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Multiscale Fusion for Underwater Image Enhancement

International Journal of Emerging Research in Engineering, Science, and Management, 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 ...
Kunisetty Sivanihimaja, E Sasikala Reddy
doaj   +1 more source

Integrating deep learning and traditional image enhancement techniques for underwater image enhancement

IET Image Processing, 2022
Underwater images usually suffer from colour distortion, blur, and low contrast, which hinder the subsequent processing of underwater information. To address these problems, this paper proposes a novel approach for single underwater images enhancement by
Zhenghao Shi, Yongli Wang, Zhaorun Zhou, Wenqi Ren   +3 more
doaj   +1 more source

Comparison of GAN Deep Learning Methods for Underwater Optical Image Enhancement

한국해양공학회지, 2022
Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast ...
Hong-Gi Kim, Jung-Min Seo, Soo Mee Kim
doaj   +1 more source

Effective solution for underwater image enhancement

Optics 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

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, Xi Yang, ZhenMing Li, Tianlun Zhang   +3 more
openaire   +2 more sources

Underwater Image Enhancement Using a Diffusion Model with Adversarial Learning. [PDF]

J Imaging
Due to the distinctive attributes of underwater environments, underwater images frequently encounter challenges such as low contrast, color distortion, and noise.
Ding X, Chen X, Sui Y, Wang Y, Zhang J.
europepmc   +2 more sources

Unveiling the hidden depths: advancements in underwater image enhancement using deep learning and auto-encoders. [PDF]

PeerJ Comput Sci
Underwater images hold immense value for various fields, including marine biology research, underwater infrastructure inspection, and exploration activities. However, capturing high-quality images underwater proves challenging due to light absorption and
Bantupalli J, Kachapilly AJ, Roy S, L K P.   +3 more
europepmc   +3 more sources

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
openaire   +2 more sources

Underwater image enhancement with latent consistency learning‐based color transfer

IET Image Processing, 2022
Due to the inevitable wavelength‐dependent light absorption and forward/backward scattering, underwater images usually suffer severe color distortion and are hazy.
Hua Yang, Fei Tian, Qi Qi, Q. M. Jonathan Wu, Kunqian Li   +4 more
doaj   +1 more source

UMGAN: Underwater Image Enhancement Network for Unpaired Image-to-Image Translation

Journal of Marine Science and Engineering, 2023
Due to light absorption and scattering underwater images suffer from low contrast, color distortion, blurred details, and uneven illumination, which affect underwater vision tasks and research.
Boyang Sun, Yupeng Mei, Ni Yan, Yingyi Chen   +3 more
doaj   +1 more source