  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.
