tutorial otb/monteverdi part 1
Post on 21-Jun-2015
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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/Im2_C_02112006_169_388/372596101/SPVIEW01
/IMAGERY.TIF
Menu Visualization > Viewer
(Alternative – right click on the module in the pipeline)
Discover the viewer functionalities
Use case 1 : open an image, and discover the viewer Use case 1 : open an image, and discover the viewer
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Visualization
Viewer (1/4)
Monteverdi – ViewerMonteverdi – Viewer
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Visualization
Viewer (2/4)
Monteverdi - ViewerMonteverdi - Viewer
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Visualization
Viewer (3/4)
Monteverdi - ViewerMonteverdi - Viewer
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Visualization
Viewer (4/4)
Monteverdi - ViewerMonteverdi - Viewer
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Menu File > Open
./theme2/IM2/Im2_C_02112006_169_388/372596101/SPVIEW01/
IMAGERY.TIF
Menu Visualization > Viewer (lock the pipeline !)
File > Extract ROI from dataset
Positions (x,y) = [1600,1000], sizeX=2000 (w), sizeY=1500 (h)
File > Save dataset
File > Save dataset (advanced)
Save only Channel 1 in Float type
Seel also :
Right click on pipeline module ExtractROI > Show module
Cache dataset
Use case 2 : create a pipeline, save an image Use case 2 : create a pipeline, save an image
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File > Extract ROI
Monteverdi - ROIMonteverdi - ROI
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File > Save dataset (advanced)
Choice of data type
Choice of output channels
Monteverdi – Save datasetMonteverdi – Save dataset
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Menu File > Open
./theme2/IM2/extraitIm2_C/Im2_c_extrait.tif
Menu Filtering > Threshold
Generic Threshold / Threshold Above / Change Lower threshold
Generic Threshold / Threshold Below / Change Upper Threshold
➢Role of outside value
➢Role of alpha (alpha blending) : alpha=0
Generic Threshold / Threshold outside / Change upper & lower th.
Binary threshold / Lower & Upper threshold / Outside & Inside
values
Use case 3 : threshold an imageUse case 3 : threshold an image
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Filtering
Threshold
Monteverdi - ThresholdMonteverdi - Threshold
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Menu File > Open
./data_tp/theme2/IM2/extraitIm2_C/Im2_c_extrait.tif
Menu Filtering > Mean-shift clustering
Change radius : 5
Spectral radius : 15
Min region size : 15
Clusters : ON
Change values and Click on Run button
Click on Close button after selecting right set of parameters
See also :
➢ Image filtered / Image clustered
➢See OTB-Software-Guide_V3.0.pdf p 174
Use case 4 : segmentation with mean-shiftUse case 4 : segmentation with mean-shift
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Filtering
Meanshift clustering
Monteverdi – Mean-shiftMonteverdi – Mean-shift
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Menu File > Open
./theme2/IM2/extraitIm2_C/Im2_c_extrait.tif
Menu Filtering > Feature extraction
Test the following features (See OTB-Software-Guide_V3.0.pdf for
technical details on algorithms)
➢Edge detection : Touzi
➢Spectral angle : choose one vegetation pixel
➢Variance
➢Mean
➢Rec. gradient
➢Morphology > Morphology opening
➢Edge density > Sobel
➢Original data (=> no need to concatenate channels after filtering)
Use case 5 : Feature extraction (1/2)Use case 5 : Feature extraction (1/2)
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Menu Filtering > Feature extraction
Test the following features (See OTB-Software-Guide_V3.0.pdf for
technical details on algorithms) :
➢Radiometric indexesVegetation
• NDVI, RVI, PVI, etc Soil
• BI2
Built up• ISU
Further work :
➢Rename output image channels
➢Save your result
➢Build Mean, variance image on a Touzi image
Use case 5 : Feature extraction (2/2)Use case 5 : Feature extraction (2/2)
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Filtering
Feature Extraction (1/2)
Monteverdi – Feather extractionMonteverdi – Feather extraction
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Filtering
Feature Extraction (2/2)
Monteverdi – Feather extractionMonteverdi – Feather extraction
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Solution : mean, variance over Touzi image
Reader
Feature Extraction (Reader0) > Touzi
Feature Extraction (FeatureExtraction1) > Mean, Variance
Save your result
Monteverdi – Feather extractionMonteverdi – Feather extraction
