# Underwater Image Enhancement Using Convolutional Neural Network

arXiv: https://arxiv.org/abs/2109.08916 · HTML: https://mlsanity.com/paper/2109.08916/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 17 references that are in the map.
- First posted on arXiv 18 Sep 2021.

## Abstract (arXiv)

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.