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Compute Control Points

Summary

Computes the control points between the mosaic dataset and the reference image. The control points can then be used in conjunction with tie points to compute the adjustments for the mosaic dataset.

Usage

  • If you want accurate control point results, the High tolerance option for the Similarity parameter is recommended.

  • The control points can be combined with tie points, using the Append Control Points tool.

  • The control points and tie points are then used within the Compute Adjustments tool.

  • If you have many items within your mosaic dataset, the Output Image Features parameter should not be specified; otherwise, your result can take a long time to calculate.

Syntax

ComputeControlPoints_management (in_mosaic_dataset, in_reference_images, out_control_points, {similarity}, {out_image_feature_points})
ParameterExplanationData Type
in_mosaic_dataset

The input mosaic dataset that will be used to create control points.

Mosaic Dataset; Mosaic Layer
in_reference_images

The reference images that will be used to create control points for your mosaic dataset. If you have multiple images, create a mosaic dataset from the images and use the mosaic dataset as the reference.

Raster Layer; Raster Dataset; Image Service; MapServer; WMS Map; Mosaic Layer; Internet Tiled Layer; Map Server Layer
out_control_points

The output control point table. This table will contain the control points that were created.

Feature Class
similarity
(Optional)

Choose the tolerance level for your control point matching.

  • LOW —The similarity tolerance for finding control points will be low. This option will produce the most control points, but some may have a higher level of error.
  • MEDIUM —The similarity tolerance for finding control points will be medium.
  • HIGH —The similarity tolerance for finding control points will be high. This option will produce the least number of control points, but each matching pair will have a lower level of error. This is the default.
String
out_image_feature_points
(Optional)

The output image feature points table. This will be saved as a polygon feature class. This output can be quite large.

Feature Class

Code sample

ComputeControlPoints example 1 (Python window)

This is a Python sample for the ComputeControlPoints tool.

import arcpy
arcpy.ComputeControlPoints_management("c:/block/BD.gdb/redQB", 
     "c:/block/BD.gdb/redQB_tiePoints", "HIGH",
     "c:/block/BD.gdb/redQB_mask", "c:/block/BD.gdb/redQB_imgFeatures")
ComputeTiePoints example 2 (stand-alone script)

This is a Python script sample for the ComputeControlPoints tool.

#compute control points

import arcpy
arcpy.env.workspace = "c:/workspace"

#compute control points using a mask 
mdName = "BD.gdb/redlandsQB"
in_mask = "BD.gdb/redlandsQB_mask"
out_controlPoint = "BD.gdb/redlandsQB_tiePoints"
out_imageFeature = "BD.gdb/redlandsQB_imageFeatures"

arcpy.ComputeControlPoints_management(mdName, out_controlPoint, 
     "HIGH", in_mask, out_imageFeature)

Environments

Licensing information

  • ArcGIS for Desktop Basic: No
  • ArcGIS for Desktop Standard: Yes
  • ArcGIS for Desktop Advanced: Yes

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