Towards establishing an automated selection framework for underwater image enhancement methods

Conference paper (2023)

Authors

A. Ilioudi Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
B.J. Wolf University Medical Center Groningen
A. Dabiri Team Azita Dabiri - Mechanical, Maritime and Materials Engineering
B.H.K. De Schutter Delft Center for Systems and Control
Research Group
Team Bart De Schutter (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2023 A. Ilioudi, B.J. Wolf, A. Dabiri, B.H.K. De Schutter
DOI
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https://doi.org/10.1109/OCEANSLimerick52467.2023.10244710
Computer vision Image processing Underwater image enhancement
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Published Date

2023

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Bart De Schutter

Abstract

The majority of computer vision architectures are developed based on the assumption of the availability of good quality data. However, this is a particularly hard requirement to achieve in underwater conditions. To address this limitation, plenty of underwater image enhancement methods have received considerable attention during the last decades, but due to the lack of a commonly accepted framework to systematically evaluate them and to determine the likely optimal one for a given image, their adoption in practice is hindered, since it is not clear which one can achieve the best results. In this paper, we propose a standardized selection framework to evaluate the quality of an underwater image and to estimate the most suitable image enhancement technique based on its impact on the image classification performance.