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Guidelines for underwater image enhancement based on benchmarking of different methods

File(s)
Journal
Remote Sensing
Date Issued
October 1, 2018
Author(s)
Mangeruga, Marino  
Bruno, Fabio  
Cozza, Marco  
Agrafiotis, Panagiotis  
Skarlatos, Dimitrios  
DOI
10.3390/rs10101652
Abstract
Images obtained in an underwater environment are often affected by colour casting and suffer from poor visibility and lack of contrast. In the literature, there are many enhancement algorithms that improve different aspects of the underwater imagery. Each paper, when presenting a new algorithm or method, usually compares the proposed technique with some alternatives present in the current state of the art. There are no studies on the reliability of benchmarking methods, as the comparisons are based on various subjective and objective metrics. This paper would pave the way towards the definition of an effective methodology for the performance evaluation of the underwater image enhancement techniques. Moreover, this work could orientate the underwater community towards choosing which method can lead to the best results for a given task in different underwater conditions. In particular, we selected five well-known methods from the state of the art and used them to enhance a dataset of images produced in various underwater sites with different conditions of depth, turbidity, and lighting. These enhanced images were evaluated by means of three different approaches: objective metrics often adopted in the related literature, a panel of experts in the underwater field, and an evaluation based on the results of 3D reconstructions.
Funding(s)
Advanced VR, iMmersive serious games and Augmented REality as tools to raise awareness and access to European underwater CULTURal heritage  
Subjects

3D reconstruction

Automatic colour equa...

Benchmark

CLAHE

Colour correction

Dehazing

Lab

Non-local dehazing

Screened poisson equa...

Underwater image enha...

File(s)
Thumbnail Image
Name

remotesensing-10-01652.pdf

Size

5.8 MB

Format

Adobe PDF

Checksum (MD5)

041122d7eea9ff404fcef8dc439b8ae8

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