.}",

note = "EXT={"}Lukin, V. V.{"}",

year = "2019",

doi = "10.1615/TelecomRadEng.v78.i13.10",

language = "English",

volume = "78",

pages = "1129--1142",

journal = "Telecommunications and Radio Engineering",

issn = "0040-2508",

publisher = "Begell House",

number = "13",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Prediction of signal denoising efficiency for DCT-based filter

AU - Abramov, S. K.

AU - Abramova, V. V.

AU - Lukin, V. V.

AU - Egiazarian, Karen O.

N1 - EXT="Lukin, V. V."

PY - 2019

Y1 - 2019

N2 - Signals acquired by different sensors are often noisy and are subject to filtering aimed to reduce noise and preserve important information. Although a great number of different filters exist, their performance does not always satisfy users. There are practical situations when denoising does not lead to expected positive effect which makes it useless. In this paper, we show that a denoising efficiency can be predicted for DCT-based filters. This can be accurately done by an analysis of statistics of DCT-coefficients in a limited number of blocks without execution of denoising itself. Peculiarities of preliminary analysis needed to carry out prediction are discussed. It is shown that a prediction is able to perform well for a wide range of signals and signal-to-noise ratios.

AB - Signals acquired by different sensors are often noisy and are subject to filtering aimed to reduce noise and preserve important information. Although a great number of different filters exist, their performance does not always satisfy users. There are practical situations when denoising does not lead to expected positive effect which makes it useless. In this paper, we show that a denoising efficiency can be predicted for DCT-based filters. This can be accurately done by an analysis of statistics of DCT-coefficients in a limited number of blocks without execution of denoising itself. Peculiarities of preliminary analysis needed to carry out prediction are discussed. It is shown that a prediction is able to perform well for a wide range of signals and signal-to-noise ratios.

KW - Efficiency

KW - Prediction

KW - Signal denoising

U2 - 10.1615/TelecomRadEng.v78.i13.10

DO - 10.1615/TelecomRadEng.v78.i13.10

M3 - Article

VL - 78

SP - 1129

EP - 1142

JO - Telecommunications and Radio Engineering

JF - Telecommunications and Radio Engineering

SN - 0040-2508

IS - 13

ER -

TUTCRIS