Tutorial OTB/Monteverdi Part 2

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1 orfeo-toolbox.org Use cases with the Orfeo Toolbox framework Monteverdi Use cases with the Orfeo Toolbox framework Monteverdi

description

Tutorial on the OTB/Monteverdi application - part 2

Transcript of Tutorial OTB/Monteverdi Part 2

Page 1: Tutorial OTB/Monteverdi Part 2

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Use cases with the Orfeo Toolbox framework Monteverdi

Use cases with the Orfeo Toolbox framework Monteverdi

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Menu File > Open

./theme2/IM2/Extraits/Im2_p_extrait.tif

Menu File > Open

./theme2/IM2/Extraits/Im2_c_extrait.tif

Menu Geometry > Homologous points extraction

Fix image : PAN

Moving image : XS

Select homologous points in the bottom windows

➢Add / Evaluate / Guess

=> Output : XS image at the same size and resolution than the panchromatic one. Images fusion is now possible.

Use case 12 : Superimpose two images with homologous points

Use case 12 : Superimpose two images with homologous points

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Menu Geometry > Homologous points extraction

Monteverdi – Homologous points extractionMonteverdi – Homologous points extraction

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Filtering

Pan-sharpen an image

➢Requires Panchromatic and Multispectral input images at the same

resolution

Menu Filtering > Pan-sharpen an image

➢Enter PAN and XS image well registeredOrtho-images of PAN + ortho-image of XS

Ortho-image PAN + superimpose of XSXS resampled on PAN image with Homologous points

Use Case 13 : pan-sharpen a multispectral image (image fusion)

Use Case 13 : pan-sharpen a multispectral image (image fusion)

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Filtering

Menu Filtering > Pan-sharpen an image

Pan-sharpen an image (image fusion)Pan-sharpen an image (image fusion)

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Menu Filtering > Band math

Addition, Substraction, Multiplication, Ratio, Shift-Scale (A*X+B)

Use case 14 : compare results, perform simple math computation

Use case 14 : compare results, perform simple math computation

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Menu Geometry > GCP to sensor model

Monteverdi – GCP to sensor modelMonteverdi – GCP to sensor model

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Menu Geometry > Reproject image

Reproject the image (existence of geometric model) into another

ground reference (UTM, LAMBERT, TRANSMERCATOR)

Monteverdi – Reproject imageMonteverdi – Reproject image

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Menu File > Open

./data_otb/SpotBefore.png

Menu File > Open

./data_otb/SpotAfter.png

Menu Filtering > Change detection

Select changed ROI polygons

Select unchanged ROI polygons

Learn

Display results

Use case 15 : Change detection – application to floodingsUse case 15 : Change detection – application to floodings

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Filtering

Change

Detection

MonteverdiMonteverdi

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Menu File > Open

./data_otb/GommaAvant.png

Menu File > Open

./data_otb/GommaApres.png

Menu Filtering > Change detection

Select changed ROI polygons

Select unchanged ROI polygons

Learn

Display results

Use case 15.1 : Change detection – application with radarUse case 15.1 : Change detection – application with radar

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Menu SAR

Despeckle image : apply Frost / Lee filter

Compute intensity and log-intensity

MonteverdiMonteverdi

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Menu SAR > Despeckle image

MonteverdiMonteverdi

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Menu SAR > Compute intensity and log-intensity

MonteverdiMonteverdi

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Menu File > Open

./data_otb/GommaAvant.png

Menu File > Open

./data_otb/GommaApres.png

Menu SAR > Despeckle image (GommaAvant)

Lee Filter

Radius : 10

Menu SAR > Despeckle image (GommaApres)

Lee Filter

Radius : 10

Menu Filtering > Change detection

Select changed ROI polygons, unchanged ROI polygons

Learn, Display results

Menu Filtering > Band-math (compare the results)

Use case 15.2 : Change detection – application with filtered radar image

Use case 15.2 : Change detection – application with filtered radar image

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Menu File > Open

./data_otb/ERSBefore.png

Menu File > Open

./data_otb/ERSAfter.png

Menu Filtering > Change detection

Select changed ROI polygons

Select unchanged ROI polygons

Learn, Display results

Use case 15.3 : Change detection – application with radar (floodings)

Use case 15.3 : Change detection – application with radar (floodings)

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Menu File > Open

./data_otb/ERSBefore.png

Menu File > Open

./data_otb/ERSAfter.png

Menu SAR > Despeckle image (ERSBefore)

Lee Filter

Radius : 10

Menu SAR > Despeckle image (ERSAfter)

Lee Filter

Radius : 10

Menu Filtering > Change detection

Select changed ROI polygons, unchanged ROI polygons

Learn, Display results

Menu Filtering > Band-math (compare the results)

Use case 15.4 : Change detection – application with radar (floodings)

Use case 15.4 : Change detection – application with radar (floodings)

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Menu File > Open

./data_tp/theme1/IM2/Extraits/Ext_IM2_22031986_20mC.tif

Menu File > Open

./data_tp/theme1/IM2/Extraits/Ext_IM2_04102008_10mC.tif

...

Menu Filtering > Change detection

Select changed ROI polygons, unchanged ROI polygons

Learn, Display results

Use case 16 : Change detection applied to vegetationUse case 16 : Change detection applied to vegetation

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Menu File > Open

./data_tp/theme1/IM2/Extraits/Ext_IM2_22031986_20mC.tif

Menu File > Open

./data_tp/theme1/IM2/Extraits/Ext_IM2_04102008_10mC.tif

Menu Geometry > Homologous points

Resample 20m image on 10m image

Menu Filtering > Change detection

Select changed ROI polygons, unchanged ROI polygons

Learn, Display results

Further work :

Use also Ext_IM2_26032004_10mC.tif and Ext_IM2_17042000_20mC.tif

Compare results with Band-Math

Use case 16 : Change detection applied to vegetationUse case 16 : Change detection applied to vegetation

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Future evolutions

Integration of new OTB modules

Delete pipeline module functionality

Load / Save project functions

Change input images option into the pipeline

+ Future needs of the Monteverdi users !

Monteverdi Monteverdi

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Thank you for your attention !

Monteverdi Monteverdi