Available with Advanced license.
The parameters used in computing the block adjustment are defined in the Adjust window. The adjustment options available depend on the type of workspace you defined when you set up your ortho mapping project.
Adjustment options for scanned aerial data
The block adjustment parameters for scanned aerial photographs are described below.
Perform Camera Calibration
Automatic camera calibration computes and improves the camera’s geometric parameters, while determining image orientation and image ground coordinates. Select these options to improve the overall quality and accuracy of bundle block adjustment. For more information on calibration options, see Cameras table schema.
- Focal Length—Refines the focal length of the camera lens
- Principal Point—Refines the principal point of the autocollimation
- K1,K2,K3—Refines the radial distortion coefficients
- P1,P2—Refines the tangential distortion coefficients
Note:
Automatic camera calibration requires that your image collection have an in-strip overlap of 60 percent or more and a cross-strip overlap of 30 percent or more.Advanced Options
The Advanced Options section provides additional settings that can be used to optimize the adjustment process. A description of each setting is given below.
Quick Adjust At Coarse Resolution Only
If this option is checked, adjustment is performed at a coarse, user-defined resolution. This coarse adjustment is done quickly and allows you to review the data coverage for your project area and the processing parameters for the collection before running the more accurate, refined adjustment at the source imagery resolution. For example, when you collect data in the field, you can use this option for an initial assessment of the adjustment. Then run Adjust again to compute the refined adjustment. If this option is not checked, tie points are computed at the source image resolution, and triangulation is performed using the computed tie points.
Compute posterior standard deviation for images and solution points
The following options allow you to compute the standard deviation for the image exterior orientation parameters and solution point coordinates:
- Compute Posterior Standard Deviation for Images—The posterior standard deviation of solution points after adjustment is computed. The computed standard deviation values are stored in the Solution table.
- Compute Posterior Standard Deviation for Solution Points—The posterior standard deviation of each image location and orientation after adjustment are computed. The computed standard deviation values are stored in the Solution Points table.
Reproject Tie Points
A part of the adjustment process includes computing and displaying each tie point at its correct 2D map location. This is an optional step that only supports the visual analysis of tie points with the 2D map view. Following adjustment, the Reproject Tie Points option in the Manage Tie Points drop-down menu must be used.
Note:
When working with large projects with more than 1,000 images, this step can be skipped to reduce adjustment processing duration, without any adverse impact to the adjustment quality.
Tie Point matching
Tie points are points that represent common objects or locations within the overlap areas between adjacent images. These points are used to improve geometric accuracy in the block adjustment. The Tie Point Matching category in the Adjust tool includes options to support the automatic computation of tie points from overlapping images. Check the Full Frame Pairwise Matching check box to enable the automatic computation of tie points. The following conditions must be met for optimal results:
- Topography imaged is highly variable, for example, hilly terrain with large variations in height.
- Forward and lateral overlap percentages between images are lower than the recommended value.
- The accuracy of the initial imagery orientation parameters and projection center coordinates are low.
- Images have high oblique angles.
Image Resolution Factor
Use this parameter to define a resolution at which match points will be computed and the initial adjustment performed. The range of values is between full resolution and 8 times the resolution of the source imagery.
The default value of 8 times the source resolution is suitable for most imagery that includes a diverse set of features. A smaller value, such as 4 or 2, can be used for imagery with ubiquitous features, such as sand, water, or agricultural areas, where match points are difficult to compute at coarse resolution.
Image Location Accuracy
The inherent positional accuracy of the imagery depends on the sensor viewing geometry, type of sensor, and level of processing. Positional accuracy is typically described as part of the imagery deliverable. Choose the keyword that best describes the accuracy of the imagery.
The values consist of three settings that are used in the tie point calculation algorithm to determine the number of images in the neighborhood to use. For example, when the accuracy is set to High, the algorithm uses a smaller neighborhood to identify matching features in the overlapping images.
| Setting | Description |
|---|---|
Low | Images have poor location accuracy and large errors in sensor orientation (rotation of more than 5 degrees). The scale invariant feature transform (SIFT) algorithm is used, which has a large pixel search range to support point matching computation. |
Medium | Images have moderate location accuracy and small errors in sensor orientation (rotation of less than 5 degrees). The Harris algorithm is used with a search range of approximately 800 pixels to support the point matching computation. This is the default setting. |
High | Images have high location accuracy and small errors in sensor orientation. This setting is suitable for satellite imagery and aerial imagery that has been provided with exterior orientation data. The Harris algorithm is used with a small search range to support point matching computation. |
Mask Polygon Features
Use a polygon feature class to exclude areas you do not want used when computing tie points.
In the attribute table of the feature class, the mask field controls the inclusion or exclusion of areas for computing tie points. A value of 1 indicates that the areas defined by the polygons (inside) are excluded from the computation. A value of 2 indicates that the areas defined by the polygons (inside) are included in the computation and areas outside of the polygons are excluded.
Scanned historical imagery tutorial
For a guided tutorial on the full scanned imagery workflow, see Create Scanned Aerial Imagery Products in ArcGIS Pro.