Proceedings ArticleDOI
Underwater image restoration based on minimum information loss principle and optical properties of underwater imaging
Chongyi Li,Jichang Guo,Shanji Chen,Yibin Tang,Yanwei Pang,Jian Wang +5 more
- pp 1993-1997
TLDR
Using the quad-tree subdivision and graph-based segmentation, the global background light can be robustly estimated and the medium transmission map is estimated based on minimum information loss principle and optical properties of underwater imaging.Abstract:
Restoring underwater image from a single image is known to be an ill-posed problem. Some assumptions made in previous methods are not suitable in many situations. In this paper, an effective method is proposed to restore underwater images. Using the quad-tree subdivision and graph-based segmentation, the global background light can be robustly estimated. The medium transmission map is estimated based on minimum information loss principle and optical properties of underwater imaging. Qualitative experiments show that our results are characterized by relatively genuine color, natural appearance, and improved contrast and visibility. Quantitative comparisons demonstrate that the proposed method can achieve better quality of underwater images when compared with several other methods.read more
Citations
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Journal ArticleDOI
An Underwater Image Enhancement Benchmark Dataset and Beyond
TL;DR: This paper constructs an Underwater Image Enhancement Benchmark (UIEB) including 950 real-world underwater images, 890 of which have the corresponding reference images and proposes an underwater image enhancement network (called Water-Net) trained on this benchmark as a baseline, which indicates the generalization of the proposed UIEB for training Convolutional Neural Networks (CNNs).
Journal ArticleDOI
Underwater scene prior inspired deep underwater image and video enhancement
TL;DR: The proposed UWCNN model directly reconstructs the clear latent underwater image, which benefits from the underwater scene prior which can be used to synthesize underwater image training data, and can be easily extended to underwater videos for frame-by-frame enhancement.
Journal ArticleDOI
Generalization of the Dark Channel Prior for Single Image Restoration
TL;DR: The approach can be interpreted as a generalization of the common dark channel prior (DCP) approach to image restoration, and the method reduces to several DCP variants for different special cases of ambient lighting and turbid medium conditions.
Journal ArticleDOI
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
TL;DR: Li et al. as mentioned in this paper proposed an underwater image enhancement network via medium transmission-guided multi-color space embedding, which enriches the diversity of feature representations by incorporating the characteristics of different color spaces into a unified structure.
Journal ArticleDOI
An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
TL;DR: Wang et al. as mentioned in this paper reviewed the image enhancement and restoration methods that tackle typical underwater image impairments, including some extreme degradations and distortions, in terms of the underwater image formation model (IFM).
References
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Efficient Graph-Based Image Segmentation
TL;DR: An efficient segmentation algorithm is developed based on a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image and it is shown that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties.
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Guided Image Filtering
Kaiming He,Jian Sun,Xiaoou Tang +2 more
TL;DR: The guided filter is a novel explicit image filter derived from a local linear model that can be used as an edge-preserving smoothing operator like the popular bilateral filter, but it has better behaviors near edges.
Journal ArticleDOI
Single Image Haze Removal Using Dark Channel Prior
Kaiming He,Jian Sun,Xiaoou Tang +2 more
TL;DR: A simple but effective image prior - dark channel prior to remove haze from a single input image is proposed, based on a key observation - most local patches in haze-free outdoor images contain some pixels which have very low intensities in at least one color channel.
Book ChapterDOI
Guided image filtering
Kaiming He,Jian Sun,Xiaoou Tang +2 more
TL;DR: The guided filter is demonstrated that it is both effective and efficient in a great variety of computer vision and computer graphics applications including noise reduction, detail smoothing/enhancement, HDR compression, image matting/feathering, haze removal, and joint upsampling.
Journal ArticleDOI
Underwater Image Enhancement by Wavelength Compensation and Dehazing
John Y. Chiang,Ying-Ching Chen +1 more
TL;DR: A novel systematic approach to enhance underwater images by a dehazing algorithm, to compensate the attenuation discrepancy along the propagation path, and to take the influence of the possible presence of an artifical light source into consideration is proposed.
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