SARDecompositions - SARDecompositions

From one-band complex images (each one related to an element of the Sinclair matrix), returns the selected decomposition.

Detailed description

From one-band complex images (HH, HV, VH, VV), returns the selected decomposition.

All the decompositions implemented are intended for the mono-static case (transmitter and receiver are co-located). There are two kinds of decomposition : coherent ones and incoherent ones. In the coherent case, only the Pauli decomposition is available. In the incoherent case, there the decompositions available : Huynen, Barnes, and H-alpha-A. User must provide three one-band complex images HH, HV or VH, and VV (mono-static case <=> HV = VH). Incoherent decompositions consist in averaging 3x3 complex coherency/covariance matrices; the user must provide the size of the averaging window, thanks to the parameter inco.kernelsize.


This section describes in details the parameters available for this application. Table [1] presents a summary of these parameters and the parameters keys to be used in command-line and programming languages. Application key is SARDecompositions .

[1]Table: Parameters table for SARDecompositions.
Parameter Key Parameter Name Parameter Type
inhh Input Image Input image
inhv Input Image Input image
invh Input Image Input image
invv Input Image Input image
out Output Image Output image
decomp Decompositions Choices
decomp haa H-alpha-A incoherent decomposition Choice
decomp barnes Barnes incoherent decomposition Choice
decomp huynen Huynen incoherent decomposition Choice
decomp pauli Pauli coherent decomposition Choice
inco Incoherent decompositions Group
inco.kernelsize Kernel size for spatial incoherent averaging. Int
ram Available RAM (Mb) Int
inxml Load otb application from xml file XML input parameters file
outxml Save otb application to xml file XML output parameters file

Input Image: Input image (HH).

Input Image: Input image (HV).

Input Image: Input image (VH).

Input Image: Input image (VV).

Output Image: Output image.

Decompositions Available choices are:

  • H-alpha-A incoherent decomposition: H-alpha-A incoherent decomposition.
  • Barnes incoherent decomposition: Barnes incoherent decomposition.
  • Huynen incoherent decomposition: Huynen incoherent decomposition.
  • Pauli coherent decomposition: Pauli coherent decomposition.

[Incoherent decompositions]: This group allows setting parameters related to the incoherent decompositions.

  • Kernel size for spatial incoherent averaging.: Minute (0-59).

Available RAM (Mb): Available memory for processing (in MB).

Load otb application from xml file: Load otb application from xml file.

Save otb application to xml file: Save otb application to xml file.


To run this example in command-line, use the following:

otbcli_SARDecompositions -inhh HH.tif -invh VH.tif -invv VV.tif -decomp haa -out HaA.tif

To run this example from Python, use the following code snippet:


# Import the otb applications package
import otbApplication

# The following line creates an instance of the SARDecompositions application
SARDecompositions = otbApplication.Registry.CreateApplication("SARDecompositions")

# The following lines set all the application parameters:
SARDecompositions.SetParameterString("inhh", "HH.tif")

SARDecompositions.SetParameterString("invh", "VH.tif")

SARDecompositions.SetParameterString("invv", "VV.tif")


SARDecompositions.SetParameterString("out", "HaA.tif")

# The following line execute the application


Some decompositions output real images, while this application outputs complex images for general purpose. Users should pay attention to extract the real part of the results provided by this application.


This application has been written by OTB-Team.

See Also

These additional resources can be useful for further information:
SARPolarMatrixConvert, SARPolarSynth