alos optical data processing end of stage presentation trainee: arnal etienne [email protected]...
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Alos optical data processingAlos optical data processing
End of Stage Presentation
Trainee: ARNAL Etienne
Tutor: Mr COLIN Olivier
10/04/23ESRIN - ARNAL Etienne 2
Presentation OutlinePresentation Outline
Alos Product Descriptor (PRISM and AVNIR2)
Alos Image Processing (PRISM and AVNIR2)
Digital Elevation Model
3D results
10/04/23ESRIN - ARNAL Etienne 3
Alos Product Descriptor Alos Product Descriptor (1/5)(1/5)
Image DEM
Realisation of a cqfd dictionary containing the fields of the Product Format Description of Prism and Avnir2.
Allows to find quickly all fields of level:1A = raw data extracted from the Level 0,1B1 = with radiometric corrections,1B2R = geo-referenced,1B2G = geo-coded.
3D results
Data
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Alos Product Descriptor Alos Product Descriptor (2/5)(2/5)
CQFD: binary data reader.
VOL
LED
IMG
TRL
SUP
Tie Points
in the data
FILE ; |_ VOL ; | |_ VolumeDescriptor ;| |_ FilePointer ; (3 to 9)| |_TextRecord ;|_ LED ; | |_ CommonFileDescriptor ; | |_ FileDescriptor ; | |_ SceneHeader ; | |_ Ancillary1 ; | |_ Ancillary2 ; | |_ Ancillary3 ;
Data Image DEM3D
results
10/04/23ESRIN - ARNAL Etienne 5
Alos Product Descriptor Alos Product Descriptor (3/5)(3/5)
CQFD: binary data reader.
VOL
LED
IMG
TRL
SUP
Tie Points
in the data
|_ IMG ; | |_ IMG1 ; (1 to 6)| | |_ CommonFileDescriptor ; | | |_ FileDescriptor ; | | |_ Line 1 ;| | |_ …| | |_ Line n ;|_ TRL ;| |_ CommonFileDescriptor ; | |_ FileDescriptor ; | |_ Trailer ;|_ SUP ; | |_ CommonFileDescriptor ; | |_ FileDescriptor ; | |_ Ancillary ;
Data Image DEM3D
results
10/04/23ESRIN - ARNAL Etienne 6
Alos Product Descriptor Alos Product Descriptor (4/5)(4/5)
CQFD: binary data reader.
VOL
LED
IMG
TRL
SUP
Tie Points
in the data
|_ TiePoints ; | |_ Line 1 ;| | |_ Lat ;| | |_ Long ;| |_ …| |_ Line n ;
39
38
27
26
25
243210
39
38
27
26
25
243210
),(),(
JIIJJIJIIJJI
JIIJJIJIIJJI
JIf
(I,J) are pixel and line of corrected image
(φ,λ) are degrees of latitude and longitude
Data Image DEM3D
results
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Alos Product Descriptor Alos Product Descriptor (5/5)(5/5)
Thanks to this CQFD dictionary, everybody can find a precise field in every Prism and Avnir2 data.
The next step is to create image.
Data Image DEM3D
results
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Alos Image Processing Alos Image Processing (1/5)(1/5)
3 various image data structure:
Several CCD (Prism 1A, 1B1) From 3 to 6 CCD CCD = ~4992 pixels * 16000 lines Overlap = 32 pixels
One CCD (Prism 1B2R, 1B2G) CCD = ~15000 pixels * 14000 lines
4 Spectral Bands (Avnir2) Band = ~7150 pixels * 8000 lines
Data DEM3D
resultsImage
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Alos Image Processing Alos Image Processing (2/5)(2/5)
Imager: data reader for image generationFor each pixel:
– elaborates from the band values (0 to 255) applying sun angle correction and stretching to enhance image contrast,
– extracts Tie Point (λ,φ) grid.It creates:
one image file (including all CCD/Bands), one GeoTiff file (geolocalisation).
Data Image DEM3D
results
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Prism Nadir 1B2R
Data Image DEM3D
results
Shizuoka, Japan on February 14, 2006Shizuoka, Japan on February 14, 2006
Alos Image Processing Alos Image Processing (3/5)(3/5)
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Alos Image Processing Alos Image Processing (4/5)(4/5)
Avnir2
Data Image DEM3D
results
Tanegashima Is., Japan on February 17, 2006Tanegashima Is., Japan on February 17, 2006
10/04/23ESRIN - ARNAL Etienne 12
Alos Image Processing Alos Image Processing (5/5)(5/5)
encountered problems
Avnir2, ±5 pixels between each columns. Prism and Avnir2, geolocalisation error. Prism, many artifacts. Prism and Avnir 1B2(R/G), nothing about time in the data.
