Underwater Image Enhancement Using Convolutional Neural Network

This work proposes a method for underwater image enhancement using the principle of histogram equalization. Since underwater images have a global strong dominant colour, their colourfulness and contrast are often degraded. Before applying the histogram equalisation technique on the image, the image...

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Bibliographic Details
Published in:arXiv.org 2021-09
Main Authors: Yadav, Anushka, Upadhyay, Mayank, Singh, Ghanapriya
Format: Article
Language:English
Subjects:
Artificial neural networks
Equalization
Histograms
Image contrast
Image enhancement
Neural networks
Underwater
Online Access:Get full text
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Summary:This work proposes a method for underwater image enhancement using the principle of histogram equalization. Since underwater images have a global strong dominant colour, their colourfulness and contrast are often degraded. Before applying the histogram equalisation technique on the image, the image is converted from coloured image to a gray scale image for further operations. Histogram equalization is a technique for adjusting image intensities to enhance contrast. The colours of the image are retained using a convolutional neural network model which is trained by the datasets of underwater images to give better results.
ISSN:2331-8422