Robust contrast enhancement of noisy low-light images

Denoising-enhancement-completion

Jaemoon Lim, Jin Hwan Kim, Jae Young Sim, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

A robust contrast enhancement algorithm for noisy low-light images, called the denoising-enhancement-completion (DEC), is proposed in this work. We observe that noise components in low-light images degrade the performance of the contrast enhancement. Therefore, we first reduce noise components in an input image. Then, we compute the reliability weight for each pixel, by measuring the difference between the input image and the denoised image, and categorize each pixel into one of two classes: noise-free or noisy. We perform the selective histogram equalization to enhance the contrast of the noise-free pixels only. Finally, we restore missing values of the noisy pixels using the enhanced noise-free pixel values, by employing a low-rank matrix completion scheme. Experimental results show that the proposed DEC algorithm removes noise and enhances the contrast of low-light images more effectively than conventional algorithms.

Original languageEnglish
Title of host publicationProceedings - International Conference on Image Processing, ICIP
PublisherIEEE Computer Society
Pages4131-4135
Number of pages5
Volume2015-December
ISBN (Print)9781479983391
DOIs
Publication statusPublished - 2015 Dec 9
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: 2015 Sep 272015 Sep 30

Other

OtherIEEE International Conference on Image Processing, ICIP 2015
CountryCanada
CityQuebec City
Period15/9/2715/9/30

Fingerprint

Image denoising
Pixels

Keywords

  • contrast enhancement
  • Low-light image enhancement
  • matrix completion
  • noise reduction

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Lim, J., Kim, J. H., Sim, J. Y., & Kim, C-S. (2015). Robust contrast enhancement of noisy low-light images: Denoising-enhancement-completion. In Proceedings - International Conference on Image Processing, ICIP (Vol. 2015-December, pp. 4131-4135). [7351583] IEEE Computer Society. https://doi.org/10.1109/ICIP.2015.7351583

Robust contrast enhancement of noisy low-light images : Denoising-enhancement-completion. / Lim, Jaemoon; Kim, Jin Hwan; Sim, Jae Young; Kim, Chang-Su.

Proceedings - International Conference on Image Processing, ICIP. Vol. 2015-December IEEE Computer Society, 2015. p. 4131-4135 7351583.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Lim, J, Kim, JH, Sim, JY & Kim, C-S 2015, Robust contrast enhancement of noisy low-light images: Denoising-enhancement-completion. in Proceedings - International Conference on Image Processing, ICIP. vol. 2015-December, 7351583, IEEE Computer Society, pp. 4131-4135, IEEE International Conference on Image Processing, ICIP 2015, Quebec City, Canada, 15/9/27. https://doi.org/10.1109/ICIP.2015.7351583
Lim J, Kim JH, Sim JY, Kim C-S. Robust contrast enhancement of noisy low-light images: Denoising-enhancement-completion. In Proceedings - International Conference on Image Processing, ICIP. Vol. 2015-December. IEEE Computer Society. 2015. p. 4131-4135. 7351583 https://doi.org/10.1109/ICIP.2015.7351583
Lim, Jaemoon ; Kim, Jin Hwan ; Sim, Jae Young ; Kim, Chang-Su. / Robust contrast enhancement of noisy low-light images : Denoising-enhancement-completion. Proceedings - International Conference on Image Processing, ICIP. Vol. 2015-December IEEE Computer Society, 2015. pp. 4131-4135
@inproceedings{639dbeebd73b454cb497291dc4deb2c2,
title = "Robust contrast enhancement of noisy low-light images: Denoising-enhancement-completion",
abstract = "A robust contrast enhancement algorithm for noisy low-light images, called the denoising-enhancement-completion (DEC), is proposed in this work. We observe that noise components in low-light images degrade the performance of the contrast enhancement. Therefore, we first reduce noise components in an input image. Then, we compute the reliability weight for each pixel, by measuring the difference between the input image and the denoised image, and categorize each pixel into one of two classes: noise-free or noisy. We perform the selective histogram equalization to enhance the contrast of the noise-free pixels only. Finally, we restore missing values of the noisy pixels using the enhanced noise-free pixel values, by employing a low-rank matrix completion scheme. Experimental results show that the proposed DEC algorithm removes noise and enhances the contrast of low-light images more effectively than conventional algorithms.",
keywords = "contrast enhancement, Low-light image enhancement, matrix completion, noise reduction",
author = "Jaemoon Lim and Kim, {Jin Hwan} and Sim, {Jae Young} and Chang-Su Kim",
year = "2015",
month = "12",
day = "9",
doi = "10.1109/ICIP.2015.7351583",
language = "English",
isbn = "9781479983391",
volume = "2015-December",
pages = "4131--4135",
booktitle = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",

}

TY - GEN

T1 - Robust contrast enhancement of noisy low-light images

T2 - Denoising-enhancement-completion

AU - Lim, Jaemoon

AU - Kim, Jin Hwan

AU - Sim, Jae Young

AU - Kim, Chang-Su

PY - 2015/12/9

Y1 - 2015/12/9

N2 - A robust contrast enhancement algorithm for noisy low-light images, called the denoising-enhancement-completion (DEC), is proposed in this work. We observe that noise components in low-light images degrade the performance of the contrast enhancement. Therefore, we first reduce noise components in an input image. Then, we compute the reliability weight for each pixel, by measuring the difference between the input image and the denoised image, and categorize each pixel into one of two classes: noise-free or noisy. We perform the selective histogram equalization to enhance the contrast of the noise-free pixels only. Finally, we restore missing values of the noisy pixels using the enhanced noise-free pixel values, by employing a low-rank matrix completion scheme. Experimental results show that the proposed DEC algorithm removes noise and enhances the contrast of low-light images more effectively than conventional algorithms.

AB - A robust contrast enhancement algorithm for noisy low-light images, called the denoising-enhancement-completion (DEC), is proposed in this work. We observe that noise components in low-light images degrade the performance of the contrast enhancement. Therefore, we first reduce noise components in an input image. Then, we compute the reliability weight for each pixel, by measuring the difference between the input image and the denoised image, and categorize each pixel into one of two classes: noise-free or noisy. We perform the selective histogram equalization to enhance the contrast of the noise-free pixels only. Finally, we restore missing values of the noisy pixels using the enhanced noise-free pixel values, by employing a low-rank matrix completion scheme. Experimental results show that the proposed DEC algorithm removes noise and enhances the contrast of low-light images more effectively than conventional algorithms.

KW - contrast enhancement

KW - Low-light image enhancement

KW - matrix completion

KW - noise reduction

UR - http://www.scopus.com/inward/record.url?scp=84956659897&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84956659897&partnerID=8YFLogxK

U2 - 10.1109/ICIP.2015.7351583

DO - 10.1109/ICIP.2015.7351583

M3 - Conference contribution

SN - 9781479983391

VL - 2015-December

SP - 4131

EP - 4135

BT - Proceedings - International Conference on Image Processing, ICIP

PB - IEEE Computer Society

ER -