Alos optical data processingAlos optical data processing

End of Stage Presentation

Trainee: ARNAL Etienne

etienne.arnal@isen.fr

Tutor: Mr COLIN Olivier

olivier.colin@esa.int

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

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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

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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

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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

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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

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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