Automated correction of surface obstruction errors in digital surface models using off-the-shelf image processing

Détails

ID Serval
serval:BIB_07748451CEAA
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Automated correction of surface obstruction errors in digital surface models using off-the-shelf image processing
Périodique
PHOTOGRAMMETRIC RECORD
Auteur⸱e⸱s
James Timothy D., Barr Stuart L., Lane Stuart N.
ISSN
0031-868X
Statut éditorial
Publié
Date de publication
12/2006
Volume
21
Numéro
116
Pages
373-397
Notes
ISI:000242864500006
Résumé
Airborne topographic data collection requires removal of errors that
arise due to surface features that obstruct the ground from the sensor.
Typically, this has been based on manual correction and/or automated
filtering. To some degree, the latter has provided a method for
identifying and removing unwanted surface obstructions in large
topographic data-sets. However, the algorithms used are unintelligent
in that they cannot reliably differentiate between the various types of
obstructions and the ground. If coincident optical support imagery is
available, the use of intelligent correction routines becomes possible.
This paper describes an automated approach for removing obstruction
errors using optical support imagery and simple image processing
routines. Orthorectification and classification of support imagery
enable obstruction errors to be identified in the digital surface model
(DSM) and corrected intelligently to produce a digital terrain model
(DTM). The results show that support imagery can be used with basic
image processing routines to remove obstructions intelligently and
automatically from large topographic data-sets. Since the approach can
differentiate between types of obstructions, the removal of each type
of error can be customised, making this a very flexible approach to
topographic data correction.
Web of science
Création de la notice
03/02/2011 14:41
Dernière modification de la notice
20/08/2019 12:29
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