Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 29th Asian Conference on Remote Sensing 2008, ACRS 2008 |
| Seiten | 1313-1319 |
| Seitenumfang | 7 |
| Publikationsstatus | Veröffentlicht - 2008 |
| Veranstaltung | 29th Asian Conference on Remote Sensing 2008, ACRS 2008 - Colombo, Sri Lanka Dauer: 10 Nov. 2008 → 14 Nov. 2008 |
Publikationsreihe
| Name | 29th Asian Conference on Remote Sensing 2008, ACRS 2008 |
|---|---|
| Band | 2 |
Abstract
Imagery from the ALOS PRISM and AVNIR-2 sensors offers the potential of georeferencing and orthoimage generation to support medium- and small-scale mapping. In order to optimize the economy and productivity of these operations, image strips of maximum possible length need to be employed with a minimum of ground control, without suffering a loss in attainable accuracy. This paper describes the development of a computational system that enables realisation of this goal. The data processing flow commences with an image merging stage that results in a single scene for AVNIR and three single scenes for PRISM. In the case of PRISM, Level 1B1 sub-images are merged, and for AVNIR individual image bands are merged. Along with the merging of imagery, all sensor orientation data is rigorously transformed and referenced to a single orbit, with one set of orbit path and attitude parameters. A strip adjustment is then carried out to refine the sensor orientation. This employs four or more ground control points at the two end regions of the strip. The refined sensor orientation modelling accounts for biases within the orbit and attitude data, resulting in 1-pixel and even sub-pixel level georeferencing accuracy for all scenes of the strip. This paper overviews the computational models and steps involved, for both PRISM and AVNIR-2 imagery, and describes how the workflow has been accomplished within the Barista software system. Practical experimental test results are presented, in which it is demonstrated that 1-pixel georeferencing accuracy and better is achievable for PRISM imagery with as few as four ground control points over strip lengths of 700km. Such a control requirement is well below that generally needed for orthoimage generation approaches that neither employ rigorous sensor orientation modelling for ALOS imagery nor have the capability to merge along-track scenes into long continuous strips.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Computernetzwerke und -kommunikation
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29th Asian Conference on Remote Sensing 2008, ACRS 2008. 2008. S. 1313-1319 (29th Asian Conference on Remote Sensing 2008, ACRS 2008; Band 2).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Image merging to support georeferencing and orthoimage generation from ALOS imagery
AU - Fraser, C. S.
AU - Weser, T.
AU - Rottensteiner, F.
PY - 2008
Y1 - 2008
N2 - Imagery from the ALOS PRISM and AVNIR-2 sensors offers the potential of georeferencing and orthoimage generation to support medium- and small-scale mapping. In order to optimize the economy and productivity of these operations, image strips of maximum possible length need to be employed with a minimum of ground control, without suffering a loss in attainable accuracy. This paper describes the development of a computational system that enables realisation of this goal. The data processing flow commences with an image merging stage that results in a single scene for AVNIR and three single scenes for PRISM. In the case of PRISM, Level 1B1 sub-images are merged, and for AVNIR individual image bands are merged. Along with the merging of imagery, all sensor orientation data is rigorously transformed and referenced to a single orbit, with one set of orbit path and attitude parameters. A strip adjustment is then carried out to refine the sensor orientation. This employs four or more ground control points at the two end regions of the strip. The refined sensor orientation modelling accounts for biases within the orbit and attitude data, resulting in 1-pixel and even sub-pixel level georeferencing accuracy for all scenes of the strip. This paper overviews the computational models and steps involved, for both PRISM and AVNIR-2 imagery, and describes how the workflow has been accomplished within the Barista software system. Practical experimental test results are presented, in which it is demonstrated that 1-pixel georeferencing accuracy and better is achievable for PRISM imagery with as few as four ground control points over strip lengths of 700km. Such a control requirement is well below that generally needed for orthoimage generation approaches that neither employ rigorous sensor orientation modelling for ALOS imagery nor have the capability to merge along-track scenes into long continuous strips.
AB - Imagery from the ALOS PRISM and AVNIR-2 sensors offers the potential of georeferencing and orthoimage generation to support medium- and small-scale mapping. In order to optimize the economy and productivity of these operations, image strips of maximum possible length need to be employed with a minimum of ground control, without suffering a loss in attainable accuracy. This paper describes the development of a computational system that enables realisation of this goal. The data processing flow commences with an image merging stage that results in a single scene for AVNIR and three single scenes for PRISM. In the case of PRISM, Level 1B1 sub-images are merged, and for AVNIR individual image bands are merged. Along with the merging of imagery, all sensor orientation data is rigorously transformed and referenced to a single orbit, with one set of orbit path and attitude parameters. A strip adjustment is then carried out to refine the sensor orientation. This employs four or more ground control points at the two end regions of the strip. The refined sensor orientation modelling accounts for biases within the orbit and attitude data, resulting in 1-pixel and even sub-pixel level georeferencing accuracy for all scenes of the strip. This paper overviews the computational models and steps involved, for both PRISM and AVNIR-2 imagery, and describes how the workflow has been accomplished within the Barista software system. Practical experimental test results are presented, in which it is demonstrated that 1-pixel georeferencing accuracy and better is achievable for PRISM imagery with as few as four ground control points over strip lengths of 700km. Such a control requirement is well below that generally needed for orthoimage generation approaches that neither employ rigorous sensor orientation modelling for ALOS imagery nor have the capability to merge along-track scenes into long continuous strips.
KW - ALOS
KW - AVNIR-2
KW - Orthoimages
KW - PRISM
KW - Sensor orientation
KW - Strip adjustment
UR - http://www.scopus.com/inward/record.url?scp=84865692912&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84865692912
SN - 9781615676156
T3 - 29th Asian Conference on Remote Sensing 2008, ACRS 2008
SP - 1313
EP - 1319
BT - 29th Asian Conference on Remote Sensing 2008, ACRS 2008
T2 - 29th Asian Conference on Remote Sensing 2008, ACRS 2008
Y2 - 10 November 2008 through 14 November 2008
ER -