the use of orfeo toolbox in the context of map updating
DESCRIPTION
The use of Orfeo Toolbox in the context of map updating Christophe Simler; Royal Military Academy Charles Beumier; Royal Military Academy Christine Leignel; Université Libre de Bruxelles Olivier Debeir; Université Libre de Bruxelles Eléonore Wolff; Université Libre de BruxellesTRANSCRIPT
The use of Orfeo Toolbox in the Context of Map Updating
Christophe SimlerRoyal Military Academy
Brussels, Belgium
Main part of the ARMURS projectVHR satellite image (Ikonos or Quickbird) or aerial image RGB
XS pansharpenedmultispectral pixel description and mean shift segmentation
segmented image
raster of an old vectorgeographical database
region feature extraction and SVM classification
classified image (road/building/other)
change map (roads and buildings)
comparaison
pansharpening
database update
Softwares
-ORFEO Toolbox
-Development
-Proprietary code
-Open source code
FreewareExtensibleHandle most image format (use GDAL)Image processing for remote sensing
Main part of the ARMURS projectVHR satellite image (Ikonos or Quickbird) or aerial image RGB
XS pansharpenedmultispectral pixel description and mean shift segmentation
segmented image
raster of an old vectorgeographical database
region feature extraction and SVM classification
classified image (road/building/other)
change map (roads and buildings)
comparaison
pansharpening
database update
Main part of the ARMURS projectVHR satellite image (Ikonos or Quickbird) or aerial image RGB
XS pansharpenedmultispectral pixel description and mean shift segmentation: otb::MeanShiftVectorImageFilter
segmented image
raster of an old vectorgeographical database
region feature extraction and SVM classification: otb::SVMModel and otb::SVMClassifier
classified image (road/building/other)
change map (roads and buildings)
comparaison
pansharpening: otb::SimpleRcsPanSharpeningFusionImageFilter
database update
Mean shift segmentation results
Roads and buildings aregenerally preciselyextracted
Part of an Ikonos satelliteimage in the region ofJodoigne (Belgium)
Régions feature extraction
The regions obtained from the segmentation are described by the followingfeature vector:
areaeccentricity mean R mean G mean Bmean NIR
Image classification
The feature vectors are classified into classes « roads », « building » or « other »
Support Vector Machine (SVM)
Training set
Our training set is composed of about 1000 mean shift regions manually assignedto class « road », « building » or « other »
two componants of ourfeature vector:
Training
two 2-class SVM with Gaussian kernel are trained independently
road/other building/other
Parameters to tune: - kernel standard deviation- penalisation of the misclassifications
Training
training setnew couple of parameter values
decision boundaries
test set
learning
balanced loss=
INPUT : training set (road/other or building/other)
optimal parameter values(loop)
learning
OUTPUT : decision boundaries
permutation
INPUT : 2D grid value for the 2 parameters to tune
FPVN
FP
FNVP
FN
++
+=
1- optimisation of the two parameters by cross validation2- learning on the whole set3- classifier performance quantification
Optimal tuning
Energie to minimise
Optimal tuning
Minimisation with coarse-to-fine approach
Optimal tuning
Minimisation with coarse-to-fine approach
Classification: SVM input image
Part of an aerial RGBimage of a region ofBruxelles (Belgium)
SVM Classification results
Overlap of the two2-class SVM classification results
roads
buildingsother
both building androad (the existenceof such conflict areas is due to the fact the two 2-classSVM are trained separately)
Conclusion
The ORFEO ToolBox has been considered as a basic component in our application of map updating within the ARMURS project.
The provided image segmentation and classification functions speeded up the implementation and test of the approach.
As far as the demonstrator is concerned, the integrated file formats for image access and vector read are important assets.
We are also currently considering the potential of the recent OTB applicationUrban Area Extraction (from OTB 3.0) as a component on which to base building and road extraction.