| Environments | PYTHON :: EASI :: MODELER |
| Quick links | Description :: Parameters :: Parameter descriptions :: Details :: Example |
| Back to top |
| Back to top |
| Name | Type | Caption | Length | Value range |
|---|---|---|---|---|
| MFILE * | String | Input file name, directory, or text file | 1 - 192 | |
| DBGC | Integer | Input Ground Control Point segment or layer | 0 - 1 | |
| ORDER | Integer | Transformation Order | 0 - 1 | |
| MMSEG | Integer | Output math model segment or layer | 0 - 1 | |
| REPORT | String | Report mode | 0 - 192 | Quick links |
| Back to top |
MFILE
Specifies a particular file or multiple files to be processed. Wildcards (*) can be used.
DBGC
Specifies the input GCP segment or layer to use when computing the model.
DBGC must be specified either in the task or in the text file. If a folder is specified for MFILE, this segment number applies to all images. If MFILE specifies a text file, the value for DBGC is read from the file; this parameter can therefore remain empty.
ORDER
Specifies the order of the transformation that is used to compute the two-dimensional polynomial model. Valid values are 1, 2, 3, 4, or 5. If the minimum number of GCPs is not provided for the specified transformation order, the next lowest order possible is used.
If a folder is specified for MFILE, this segment number applies to all images. If MFILE specifies a text file, the value for ORDER is read from the file; this parameter can therefore remain empty.
MMSEG
Specifies the output math model segment or layer in which to store the computed model.
If a folder is specified for MFILE, this segment number applies to all images. If MFILE specifies a text file, the value for MMSEG is read from the file; this parameter can therefore remain empty. If no value is specified, a new segment is created.
REPORT
Specifies where to direct the generated report.
Available options are:
| Back to top |
POLYMODEL is a simple math model that uses a first-through-fifth order polynomial transformation, which is calculated based on two-dimensional GCPs. This math model produces the best-fit mathematically to a set of two-dimensional GCPs on an image.
The polynomial equations are fitted to the x- and y-coordinates of the GCPs by using least-squares criteria to model the correction in the image without identifying the source of the distortion. You may choose one of several polynomial orders, depending on the desired accuracy and the number of available GCPs.
First-order polynomial transformations can model a rotation, a scale, and a translation. Because a maximum of 21 additional terms can be added, providing a fifth-order polynomial, you can achieve more complex warping. Using a lower-order transformation, however, reduces the time needed to complete the correction and less geometric distortion can occur in areas without GCPs.
| Back to top |
Compute the polynomial model of an image.
EASI>mfile="xxx.pix" EASI>dbgc=3 EASI>order=2 EASI>mmseg= EASI>report= EASI>r polymodel
© PCI Geomatics Enterprises, Inc.®, 2026. All rights reserved.