Projects per year
Abstract
Underwater images suffer from color casts and low contrast due to wavelength- and distance-dependent attenuation and scattering. To solve these two degradation issues, we present an underwater image enhancement network via medium transmission-guided multi-color space embedding, called Ucolor. Concretely, we first propose a multi-color space encoder network, which enriches the diversity of feature representations by incorporating the characteristics of different color spaces into a unified structure. Coupled with an attention mechanism, the most discriminative features extracted from multiple color spaces are adaptively integrated and highlighted. Inspired by underwater imaging physical models, we design a medium transmission (indicating the percentage of the scene radiance reaching the camera)-guided decoder network to enhance the response of network towards quality-degraded regions. As a result, our network can effectively improve the visual quality of underwater images by exploiting multiple color spaces embedding and the advantages of both physical model-based and learning-based methods. Extensive experiments demonstrate that our Ucolor achieves superior performance against state-of-the-art methods in terms of both visual quality and quantitative metrics. The code is publicly available at: https://li-chongyi.github.io/Proj_Ucolor.html.
Original language | English |
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Pages (from-to) | 4985-5000 |
Journal | IEEE Transactions on Image Processing |
Volume | 30 |
Online published | 7 May 2021 |
DOIs | |
Publication status | Published - 2021 |
Research Keywords
- underwater imaging
- image enhancement
- color correction
- scattering removal
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Dive into the research topics of 'Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding'. Together they form a unique fingerprint.Projects
- 5 Finished
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GRF: Learning-based Three-dimensional Point Cloud Data Reconstruction and Processing
HOU, J. (Principal Investigator / Project Coordinator)
1/01/21 → 23/12/24
Project: Research
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GRF: Adaptive Dynamic Range Enhancement Oriented to High Dynamic Display
KWONG, T. W. S. (Principal Investigator / Project Coordinator), KUO, J. (Co-Investigator), WANG, S. (Co-Investigator) & Zhang, X. (Co-Investigator)
1/01/21 → 5/09/23
Project: Research
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GRF: Learning Based Hyperspectral Image Reconstruction and Discriminative Representation
HOU, J. (Principal Investigator / Project Coordinator)
1/01/20 → 22/12/23
Project: Research