A dataset to evaluate underwater image restoration methods
Amanda Duarte, Felipe Codevilla, Joel De O. Gaya, Sílvia Silva da Costa Botelho · OCEANS 2016 - Shanghai · 2016
Image restoration methods have been made to repair images that have some kind of degradation. Most of these methods are designed to deal with the degradation caused by the over-land effects. However, when the images was captured in underwater environments, there are different properties that can degrade the image in unusual ways. This work aims to evaluate how the popular image restoration methods behaves when applied in underwater images with the presence of turbidity in the water. For this, we propose a dataset where we are able to control the amount of image degradation due to underwater properties on a scenario with 3D objects that represents the seabed characteristics. After that, we evaluate the restoration of these methods and their behavior through the image degradation due to turbidity.