Data Image DEM3D
results
Nadir Forward
10/04/23ESRIN - ARNAL Etienne 13
Digital Elevation Model Digital Elevation Model (1/10)(1/10)
Stereoscopy 3D, imager process.
For each pixel [I,J],
Find the value of pixel Nadir [I,J] and [λ,φ]=fN(I,J)
Find the value of pixel Backward fB-1[λ,φ]
Find the value of pixel Forward fF-1[λ,φ]
Output: one RGB image with R=Nadir, G=Forward and B=Backward.
Data Image3D
resultsDEM
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Digital Elevation Model Digital Elevation Model (2/10)(2/10)
DEM, bases Height is proportional to the along track displacement.
Data Image DEM3D
resultsN
adir
For
war
dS
atellite track
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Digital Elevation Model Digital Elevation Model (3/10)(3/10)
DEM, base equation
∆ is a multiple of the ground resolution
Data Image DEM3D
results
tan
h
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Digital Elevation Model Digital Elevation Model (4/10)(4/10)
DEM Algorithm. Image adjustments
Data Image DEM3D
results
Forward Nadir Backward
Mean = 35
STD = 3.4398
Mean = 43
STD = 2.4389
Mean = 57
STD = 2.5302
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Digital Elevation Model Digital Elevation Model (5/10)(5/10)
DEM Algorithm. Image adjustments, Generate pyramid image,
Data Image DEM3D
results
with gradually degraded resolution.
Pass the matched points to the higher resolution level for fine matching.
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Digital Elevation Model Digital Elevation Model (6/10)(6/10)
DEM Algorithm. Image rectification, Generate pyramid image, Feature matching,
Data Image DEM3D
results
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Digital Elevation Model Digital Elevation Model (7/10)(7/10)
DEM Algorithm. Image rectification, Generate pyramid image, Feature matching, Matching results,
Data Image DEM3D
results
1/16
1/8
1/4
1/21/1
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Digital Elevation Model Digital Elevation Model (8/10)(8/10)
DEM Algorithm. Image rectification, Generate pyramid image, Feature matching, Matching results, Filtering.
Data Image DEM3D
results
Median filter, reduce noise (peaks):
Mean filter, reduce high frequencies:
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Digital Elevation Model Digital Elevation Model (9/10)(9/10)
Integration in eogrid.esrin.esa.int.
Modification for Linux (no graphics), Installation of Matlab Component Runtime, Compilation of Matlab code (Stand-alone application). Integrated new “DEM” application in G-POD in < 1 day
Data Image DEM3D
results
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Digital Elevation Model Digital Elevation Model (10/10)(10/10)
encountered problems
Co-registration is corrected manually due to ALOS processors geo-referencing problem
Result of matching requires validation of the correlation distribution not trivial
Correlation is impaired by high height gradients in image (e.g. buildings) possible solution to weight the matching window with distance to centre
Patterns oriented along-track have low correlation contrast Moving objects (cars, boats, troy horses, etc) Sun glint creates big differences between views Image radiometric quality (e.g. striping, spurious saturation artifacts) Image boundaries
Data Image DEM3D
results
10/04/23ESRIN - ARNAL Etienne 24
3D results3D results Japan, Shizuoka and surroundings , 02/14/2006. AATSR Hurricane Jeanne, 20/09/2004
Stereoscopic views. Digital Elevation models.
Data Image DEM3D
results
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Potential Enhancements Potential Enhancements Investigate alternative matching methods for high
gradient terrains (e.g. parallax, urban areas) Make adaptive algorithm e.g. apply dynamically different
techniques/parameters depending on correlation contrast observed
Integrate automatic co-registration of the 3 views with a good geo-referencing.
Add possibility to correlate several bands in parallel (e.g. AATSR dual views with 4 channels)
Include DEM geo-coding in last stage Optimize algorithm for performance in multi-processing
environment (e.g. tiling) Calibration & Validation !
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ThanksThanks Olivier Colin, Jerome Louis, Philippe Goryl, Peter Reinartz (DLR), Nityaporn Sirikan, Patrick Grimont, Emmanuel Mathot.
Questions ?
Data Image DEM3D
results