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Improvement of EPIC/DSCOVR Image Registration by Means of Automatic Coastline Detection

Molina García, Víctor and Sasi, Sruthy and Efremenko, Dmitry S. and Loyola, Diego (2019) Improvement of EPIC/DSCOVR Image Registration by Means of Automatic Coastline Detection. Remote Sensing, 11 (15), pp. 1-16. Multidisciplinary Digital Publishing Institute (MDPI). DOI: 10.3390/rs11151747 ISSN 2072-4292

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Official URL: https://www.mdpi.com/2072-4292/11/15/1747

Abstract

In this work, we address the image geolocation issue that is present in the imagery of EPIC/DSCOVR (Earth Polychromatic Imaging Camera/Deep Space Climate Observatory) Level 1B version 2. To solve it, we develop an algorithm that automatically computes a registration correction consisting of a motion (translation plus rotation) and a radial distortion. The correction parameters are retrieved for every image by means of a regularised non-linear optimisation process, in which the spatial distances between the theoretical and actual locations of chosen features are minimised. The actual features are found along the coastlines automatically by using computer vision techniques. The retrieved correction parameters show a behaviour that is related to the period of DSCOVR orbiting around the Lagrangian point L1. With this procedure, the EPIC coastlines are collocated with an accuracy of about 1.5 pixels, thus significantly improving the original registration of about 5 pixels from the imagery of EPIC/DSCOVR Level 1B version 2.

Item URL in elib:https://elib.dlr.de/128748/
Document Type:Article
Title:Improvement of EPIC/DSCOVR Image Registration by Means of Automatic Coastline Detection
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Molina García, VíctorVictor.MolinaGarcia (at) dlr.dehttps://orcid.org/0000-0002-2564-5396
Sasi, SruthySruthy.Sasi (at) dlr.dehttps://orcid.org/0000-0002-5477-9879
Efremenko, Dmitry S.Dmitry.Efremenko (at) dlr.dehttps://orcid.org/0000-0002-7449-5072
Loyola, DiegoDiego.Loyola (at) dlr.dehttps://orcid.org/0000-0002-8547-9350
Date:25 July 2019
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:11
DOI :10.3390/rs11151747
Page Range:pp. 1-16
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
ISSN:2072-4292
Status:Published
Keywords:EPIC; registration; geolocation; computer vision; regularisation
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Atmosphären- und Klimaforschung
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Atmospheric Processors
Deposited By: Molina García, Víctor
Deposited On:13 Aug 2019 10:39
Last Modified:14 Dec 2019 04:27

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