Underwater Image Enhancement Using Particle Swarm Optimization

Abstract

This article introduces a framework for enhancing underwater images using the particle swarm optimization algorithm. A pre-processing step is introduced to reduce the absorbing and scattering effects of water before applying a filter based on this algorithm to enhance the image. The quality of enhanced images is quantitatively assessed by applying the framework on a dataset of underwater images. The obtained results show a considerable improvement.

Keywords

• underwater images
• particle swarm optimization
• underwater image enhancement
• kullback–leibler divergence
• histogram
• peak signal-to-noise ratio
• number of edges