Gamma ISP: Reference Manual

offset_pwr

offset_pwr estimates the range and azimuth registration offset fields using cross correlation optimization of the detected SLC data (rather than the fringe visibility algorithm used in offset_SLC). offset_pwr is used for SLC data that is either stored as pairs of floats (fcomplex) or pairs of short integers (scomplex).

SYNOPSIS
offset_pwr offset_pwr <SLC1> <SLC2> <SLC1_par> <SLC2_par> <OFF_par> <offs> <snr> [rwin] [azwin] [offsets] [n_ovr] [nr] [naz] [thres] [c_ovr] [pflag] [pltflg]

<SLC-1>	(input) single-look complex image 1 (reference)
<SLC-2>	(input) single-look complex image 2
<SLC1_par>	(input) SLC-1 ISP image parameter file
<SLC2_par>	(input) SLC-2 ISP image parameter file
<OFF_par>	(input) ISP offset/interferogram parameter file
<offs>	(output) offset estimates (FCOMPLEX)
<snr>	(output) offset estimation SNR (FLOAT)
[rwin]	search window size (range pixels, (enter - for default from offset parameter file))
[azwin]	search window size (azimuth pixels, (enter - for default from offset parameter file))
[offsets]	(output) range and azimuth offsets and SNR data in text format, enter - for no output
[n_ovr]	SLC oversampling factor (integer, (1,2,4), default: 2)
[nr]	number of offset estimates in range direction (enter - for default from offset parameter file)
[naz]	number of offset estimates in azimuth direction (enter - for default from offset parameter file)
[thres]	offset estimation quality threshold (enter - for default from offset parameter file)
[c_ovr]	correlation function oversampling factor (integer (1,2,4) default: 4)
[pflag]	print flag: 0: print offset summary 1: print all offset data
[pltflg]	plotting flag: 0: none (default) 1: output plots in PNG format 2: screen output and PNG format plots 3: output plots in PDF format

EXAMPLE
offset_pwr 19960421.slc 19960422.slc 19960421.slc.par 19960422.slc.par 19960421_19960422.off 19960421_19960422.offs 19960421_19960422.snr 64 64 19960421_19960422.offsets 2 32 64 7.0

estimates range and azimuth registration offsets (offsets of 19960421.slc relative to 19960422.slc) using the cross-correlation algorithm over a grid of 32 range locations and 64 azimuth locates. Each of the patches is 64x64 pixels. The SLC oversampling factor is set to 2.

offset_pwr 19960421.slc 19960422.slc 19960421.slc.par 19960422.slc.par 19960421_19960422.off offs snr 64 64 offsets 2 8 8 7.0 4 1 2

In this example offsets are calculated on an 8 x 8 grid in the geometry of SLC-1. The offset measurements are printed to the screen and plots are generated for each point and displayed on the screen.

DESCRIPTION

offset_pwr estimates the range and azimuth registration offset fields using cross correlation optimization of the detected SLC data. This cross correlation optimization algorithm rapidly generates the offset fields by correlating image chips. The image chips dimensions can be specified on the command line and can vary in the range of 16 to 512 depending on the interferogram correlation. The coordinates of the image section selected to be processed are relative to SLC-1.

The number of image chips used in range and azimuth, the range and azimuth sizes of the image chips used in the search, and the signal to noise (SNR) threshhold to accept an estimate may be entered on the command line. Default values are taken from the ISP offset/interferogram parameter file. Recommended values are suggested as default values in the program create_offset. For the SNR threshold, values of 7.0 and larger are recommended.

The range and azimuth offset estimates are written to a binary data file (fcomplex format) with the offsets coded as pairs of floating point numbers (range offset, azimuth offset). This algorithm is somewhat less accurate than the fringe visibility method, but has the advantage that it is faster than the coherence optimization method and more robust in the presence of low correlation.

A disadvantage of this algorithm is that some estimates can be very far off and still show high SNR, especially in urban regions. In other words the SNR values used as qualtiy measure for the reliability of each individual estimate are not always reliable itself. Usually, such blunders can be effectively removed later on based on its high deviation from the global fit (a feature supported by the offset_fit program which is used to calculate the registration offset polynomial based on the offset and SNR estimates).

For most cases a SNR threshold of 7.0 for the acceptance of an offset leads to good results. In cases of low correlation the selection of a larger estimation window may be the better choice than the reduction of the threshold. If the number of valid offsets is 0 then the program exists with an error.

Oversampling of the SLC images is supported. The minimum SLC oversampling factor should be selected to be 2. Using no SLC oversampling results in aliasing of the 2D correlation function used to determine offset. Nominal oversampling factor is 2, and if the precision measurement of the offset field is desired, increasing this value to 4.The location of the correlation maximum is estimated using a two-dimensional quadratic least squares fit.

OPTIONS
The offset estimation programs use already existing range and azimuth offset polynomials found in the ISP offset/interferogram parameter file to improve its initial registration offset guess. An iterative use of this feature allows to optimize the efficiency and accuracy of the registration offset estimation. After an initial offset estimation from the orbit parameters (init_offset_orbit) or the data itself (init_offset, a first offset polynomial is determined based on estimates calculated with offset_pwr which is efficient using large search windows. With these quite accurate registration polynomials offset_SLC_tracking or offset_pwr_tracking can then be run efficiently on many locations throughout the image, using small search windows.