Please use this identifier to cite or link to this item:
Title: Correcting Image Refraction: Towards Accurate Aerial Image-Based Bathymetry Mapping in Shallow Waters
Authors: Agrafiotis, Panagiotis 
Karantzalos, K. 
Georgopoulos, Andreas 
Skarlatos, Dimitrios 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Bathymetry;UAV;Aerial imagery;Seabed mapping;Coastal mapping;DSM;Refraction correction;SfM;Machine learning;Image correction
Issue Date: Jan-2020
Source: Remote Sensing, 2020, vol. 12, no. 2
Volume: 12
Issue: 2
Journal: Remote Sensing 
Abstract: Although aerial image-based bathymetric mapping can provide, unlike acoustic or LiDAR (Light Detection and Ranging) sensors, both water depth and visual information, water refraction poses significant challenges for accurate depth estimation. In order to tackle this challenge, we propose an image correction methodology, which first exploits recent machine learning procedures that recover depth from image-based dense point clouds and then corrects refraction on the original imaging dataset. This way, the structure from motion (SfM) and multi-view stereo (MVS) processing pipelines are executed on a refraction-free set of aerial datasets, resulting in highly accurate bathymetric maps. Performed experiments and validation were based on datasets acquired during optimal sea state conditions and derived from four different test-sites characterized by excellent sea bottom visibility and textured seabed. Results demonstrated the high potential of our approach, both in terms of bathymetric accuracy, as well as texture and orthoimage quality.
Description: The article was funded by the “CUT Open Access Author Fund”
ISSN: 2072-4292
DOI: 10.3390/rs12020322
Rights: © by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license
Type: Article
Affiliation : Cyprus University of Technology 
National Technical University of Athens 
Appears in Collections:Άρθρα/Articles

Files in This Item:
File Description SizeFormat
remotesensing.pdf19.52 MBAdobe PDFView/Open
CORE Recommender
Show full item record

Citations 20

checked on Mar 29, 2021


Last Week
Last month
checked on Apr 22, 2021

Page view(s)

Last Week
Last month
checked on May 10, 2021

Download(s) 50

checked on May 10, 2021

Google ScholarTM



This item is licensed under a Creative Commons License Creative Commons