Underwater Image Enhancement Based on the Iteration of a Generalization of Dark Channel Prior

Yosuke Ueki; Masaaki Ikehara

doi:10.1109/VCIP47243.2019.8965726

Underwater Image Enhancement Based on the Iteration of a Generalization of Dark Channel Prior

Yosuke Ueki, Masaaki Ikehara

Department of Electronics and Electrical Engineering

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

8 Citations (Scopus)

Abstract

Underwater image enhancement is important for images captured in underwater because underwater images often suffer from color cast, low contrast and degraded visibility due to the absorption and scattering of light in water. In this paper, we propose a novel algorithm for underwater image restoration based on a generalization of the dark channel prior (GDCP). Though there are various types of underwater images, we especially focus on underwater images with depth because these images are not enhanced well by current algorithms. The proposed algorithm is composed of the iteration of GDCP and image fusion. Additionally, we introduce the new ambient light estimation to adapt to more types of images. Experimental results show that proposed algorithm is effective for various types of underwater images, especially for the images with depth.

Original language	English
Title of host publication	2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728137230
DOIs	https://doi.org/10.1109/VCIP47243.2019.8965726
Publication status	Published - 2019 Dec
Event	34th IEEE International Conference on Visual Communications and Image Processing, VCIP 2019 - Sydney, Australia Duration: 2019 Dec 1 → 2019 Dec 4

Publication series

Name	2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019

Conference

Conference	34th IEEE International Conference on Visual Communications and Image Processing, VCIP 2019
Country/Territory	Australia
City	Sydney
Period	19/12/1 → 19/12/4

Keywords

ambient light estimation
image enhancement
image restoration
transmission estimation
underwater image

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Signal Processing
Computer Networks and Communications
Media Technology

Access to Document

10.1109/VCIP47243.2019.8965726

Cite this

Ueki, Y., & Ikehara, M. (2019). Underwater Image Enhancement Based on the Iteration of a Generalization of Dark Channel Prior. In 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019 Article 8965726 (2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VCIP47243.2019.8965726

Underwater Image Enhancement Based on the Iteration of a Generalization of Dark Channel Prior. / Ueki, Yosuke; Ikehara, Masaaki.
2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8965726 (2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019).

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

Ueki, Y & Ikehara, M 2019, Underwater Image Enhancement Based on the Iteration of a Generalization of Dark Channel Prior. in 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019., 8965726, 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019, Institute of Electrical and Electronics Engineers Inc., 34th IEEE International Conference on Visual Communications and Image Processing, VCIP 2019, Sydney, Australia, 19/12/1. https://doi.org/10.1109/VCIP47243.2019.8965726

Ueki Y, Ikehara M. Underwater Image Enhancement Based on the Iteration of a Generalization of Dark Channel Prior. In 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8965726. (2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019). doi: 10.1109/VCIP47243.2019.8965726

Ueki, Yosuke ; Ikehara, Masaaki. / Underwater Image Enhancement Based on the Iteration of a Generalization of Dark Channel Prior. 2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE International Conference on Visual Communications and Image Processing, VCIP 2019).

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abstract = "Underwater image enhancement is important for images captured in underwater because underwater images often suffer from color cast, low contrast and degraded visibility due to the absorption and scattering of light in water. In this paper, we propose a novel algorithm for underwater image restoration based on a generalization of the dark channel prior (GDCP). Though there are various types of underwater images, we especially focus on underwater images with depth because these images are not enhanced well by current algorithms. The proposed algorithm is composed of the iteration of GDCP and image fusion. Additionally, we introduce the new ambient light estimation to adapt to more types of images. Experimental results show that proposed algorithm is effective for various types of underwater images, especially for the images with depth.",

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AB - Underwater image enhancement is important for images captured in underwater because underwater images often suffer from color cast, low contrast and degraded visibility due to the absorption and scattering of light in water. In this paper, we propose a novel algorithm for underwater image restoration based on a generalization of the dark channel prior (GDCP). Though there are various types of underwater images, we especially focus on underwater images with depth because these images are not enhanced well by current algorithms. The proposed algorithm is composed of the iteration of GDCP and image fusion. Additionally, we introduce the new ambient light estimation to adapt to more types of images. Experimental results show that proposed algorithm is effective for various types of underwater images, especially for the images with depth.

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Underwater Image Enhancement Based on the Iteration of a Generalization of Dark Channel Prior

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Keywords

ASJC Scopus subject areas

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