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Menu File > Open
./theme1/IM2/Extraits/Ext_IM2_04102008_10mC.tif
Menu Filtering > Feature extraction > NDVI
Menu File > Concatenate Image
Add Reader0 → Channel 1
Add Reader0 → Channel 2
Add FeatureExtraction1 → OutputImage
View the result
Use case 6 : concatenate your resultsUse case 6 : concatenate your results
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File > Concatenate images
Monteverdi – Concatenate imagesMonteverdi – Concatenate images
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Menu File > Open
./theme2/IM2/extraitIm2_C/Im2_c_extrait.tif
Menu Learning > SVM Classification
Create several classes (4-5)
➢Edit names
➢Change colors
➢Select polygons
Learn
Validate
Display
Further work :
Same case with concatenated NDVI channel
Use case 7 : supervised classification with SVMUse case 7 : supervised classification with SVM
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Menu Learning > SVM classification (1/3)
MonteverdiMonteverdi
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Menu Learning > SVM classification (2/3)
MonteverdiMonteverdi
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Menu Learning > SVM classification (3/3)
MonteverdiMonteverdi
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Menu File > Open
./theme2/IM2/extraitIm2_C/Im2_c_extrait.tif
Menu Learning > k-means clustering (doc OTBSoftwareGuide_V3.0.pdf p 448)
Training 15%
Number of classes : 5
Iteration number : 1
Convergence : 0.0001
Further work :
Compare with SVM supervised classification
Use case 8 : unsupervised clustering with k-meansUse case 8 : unsupervised clustering with k-means
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Menu Learning > K-means
MonteverdiMonteverdi
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Menu File > Open
./reunion_S5/thr1a/imagery.tif
Menu Geometry > Orthorectification
Size X : 220, Size Y : 200
(try larger size with powerful computers)
Spacing X : 10, Spacing Y : -10 (m)
Longitude : -55.4, Latitude : -21.0
UTM / Linear
(=> Module created in pipeline)
Visualization > Viewer (Orthorectifcation0) > Click on Streamed / Cache (This launches the orthorectification).
“Cached” : click on OK to view the image
Use case 9 : orthorectify an image (Spot 5 level 1A) without DEM
Use case 9 : orthorectify an image (Spot 5 level 1A) without DEM
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Menu Geometry > Orthorectification (1/2)
MonteverdiMonteverdi
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Menu Geometry > Orthorectification (2/2)
MonteverdiMonteverdi
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Menu File > Open
./reunion_S5/thr1a/imagery.tif
Menu Geometry > Orthorectification
Size X : 220, Size Y : 200
(try larger size with powerful computers)
Spacing X : 10, Spacing Y : -10 (m)
Longitude : -55.4, Latitude : -21.0
UTM / Linear
DEM : enter the directory where .hgt files are
Visualization > Viewer (Orthorectifcation0) > Click on Streamed / Cache (This launches the orthorectification).
“Cached” : click on OK to view the image
Use case 10 : orthorectify an image (Spot 5 level 1A) with DEM
Use case 10 : orthorectify an image (Spot 5 level 1A) with DEM
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Menu Geometry > Superimpose two images
Combination of geometric models of the two images (note : works with
images with geometric model)
➢ Image to be superimposed : use of the direct geometric model to
build Longitude/Latitude projection
➢Combination with the inverse model of the reference image.
➢Reprojection
Use case 11 : Superimpose XS image over THR one (1/2)Use case 11 : Superimpose XS image over THR one (1/2)
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Menu File > Open
./reunion_S5/thr1a/imagery.tif
Menu Geometry > Orthorectification
Size X : 220, Size Y : 200
Spacing X : 10, Spacing Y : -10 (m)
Longitude : -55.4, Latitude : -21.0
UTM / Linear
Menu Geometry > Superimpose two images
Image to reproject : J1A / XS image
Reference Image : ortho of THR1A / Panchromatic image
Choose the same DEM model
Visualization > Viewer (Reprojected Image) > Stream / Caching... / Cached
Use case 11 : Superimpose XS image over THR one (2/2)Use case 11 : Superimpose XS image over THR one (2/2)
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Menu Geometry > Superimpose two images
Monteverdi – Superimpose two imagesMonteverdi – Superimpose two images
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Thank you for your attention !
Monteverdi Monteverdi
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