Underwater Image Enhancement Using Convolutional Neural Network

09/18/2021
by   Anushka Yadav, et al.
0

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.

READ FULL TEXT
research
07/10/2018

Deep Underwater Image Enhancement

In an underwater scene, wavelength-dependent light absorption and scatte...
research
01/11/2019

An Underwater Image Enhancement Benchmark Dataset and Beyond

Underwater image enhancement has been attracting much attention due to i...
research
08/14/2022

Underwater Ranker: Learn Which Is Better and How to Be Better

In this paper, we present a ranking-based underwater image quality asses...
research
03/13/2018

Robust Contrast Enhancement Forensics Using Convolutional Neural Networks

Contrast enhancement(CE) forensics has always been attracted widely atte...
research
12/03/2012

An Image Based Technique for Enhancement of Underwater Images

The underwater images usually suffers from non-uniform lighting, low con...
research
11/08/2014

Parallax Effect Free Mosaicing of Underwater Video Sequence Based on Texture Features

In this paper, we present feature-based technique for construction of mo...
research
06/29/2018

Mammographic Image Enhancement using Digital Image Processing Technique

Abstract PURPOSES this study aims to perform microcalsification detectio...

Please sign up or login with your details

Forgot password? Click here to reset