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Automatic geometric processing for very high resolution optical satellite data based on vector roads and orthophotos
ID
Pehani, Peter
(
Author
),
ID
Čotar, Klemen
(
Author
),
ID
Marsetič, Aleš
(
Author
),
ID
Zaletelj, Janez
(
Author
),
ID
Oštir, Krištof
(
Author
)
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MD5: 705E9DF5B92B717976C82BD9B04E5C32
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http://www.mdpi.com/2072-4292/8/4/343
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Abstract
In response to the increasing need for fast satellite image processing SPACE-SI developed STORM—a fully automatic image processing chain that performs all processing steps from the input optical images to web-delivered map-ready products for various sensors. This paper focuses on the automatic geometric corrections module and its adaptation to very high resolution (VHR) multispectral images. In the automatic ground control points (GCPs) extraction sub-module a two-step algorithm that utilizes vector roads as a reference layer and delivers GCPs for high resolution RapidEye images with near pixel accuracy was initially implemented. Super-fine positioning of individual GCPs onto an aerial orthophoto was introduced for VHR images. The enhanced algorithm is capable of achieving accuracy of approximately 1.5 pixels on WorldView-2 data. In the case of RapidEye images the accuracies of the physical sensor model reach sub-pixel values at independent check points. When compared to the reference national aerial orthophoto the accuracies of WorldView-2 orthoimages automatically produced with the rational function model reach near-pixel values. On a heterogeneous set of 41 RapidEye images the rate of automatic processing reached 97.6%. Image processing times remained under one hour for standard-size images of both sensor types.
Language:
English
Keywords:
automatic geometric processing
,
high resolution data
,
satellites
,
remote sensing
,
automatic image processing
,
geometric corrections
,
extraction of ground control points
,
physical sensor model
,
rational function model
,
earth observation
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FE - Faculty of Electrical Engineering
FGG - Faculty of Civil and Geodetic Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2016
Number of pages:
26 str.
Numbering:
Vol. 8, iss. 4, art. 343
PID:
20.500.12556/RUL-130347
UDC:
528:55
ISSN on article:
2072-4292
DOI:
10.3390/rs8040343
COBISS.SI-ID:
39753261
Publication date in RUL:
14.09.2021
Views:
856
Downloads:
185
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Record is a part of a journal
Title:
Remote sensing
Shortened title:
Remote sens.
Publisher:
MDPI
ISSN:
2072-4292
COBISS.SI-ID:
32345133
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:
19.04.2016
Secondary language
Language:
Slovenian
Keywords:
avtomatsko geometrijsko procesiranje
,
visoko resolucijski podatki
,
sateliti
,
daljinsko zaznavanje
Projects
Funder:
EC - European Commission
Funding programme:
European Regional Development Fund
Funder:
Other - Other funder or multiple funders
Funding programme:
Ministry of Education, Science and Sport of the Republic of Slovenia
Funder:
ARRS - Slovenian Research Agency
Project number:
J2-6777
Name:
Samodejna objektno usmerjena klasifikacija pokrovnosti podatkov optičnega daljinskega zaznavanja
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