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J. Mar. Sci. Eng. 2018, 6(1), 10; https://doi.org/10.3390/jmse6010010

Evaluation of Underwater Image Enhancement Algorithms under Different Environmental Conditions

1
3D Research s.r.l.—University of Calabria, Rende, 87036 Cosenza, Italy
2
3D Research s.r.l., Rende, 87036 Cosenza, Italy
*
Author to whom correspondence should be addressed.
Received: 4 December 2017 / Revised: 4 January 2018 / Accepted: 6 January 2018 / Published: 16 January 2018
(This article belongs to the Special Issue Maritime Environment Monitoring)
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Abstract

Underwater images usually suffer from poor visibility, lack of contrast and colour casting, mainly due to light absorption and scattering. In literature, there are many algorithms aimed to enhance the quality of underwater images through different approaches. Our purpose was to identify an algorithm that performs well in different environmental conditions. We have selected some algorithms from the state of the art and we have employed them to enhance a dataset of images produced in various underwater sites, representing different environmental and illumination conditions. These enhanced images have been evaluated through some quantitative metrics. By analysing the results of these metrics, we tried to understand which of the selected algorithms performed better than the others. Another purpose of our research was to establish if a quantitative metric was enough to judge the behaviour of an underwater image enhancement algorithm. We aim to demonstrate that, even if the metrics can provide an indicative estimation of image quality, they could lead to inconsistent or erroneous evaluations. View Full-Text
Keywords: underwater image enhancement; dehazing; colour correction; automatic colour equalization; Contrast Limited Adaptive Histogram Equalization (CLAHE); lαβ colour space; non-local dehazing; screened poisson equation underwater image enhancement; dehazing; colour correction; automatic colour equalization; Contrast Limited Adaptive Histogram Equalization (CLAHE); lαβ colour space; non-local dehazing; screened poisson equation
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Mangeruga, M.; Cozza, M.; Bruno, F. Evaluation of Underwater Image Enhancement Algorithms under Different Environmental Conditions. J. Mar. Sci. Eng. 2018, 6, 10.

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