Results 11 to 20 of about 12,320,508 (255)

Uncertainty Inspired Underwater Image Enhancement

open access: yes, 2022
A main challenge faced in the deep learning-based Underwater Image Enhancement (UIE) is that the ground truth high-quality image is unavailable. Most of the existing methods first generate approximate reference maps and then train an enhancement network with certainty. This kind of method fails to handle the ambiguity of the reference map.
Zhenqi Fu   +4 more
openaire   +5 more sources

Image-Conditional Diffusion Transformer for Underwater Image Enhancement [PDF]

open access: yes
Underwater image enhancement (UIE) has attracted much attention owing to its importance for underwater operation and marine engineering. Motivated by the recent advance in generative models, we propose a novel UIE method based on image-conditional diffusion transformer (ICDT).
Xingyang Nie   +7 more
core   +4 more sources

A Novel Underwater Image Enhancement Using Optimal Composite Backbone Network. [PDF]

open access: yesBiomimetics (Basel), 2023
Continuous exploration of the ocean has made underwater image processing an important research field, and plenty of CNN (convolutional neural network)-based underwater image enhancement methods have emerged over time.
Chen Y   +6 more
europepmc   +2 more sources

Cross-domain learning for underwater image enhancement [PDF]

open access: yes, 2023
The poor quality of underwater images has become a widely-known cause affecting the performance of the underwater development projects, including mineral exploitation, driving photography, and navigation for autonomous underwater vehicles.
He, X   +5 more
core   +1 more source

INAM-Based Image-Adaptive 3D LUTs for Underwater Image Enhancement. [PDF]

open access: yesSensors (Basel), 2023
To the best of our knowledge, applying adaptive three-dimensional lookup tables (3D LUTs) to underwater image enhancement is an unprecedented attempt. It can achieve excellent enhancement results compared to some other methods.
Xiao X, Gao X, Hui Y, Jin Z, Zhao H.
europepmc   +2 more sources

Multiscale Fusion for Underwater Image Enhancement [PDF]

open access: yes, 2022
In this paper, an enhancement scheme on underwater images is proposed. Underwater images undergo efforts like scattering and attenuation. Many techniques are proposed for underwater image and enhancement that largely depends on the features and ...
E Sasikala Reddy, Kunisetty Sivanihimaja
core   +1 more source

Effective solution for underwater image enhancement

open access: yesOptics Express, 2021
Degradation of underwater images severely limits people to exploring and understanding underwater world, which has become a fundamental but vital issue needing to be addressed in underwater optics. In this paper, we develop an effective solution for underwater image enhancement.
Ye Tao, Lili Dong, Luqiang Xu, Wenhai Xu
openaire   +2 more sources

A Survey of Restoration and Enhancement for Underwater Images [PDF]

open access: yesIEEE Access, 2019
Images captured underwater usually suffer from color distortion, detail blurring, low contrast, and a bluish or greenish tone due to light scattering and absorption in the underwater medium, which in turn the visibility is adversely affected by these factors seriously.
Weidong Zhang 0007   +5 more
openaire   +2 more sources

Unpaired Underwater Image Enhancement Based on CycleGAN

open access: yes, 2021
Underwater image enhancement recovers degraded underwater images to produce corresponding clear images. Image enhancement methods based on deep learning usually use paired data to train the model, while such paired data, e.g., the degraded images and the
Congying Li   +4 more
core   +1 more source

An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging [PDF]

open access: yes, 2019
Underwater images play a key role in ocean exploration, but often suffer from severe quality degradation due to light absorption and scattering in water medium. Although major breakthroughs have been made recently in the general area of image enhancement
Zhang, Wenqiang   +5 more
core   +1 more source

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