Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images

B. Begovic; V. Stankovic; L. Stankovic

doi:10.1109/ICIP.2011.6115829

Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images

B. Begovic, V. Stankovic, L. Stankovic

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

12 Citations (Scopus)

Abstract

Processing of solar image data has become increasingly important for accurate space weather prediction and expanding our understanding about the Sun and Universe. To enable proper analysis, image denoising and contrast enhancement are essential for removal of all artifacts introduced within the acquisition process. Hence, this paper focuses on these two tasks applied on solar images corrupted with pixel dependent Poisson and zero-mean additive Gaussian noise. The denoising frameworks are build upon on two state-of-the-art techniques, K-SVD and BM3D (for natural images) where contrast enhancement of noisy solar images is performed jointly with noise removal using sparse coding adaptive dictionary learning. Results are given for two conventional sets of solar images.

Original language	English
Title of host publication	Proceedings of the 18th IEEE International Conference on Image Processing (ICIP)
Place of Publication	New York
Publisher	IEEE
Pages	185-188
Number of pages	4
ISBN (Print)	9781457713040
DOIs	https://doi.org/10.1109/ICIP.2011.6115829
Publication status	Published - Sept 2011
Event	ICIP 2011: 2011 IEEE International Conference on Image Processing - Brussels, Belgium Duration: 11 Sept 2011 → 14 Sept 2011

Conference

Conference	ICIP 2011: 2011 IEEE International Conference on Image Processing
Country/Territory	Belgium
City	Brussels
Period	11/09/11 → 14/09/11

Keywords

representation
dictionaries
sparse
sparse coding
curvelet transform
image enhancement
contrast enhancement
solar images
denoising
dictionaries
transforms
noise reduction
noise measurement
image denoising
gaussian noise

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10.1109/ICIP.2011.6115829

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@inproceedings{634a1b7d24d245c9948b97c8f2ba9b93,

title = "Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images",

abstract = "Processing of solar image data has become increasingly important for accurate space weather prediction and expanding our understanding about the Sun and Universe. To enable proper analysis, image denoising and contrast enhancement are essential for removal of all artifacts introduced within the acquisition process. Hence, this paper focuses on these two tasks applied on solar images corrupted with pixel dependent Poisson and zero-mean additive Gaussian noise. The denoising frameworks are build upon on two state-of-the-art techniques, K-SVD and BM3D (for natural images) where contrast enhancement of noisy solar images is performed jointly with noise removal using sparse coding adaptive dictionary learning. Results are given for two conventional sets of solar images. ",

keywords = "representation, dictionaries, sparse , sparse coding, curvelet transform, image enhancement, contrast enhancement, solar images, denoising, dictionaries , transforms , noise reduction , noise measurement , image denoising , gaussian noise ",

author = "B. Begovic and V. Stankovic and L. Stankovic",

year = "2011",

month = sep,

doi = "10.1109/ICIP.2011.6115829",

language = "English",

isbn = "9781457713040",

pages = "185--188",

booktitle = "Proceedings of the 18th IEEE International Conference on Image Processing (ICIP)",

publisher = "IEEE",

note = "ICIP 2011: 2011 IEEE International Conference on Image Processing ; Conference date: 11-09-2011 Through 14-09-2011",

}

Begovic, B, Stankovic, V & Stankovic, L 2011, Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images. in Proceedings of the 18th IEEE International Conference on Image Processing (ICIP). IEEE, New York, pp. 185-188, ICIP 2011: 2011 IEEE International Conference on Image Processing , Brussels, Belgium, 11/09/11. https://doi.org/10.1109/ICIP.2011.6115829

TY - GEN

T1 - Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images

AU - Begovic, B.

AU - Stankovic, V.

AU - Stankovic, L.

PY - 2011/9

Y1 - 2011/9

N2 - Processing of solar image data has become increasingly important for accurate space weather prediction and expanding our understanding about the Sun and Universe. To enable proper analysis, image denoising and contrast enhancement are essential for removal of all artifacts introduced within the acquisition process. Hence, this paper focuses on these two tasks applied on solar images corrupted with pixel dependent Poisson and zero-mean additive Gaussian noise. The denoising frameworks are build upon on two state-of-the-art techniques, K-SVD and BM3D (for natural images) where contrast enhancement of noisy solar images is performed jointly with noise removal using sparse coding adaptive dictionary learning. Results are given for two conventional sets of solar images.

AB - Processing of solar image data has become increasingly important for accurate space weather prediction and expanding our understanding about the Sun and Universe. To enable proper analysis, image denoising and contrast enhancement are essential for removal of all artifacts introduced within the acquisition process. Hence, this paper focuses on these two tasks applied on solar images corrupted with pixel dependent Poisson and zero-mean additive Gaussian noise. The denoising frameworks are build upon on two state-of-the-art techniques, K-SVD and BM3D (for natural images) where contrast enhancement of noisy solar images is performed jointly with noise removal using sparse coding adaptive dictionary learning. Results are given for two conventional sets of solar images.

KW - representation

KW - dictionaries

KW - sparse

KW - sparse coding

KW - curvelet transform

KW - image enhancement

KW - contrast enhancement

KW - solar images

KW - denoising

KW - dictionaries

KW - transforms

KW - noise reduction

KW - noise measurement

KW - image denoising

KW - gaussian noise

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U2 - 10.1109/ICIP.2011.6115829

DO - 10.1109/ICIP.2011.6115829

M3 - Conference contribution book

SN - 9781457713040

SP - 185

EP - 188

BT - Proceedings of the 18th IEEE International Conference on Image Processing (ICIP)

PB - IEEE

CY - New York

T2 - ICIP 2011: 2011 IEEE International Conference on Image Processing

Y2 - 11 September 2011 through 14 September 2011

ER -

Contrast enhancement and denoising of Poisson and Gaussian mixture noise for solar images

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