A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

Aleksey S. Rubel; Vladimir V. Lukin; Karen Egiazarian

doi:10.1117/12.2082533

A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

Aleksey S. Rubel
, Vladimir V. Lukin^*
, Karen Egiazarian

^*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

9 Sitaatiot (Scopus)

Abstrakti

Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.

Alkuperäiskieli	Englanti
Otsikko	Proceedings of SPIE - The International Society for Optical Engineering
Kustantaja	SPIE
Vuosikerta	9399
ISBN (painettu)	9781628414899
DOI - pysyväislinkit	https://doi.org/10.1117/12.2082533
Tila	Julkaistu - 2015
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	IS&T/SPIE ELECTRONIC IMAGING / IMAGE PROCESSING: ALGORITHMS AND SYSTEMS - Kesto: 1 tammik. 1900 → …

Conference

Conference	IS&T/SPIE ELECTRONIC IMAGING / IMAGE PROCESSING: ALGORITHMS AND SYSTEMS
Ajanjakso	1/01/00 → …

Julkaisufoorumi-taso

Jufo-taso 1

!!ASJC Scopus subject areas

Applied Mathematics
Computer Science Applications
Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials
Condensed Matter Physics

Pääsy asiakirjaan

10.1117/12.2082533

Siteeraa tätä

@inproceedings{638075f046bd4bea8f9cd8868cdd4cce,

title = "A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise",

abstract = "Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.",

keywords = "DCT and BM3D filter, Denoising, Fitting, Grayscale images, Prediction",

author = "Rubel, \{Aleksey S.\} and Lukin, \{Vladimir V.\} and Karen Egiazarian",

year = "2015",

doi = "10.1117/12.2082533",

language = "English",

isbn = "9781628414899",

volume = "9399",

booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

address = "United States",

note = "IS\&T/SPIE Electronic Imaging / Image Processing: Algorithms and Systems ; Conference date: 01-01-1900",

}

Rubel, AS, Lukin, VV & Egiazarian, K 2015, A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise. julkaisussa Proceedings of SPIE - The International Society for Optical Engineering. Vuosikerta 9399, 93990P, SPIE, IS&T/SPIE ELECTRONIC IMAGING / IMAGE PROCESSING: ALGORITHMS AND SYSTEMS, 1/01/00. https://doi.org/10.1117/12.2082533

A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise. / Rubel, Aleksey S.; Lukin, Vladimir V.; Egiazarian, Karen.
Proceedings of SPIE - The International Society for Optical Engineering. Vuosikerta 9399 SPIE, 2015. 93990P.

Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

TY - GEN

T1 - A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

AU - Rubel, Aleksey S.

AU - Lukin, Vladimir V.

AU - Egiazarian, Karen

PY - 2015

Y1 - 2015

N2 - Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.

AB - Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.

KW - DCT and BM3D filter

KW - Denoising

KW - Fitting

KW - Grayscale images

KW - Prediction

U2 - 10.1117/12.2082533

DO - 10.1117/12.2082533

M3 - Conference contribution

AN - SCOPUS:84928473717

SN - 9781628414899

VL - 9399

BT - Proceedings of SPIE - The International Society for Optical Engineering

PB - SPIE

T2 - IS&T/SPIE Electronic Imaging / Image Processing: Algorithms and Systems

Y2 - 1 January 1900

ER -

A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

Abstrakti

Conference

Julkaisufoorumi-taso

!!ASJC Scopus subject areas

Pääsy asiakirjaan

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