Underwater Image Enhancement Using Convolutional Neural Network

• URL: http://arxiv.org/abs/2109.08916v1
• Date: Sat, 18 Sep 2021 12:01:14 GMT
• Title: Underwater Image Enhancement Using Convolutional Neural Network
• Authors: Anushka Yadav, Mayank Upadhyay, Ghanapriya Singh
• Abstract summary: 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.
• Score: 1.1602089225841632
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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