PSG4U2

Description

Estimate the new general four-component scattering power decomposition with unitary transformation of the coherency matrix. The total power is decomposed into surface, double-bounce, volume, and helical scattering.

Parameters

Name	Type	Length	Value range
Input: Input fully polarimetric SAR image *	Raster port	1 -
Output: Output decomposed raster *	Raster port	1 -

* Required parameter

Parameter descriptions

Input: Input fully polarimetric SAR image

The name of the input polarimetric SAR data set. The input data set must contain either non-symmetrized or symmetrized fully polarimetric (quad-polarization complex) data in scattering, covariance, coherence, or Kennaugh format. The input can be either single-look or multi-look.

Multi-look can be achieved by applying a polarimetric filter (PSBOXCAR or PSPOLFIL) prior to computing the decomposition.

The input file must be a data set that has already been imported in PCIDSK (.pix) format by SARINGEST. Alternatively, it can be the key-file name of any GDB-supported POLSAR data set in its distribution format. For more information, and a complete list of supported POLSAR sensors and data products, see SARINGEST.

Output: Output decomposed raster

The name of the output file that will hold the classification results. The output file has the same dimensions as the input file. with multi-look data, the output contains four floating-point channels representing the contribution to the power from each of the four scattering mechanisms (surface, double-bounce, volume, and helix). With single-look data, only three channels are written because the helical scattering layer is zero.

The specified file must not already exist.

Details

PSG4U2 estimates the unsupervised general four-component scattering power decomposition, based on the unitary transformation of the coherency matrix. With multi-look data sets, the total power at every pixel is partitioned into surface, double-bounce, volume, and helix scattering. With single-look data sets, the zero-valued helical layer is not written and the total power is partitioned into surface, double-bounce, and volume components.

Algorithm

Convert the data set to symmetrized coherence. Based on the T23 element, compute and apply the rotation angle. Based on the ratio of VV to HH, compute the values for surface scattering, double-bounce scattering, volume scattering and helix scattering as described in the reference.

References

Singh G., Yamaguchi Y., Park S., "General Four-Component Scattering Power Decomposition with Unitary Transformation of Coherency Matrix", IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, No. 5. May 2013.