POLYMODEL

Description

POLYMODEL is a simple math model that produces the best mathematical fit to a set of two-dimensional ground control points (GCPs).

Parameters

Name	Type	Length	Value range
Input: Image Layers: Input image layers to be processed *	Raster port	1 - 1024
Input: GCP: Input Ground Control Point segment or layer	GCP port	0 - 1
Transformation Order	Integer	0 - 1
OutputMM: Output math model segment or layer	BIN port	0 - 1
Report	String	0 - 192	See parameter description

* Required parameter

Parameter descriptions

Input: Image Layers: Input image layers to be processed

Specifies the input raw image layers to be processed.

Input: GCP: Input Ground Control Point segment or layer

Specifies the input GCP segment or layer to use when computing the model.

Transformation 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.

OutputMM: Output math model segment or layer

Specifies the output math model segment or layer in which to store the computed model.

Report

Specifies where to direct the generated report.

Available options are:

• LOG: generates a report on the terminal (default)
• <modulename.RPT>: appends a report to the module's RPT file
• DISK: generates a report on file "IMPRPT.LST"

Details

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.