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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 13 | Issue 11 | Month- November 2025
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Published Paper Details:
Paper Title
Underwater Image Enhancement Using Deep Learning
Authors
Bhavana G, Bhavana Arun Kabbur, Dr. Bama S
Keywords
Image Enhancement, Convolutional Neural Networks, Underwater image processing, Deep Neural Network, Machine Learning.
Abstract
Underwater imaging often faces challenges such as
reduced visibility, poor contrast, and color distortions due to
light absorption and scattering in water. This project presents a
novel approach to underwater image enhancement using a UNet convolutional neural network. The model was trained on a
publicly available dataset of underwater images and their
enhanced versions. Through its encoder-decoder structure, the
U-Net model effectively improves clarity, contrast, and color
fidelity.
The solution includes preprocessing data, building and training
the model, and developing a web application for user interaction.
The application, with a Flask backend and a user-friendly
frontend, allows users to upload underwater images and view
enhanced outputs. By combining deep learning with
accessibility, this project offers a practical tool for improving
underwater image quality, catering to diverse audiences and
applications.
IJCRT's Publication Details
Unique Identification Number - IJCRT2504456
Paper ID - 273830
Page Number(s) - d913-d918
Pubished in - Volume 13 | Issue 4 | April 2025
DOI (Digital Object Identifier) -
Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Bhavana G, Bhavana Arun Kabbur, Dr. Bama S, "Underwater Image Enhancement Using Deep Learning", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 4, pp.d913-d918, April 2025, Available at :http://www.ijcrt.org/papers/IJCRT2504456.pdf
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Volume 13 | Issue 11
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Volume 13 | Issue 11
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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