3D image denoising using stereo correspondences

Ngai Li; Jim S. Jimmy Li; Sharmil Randhawa

doi:10.1109/TENCON.2015.7372926

3D image denoising using stereo correspondences

Ngai Li, Jim S. Jimmy Li, Sharmil Randhawa

College of Science and Engineering

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

Abstract

In this paper, we propose an image denoising algorithm for 3D demosaicked images. Each color component of the 3D stereo images is processed for noise reduction by identifying the stereo correspondences between two stereo images at subpixel accuracy. Using our proposed method, it has been experimentally shown that there is visual improvement in the demosaicked output images using a realistic signal-dependent noise model with demonstration of a higher signal-to-noise ratio (SNR).

Original language	English
Title of host publication	TENCON 2015 - 2015 IEEE Region 10 Conference
Publisher	Institute of Electrical and Electronics Engineers
ISBN (Electronic)	9781479986415
DOIs	https://doi.org/10.1109/TENCON.2015.7372926
Publication status	Published - 5 Jan 2016
Event	TENCON: IEEE Region 10 International Conference - Macao, China Duration: 1 Nov 2015 → 4 Nov 2015 https://ieeexplore.ieee.org/xpl/conhome/7365563/proceeding

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume	2016-January
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Conference

Conference	TENCON
Country/Territory	China
City	Macao
Period	1/11/15 → 4/11/15
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7365563/proceeding

Keywords

3D images
demosaicking
image denoising
stereo correspondences

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10.1109/TENCON.2015.7372926Licence: In Copyright

Cite this

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title = "3D image denoising using stereo correspondences",

abstract = "In this paper, we propose an image denoising algorithm for 3D demosaicked images. Each color component of the 3D stereo images is processed for noise reduction by identifying the stereo correspondences between two stereo images at subpixel accuracy. Using our proposed method, it has been experimentally shown that there is visual improvement in the demosaicked output images using a realistic signal-dependent noise model with demonstration of a higher signal-to-noise ratio (SNR).",

keywords = "3D images, demosaicking, image denoising, stereo correspondences",

author = "Ngai Li and {Jimmy Li}, {Jim S.} and Sharmil Randhawa",

year = "2016",

month = jan,

day = "5",

doi = "10.1109/TENCON.2015.7372926",

language = "English",

series = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",

publisher = "Institute of Electrical and Electronics Engineers",

booktitle = "TENCON 2015 - 2015 IEEE Region 10 Conference",

address = "United States",

note = "TENCON : IEEE Region 10 International Conference ; Conference date: 01-11-2015 Through 04-11-2015",

url = "https://ieeexplore.ieee.org/xpl/conhome/7365563/proceeding",

}

3D image denoising using stereo correspondences. / Li, Ngai; Jimmy Li, Jim S.; Randhawa, Sharmil.
TENCON 2015 - 2015 IEEE Region 10 Conference. Institute of Electrical and Electronics Engineers, 2016. 7372926 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2016-January).

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

TY - GEN

T1 - 3D image denoising using stereo correspondences

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AU - Jimmy Li, Jim S.

AU - Randhawa, Sharmil

PY - 2016/1/5

Y1 - 2016/1/5

N2 - In this paper, we propose an image denoising algorithm for 3D demosaicked images. Each color component of the 3D stereo images is processed for noise reduction by identifying the stereo correspondences between two stereo images at subpixel accuracy. Using our proposed method, it has been experimentally shown that there is visual improvement in the demosaicked output images using a realistic signal-dependent noise model with demonstration of a higher signal-to-noise ratio (SNR).

AB - In this paper, we propose an image denoising algorithm for 3D demosaicked images. Each color component of the 3D stereo images is processed for noise reduction by identifying the stereo correspondences between two stereo images at subpixel accuracy. Using our proposed method, it has been experimentally shown that there is visual improvement in the demosaicked output images using a realistic signal-dependent noise model with demonstration of a higher signal-to-noise ratio (SNR).

KW - 3D images

KW - demosaicking

KW - image denoising

KW - stereo correspondences

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U2 - 10.1109/TENCON.2015.7372926

DO - 10.1109/TENCON.2015.7372926

M3 - Conference contribution

T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON

BT - TENCON 2015 - 2015 IEEE Region 10 Conference

PB - Institute of Electrical and Electronics Engineers

T2 - TENCON

Y2 - 1 November 2015 through 4 November 2015

ER -

3D image denoising using stereo correspondences

Abstract

Publication series

Conference

Keywords

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