Underwater Image Dehazing Using The Color Space Dimensionality Reduction Prior

<span lang="EN-IN">Underwater images are prone to contrast loss, limited visibility, and undesirable color cast. For underwater computer vision and pattern recognition algorithms, these images need to be pre-processed. We have addressed a novel solution to this problem by proposing fully automated underwater image dehazing using multimodal DWT fusion. Inputs for the combinational image fusion scheme are derived from Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) for contrast enhancement in HSV color space and color constancy using Shades of Gray algorithm respectively. To appraise the work conducted, the visual and quantitative analysis is performed. The restored images demonstrate improved contrast and effective enhancement in overall image quality and visibility. The proposed algorithm performs on par with the recent underwater dehazing techniques.</span>

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Underwater Single Image Dehazing Using the Color Space Dimensionality Reduction Prior

IEEE Access ◽

10.1109/access.2020.2994614 ◽

2020 ◽

Vol 8 ◽

pp. 91116-91128

Author(s):

Yongbin Liu ◽

Shenghui Rong ◽

Xueting Cao ◽

Tengyue Li ◽

Bo He

Keyword(s):

Dimensionality Reduction ◽

Color Space ◽

Single Image ◽

Image Dehazing ◽

Single Image Dehazing

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Underwater Image Enhancement Method Combining color and Luminance

Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) ◽

10.2174/2352096513999201026225829 ◽

2020 ◽

Vol 13 ◽

Author(s):

ZHAO Baiting ◽

WANG Feng ◽

JIA Xiaofen ◽

GUO Yongcun ◽

WANG Chengjun

Keyword(s):

Image Enhancement ◽

Color Space ◽

Low Frequency ◽

Brightness Enhancement ◽

Color Distortion ◽

Underwater Image ◽

Enhancement Method ◽

Frequency Components ◽

Image Contour ◽

Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

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Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding

IEEE Transactions on Image Processing ◽

10.1109/tip.2021.3076367 ◽

2021 ◽

pp. 1-1

Author(s):

Chongyi Li ◽

Saeed Anwar ◽

Junhui Hou ◽

Runmin Cong ◽

Chunle Guo ◽

...

Keyword(s):

Image Enhancement ◽

Color Space ◽

Underwater Image

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Robust Chromatic Adaptation Based Color Correction Technology for Underwater Images

Applied Sciences ◽

10.3390/app10186392 ◽

2020 ◽

Vol 10 (18) ◽

pp. 6392

Author(s):

Xieliu Yang ◽

Chenyu Yin ◽

Ziyu Zhang ◽

Yupeng Li ◽

Wenfeng Liang ◽

...

Keyword(s):

Color Space ◽

Color Correction ◽

Test Methods ◽

Chromatic Adaptation ◽

Water Type ◽

Underwater Image ◽

Other Information ◽

Color Restoration ◽

Color Cast ◽

Imaging Conditions

Recovering correct or at least realistic colors of underwater scenes is a challenging issue for image processing due to the unknown imaging conditions including the optical water type, scene location, illumination, and camera settings. With the assumption that the illumination of the scene is uniform, a chromatic adaptation-based color correction technology is proposed in this paper to remove the color cast using a single underwater image without any other information. First, the underwater RGB image is first linearized to make its pixel values proportional to the light intensities arrived at the pixels. Second, the illumination is estimated in a uniform chromatic space based on the white-patch hypothesis. Third, the chromatic adaptation transform is implemented in the device-independent XYZ color space. Qualitative and quantitative evaluations both show that the proposed method outperforms the other test methods in terms of color restoration, especially for the images with severe color cast. The proposed method is simple yet effective and robust, which is helpful in obtaining the in-air images of underwater scenes.

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Genetic Algorithm-based Dark Channel Prior Parameters Selection for Single Underwater Image Dehazing

2020 IEEE REGION 10 CONFERENCE (TENCON) ◽

10.1109/tencon50793.2020.9293849 ◽

2020 ◽

Author(s):

Vincent Jan D. Almero ◽

Ronnie S. Concepcion ◽

Jonnel D. Alejandrino ◽

Argel A. Bandala ◽

Jason L. Espanola ◽

...

Keyword(s):

Genetic Algorithm ◽

Dark Channel Prior ◽

Image Dehazing ◽

Underwater Image ◽

Parameters Selection ◽

Dark Channel ◽

Selection For

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Single Underwater Image Restoration By Multi-Scale Fusion In Multi-Color Space

10.1109/bcd51206.2021.9581847 ◽

2021 ◽

Author(s):

Zhuang Zhou ◽

Lili Wang ◽

Binghua Su ◽

Jialin Tang ◽

Yaqing Feng ◽

...

Keyword(s):

Image Restoration ◽

Color Space ◽

Multi Scale ◽

Underwater Image

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A Contrast-Guided Approach for the Enhancement of Low-Lighting Underwater Images

Journal of Imaging ◽

10.3390/jimaging5100079 ◽

2019 ◽

Vol 5 (10) ◽

pp. 79 ◽

Cited By ~ 1

Author(s):

Tunai Porto Marques ◽

Alexandra Branzan Albu ◽

Maia Hoeberechts

Keyword(s):

Automated Analysis ◽

Local Contrast ◽

Single Image ◽

Image Dehazing ◽

Artificial Lighting ◽

Lighting Conditions ◽

Underwater Image ◽

Low Visibility ◽

Contrast Information ◽

New Framework

Underwater images are often acquired in sub-optimal lighting conditions, in particular at profound depths where the absence of natural light demands the use of artificial lighting. Low-lighting images impose a challenge for both manual and automated analysis, since regions of interest can have low visibility. A new framework capable of significantly enhancing these images is proposed in this article. The framework is based on a novel dehazing mechanism that considers local contrast information in the input images, and offers a solution to three common disadvantages of current single image dehazing methods: oversaturation of radiance, lack of scale-invariance and creation of halos. A novel low-lighting underwater image dataset, OceanDark, is introduced to assist in the development and evaluation of the proposed framework. Experimental results and a comparison with other underwater-specific image enhancement methods show that the proposed framework can be used for significantly improving the visibility in low-lighting underwater images of different scales, without creating undesired dehazing artifacts.

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