Enhancing Underwater Color Images via Optical Imaging Model and Non-Local Means Denoising
Summary :
This paper proposes a novel framework for enhancing underwater images captured by optical imaging model and non-local means denoising. The proposed approach adjusts the color balance using biasness correction and the average luminance. Scene visibility is then enhanced based on an underwater optical imaging model. The increase in noise in the enhanced images is alleviated by non-local means (NLM) denoising. The final enhanced images are characterized by improved visibility while retaining color fidelity and reducing noise. The proposed method does not require specialized hardware nor prior knowledge of the underwater environment.
- Publication
- IEICE TRANSACTIONS on Information Vol.E100-D No.7 pp.1475-1483
- Publication Date
- 2017/07/01
- Publicized
- 2017/04/07
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016EDP7486
- Type of Manuscript
- PAPER
- Category
- Image Processing and Video Processing
Authors
Dubok PARK
Korea University
David K. HAN
Office of Naval Research
Hanseok KO
Korea University
Keyword
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Dubok PARK, David K. HAN, Hanseok KO, "Enhancing Underwater Color Images via Optical Imaging Model and Non-Local Means Denoising" in IEICE TRANSACTIONS on Information,
vol. E100-D, no. 7, pp. 1475-1483, July 2017, doi: 10.1587/transinf.2016EDP7486.
Abstract: This paper proposes a novel framework for enhancing underwater images captured by optical imaging model and non-local means denoising. The proposed approach adjusts the color balance using biasness correction and the average luminance. Scene visibility is then enhanced based on an underwater optical imaging model. The increase in noise in the enhanced images is alleviated by non-local means (NLM) denoising. The final enhanced images are characterized by improved visibility while retaining color fidelity and reducing noise. The proposed method does not require specialized hardware nor prior knowledge of the underwater environment.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016EDP7486/_p
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@ARTICLE{e100-d_7_1475,
author={Dubok PARK, David K. HAN, Hanseok KO, },
journal={IEICE TRANSACTIONS on Information},
title={Enhancing Underwater Color Images via Optical Imaging Model and Non-Local Means Denoising},
year={2017},
volume={E100-D},
number={7},
pages={1475-1483},
abstract={This paper proposes a novel framework for enhancing underwater images captured by optical imaging model and non-local means denoising. The proposed approach adjusts the color balance using biasness correction and the average luminance. Scene visibility is then enhanced based on an underwater optical imaging model. The increase in noise in the enhanced images is alleviated by non-local means (NLM) denoising. The final enhanced images are characterized by improved visibility while retaining color fidelity and reducing noise. The proposed method does not require specialized hardware nor prior knowledge of the underwater environment.},
keywords={},
doi={10.1587/transinf.2016EDP7486},
ISSN={1745-1361},
month={July},}
Copy
TY - JOUR
TI - Enhancing Underwater Color Images via Optical Imaging Model and Non-Local Means Denoising
T2 - IEICE TRANSACTIONS on Information
SP - 1475
EP - 1483
AU - Dubok PARK
AU - David K. HAN
AU - Hanseok KO
PY - 2017
DO - 10.1587/transinf.2016EDP7486
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2017
AB - This paper proposes a novel framework for enhancing underwater images captured by optical imaging model and non-local means denoising. The proposed approach adjusts the color balance using biasness correction and the average luminance. Scene visibility is then enhanced based on an underwater optical imaging model. The increase in noise in the enhanced images is alleviated by non-local means (NLM) denoising. The final enhanced images are characterized by improved visibility while retaining color fidelity and reducing noise. The proposed method does not require specialized hardware nor prior knowledge of the underwater environment.
ER -
English
