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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

9 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings of SPIE - The International Society for Optical Engineering
Publisher	SPIE
Volume	9399
ISBN (Print)	9781628414899
DOIs	https://doi.org/10.1117/12.2082533
Publication status	Published - 2015
Publication type	A4 Article in conference proceedings
Event	IS&T/SPIE Electronic Imaging / Image Processing: Algorithms and Systems - Duration: 1 Jan 1900 → …

Conference

Conference	IS&T/SPIE Electronic Imaging / Image Processing: Algorithms and Systems
Period	1/01/00 → …

Keywords

DCT and BM3D filter
Denoising
Fitting
Grayscale images
Prediction

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

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

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10.1117/12.2082533

Cite this

@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. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 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. Vol. 9399 SPIE, 2015. 93990P.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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

Abstract

Conference

Keywords

Publication forum classification

ASJC Scopus subject areas

Access to Document

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Cite this