Chapter 3
Recipes

This chapter presents guideline to perform various remote sensing and image processing tasks with either OTB Applications, Monteverdi or both. Its goal is not to be exhaustive, but rather to help the non-developper user to get familiar with these two packages, so that he can use and explore them for his future needs.

 3.1 From raw image to calibrated product
  3.1.1 Optical radiometric calibration
  3.1.2 Pan-sharpening
  3.1.3 Digital Elevation Model management
  3.1.4 Ortho-rectification and map projections
  3.1.5 Residual registration
 3.2 SAR processing
  3.2.1 Calibration
  3.2.2 Despeckle
  3.2.3 Polarimetry
 3.3 Image processing and information extraction
  3.3.1 Simple calculus with channels
  3.3.2 Images with no-data values
  3.3.3 Segmentation
  3.3.4 Large-Scale Mean-Shift (LSMS) segmentation
  3.3.5 Dempster Shafer based Classifier Fusion
 3.4 Classification
  3.4.1 Pixel based classification
  3.4.2 Fusion of classification maps
  3.4.3 Majority voting based classification map regularization
  3.4.4 Regression
  3.4.5 Samples selection
 3.5 Feature extraction
  3.5.1 Local statistics extraction
  3.5.2 Edge extraction
  3.5.3 Radiometric indices extraction
  3.5.4 Morphological features extraction
  3.5.5 Textural features extraction
 3.6 Stereoscopic reconstruction from VHR optical images pair
  3.6.1 Estimate epipolar geometry transformation
  3.6.2 Resample images in epipolar geometry
  3.6.3 Disparity estimation: Block matching along epipolar lines
  3.6.4 From disparity to Digital Surface Model
  3.6.5 One application to rule them all in multi stereo framework scheme
  3.6.6 Stereo reconstruction good practices
  3.6.7 Algorithm outline
 3.7 BandMathX application (based on muParserX)
  3.7.1 Syntax : first elements
  3.7.2 New operators and functions