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Diving deeper into underwater image enhancement: A survey [PDF]
Signal Processing: Image Communication, 2020 The powerful representation capacity of deep learning has made it inevitable for the underwater image enhancement community to employ its potential. The exploration of deep underwater image enhancement networks is increasing over time, and hence; a comprehensive survey is the need of the hour.
Saeed Anwar, Chongyi Li
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U-Shape Transformer for Underwater Image Enhancement
IEEE Transactions on Image Processing, 2023 under ...
Chunli Zhu, Liheng Bian
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Enhancement of Underwater Images [PDF]
International Journal of Engineering Research and, 2020 Underwater photography becomes an important research area in Ocean Engineering, Computer Graphics and Surveillance. But underwater images appear blue-green and hazy since the longer wavelength of sunlight cannot penetrate deep in the water due to salinity and high concentration of dissolve impurities in the seawater.
Vivek Sharma, Rakesh Verma
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Underwater image enhancement with image colorfulness measure [PDF]
Signal Processing: Image Communication, 2021 Abstract Due to the absorption and scattering effects of the water, underwater images tend to suffer from many severe problems, such as low contrast, grayed out colors and blurring content. To improve the visual quality of underwater images, we proposed a novel enhancement model, which is a trainable end-to-end neural model.
Xi Yang 0009 +2 more
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Underwater Images Enhancement by Revised Underwater Images Formation Model
IEEE Access, 2022 In this paper, we proposed the efficient and appealing technique for underwater images enhancement. Underwater images often suffer from haze, color distortion, low contrast and loss of the human acuity due to light scattering and absorption. To tackle these issues, proposed precise model is presented expressively showed that: (1) the estimation of the ...
Soo-Chang Pei, Chia-Yi Chen
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Enhancing underwater images by fusion [PDF]
ACM SIGGRAPH 2011 Posters, 2011 When photographs are taken in underwater conditions the visibility of the scene is degraded significantly. This is due to the fact that the radiance of a point in the scene is directly influenced by the medium scattering. Practically, distant objects and part of the scene suffers from poor visibility, loss of contrast and faded colors.
Cosmin Ancuti +3 more
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A Hybrid Framework for Underwater Image Enhancement [PDF]
IEEE Access, 2020 Underwater captured images often suffer from poor visibility caused by two major degradations: scattering and absorption. In this paper, we propose a hybrid framework for underwater image enhancement, which unifies underwater white balance and variational contrast and saturation enhancement. In our framework, the improved underwater white balance (UWB)
Xinjie Li +3 more
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Underwater image enhancement with Image Colorfulness Measure
CoRR, 2020 Due to the absorption and scattering effects of the water, underwater images tend to suffer from many severe problems, such as low contrast, grayed out colors and blurring content. To improve the visual quality of underwater images, we proposed a novel enhancement model, which is a trainable end-to-end neural model.
Hui Li +3 more
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Domain Adaptation for Underwater Image Enhancement
IEEE Transactions on Image Processing, 2023 Recently, learning-based algorithms have shown impressive performance in underwater image enhancement. Most of them resort to training on synthetic data and achieve outstanding performance. However, these methods ignore the significant domain gap between the synthetic and real data (i.e., interdomain gap), and thus the models trained on synthetic data ...
Zhengyong Wang +5 more
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Deep Underwater Image Enhancement
CoRR, 2018 In an underwater scene, wavelength-dependent light absorption and scattering degrade the visibility of images, causing low contrast and distorted color casts. To address this problem, we propose a convolutional neural network based image enhancement model, i.e., UWCNN, which is trained efficiently using a synthetic underwater image database. Unlike the
Saeed Anwar, Chongyi Li, Fatih Porikli
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