Summary
Finds the image candidates within in the mosaic dataset that best represents the mosaic area.
Densely overlapped images are necessary in many projects but can cause uncertainty on which images within the mosaic dataset should be used in your analysis. This tool can help decide which images are optimal, based on areas of maximum overlap and maximum amount of area excluded.
The input mosaic dataset will include a new field named Candidate in the mosaic dataset footprint table. This field determines which images are used in certain operations, such as color balancing, seamline generation, ortho mapping, and mosaic methods.
Usage
This tool is useful when dealing with orthomosaic projects, where there may numerous overlapping UAV or UAS data in your mosaic dataset. In these cases choosing the optimal images within your mosaic dataset will generate a good block adjustment result for your orthomosaic.
Compute Mosaic Candidates should be used before running the Build Seamlines or Color Balance Mosaic Dataset tools. The input mosaic dataset will include a new field named Candidate in the mosaic dataset footprint table. This field determines which images are used in these operations.
The Candidate field in the mosaic dataset footprint table can have a value of 0, 1, or 2. A value of 0 means that the image is not an appropriate candidate. A value of 1 means that this image is an appropriate candidate according to the tool output, and it will automatically be used by any algorithms that use the Candidate field. A value of 2 can be manually added so the selected image will automatically be used by any algorithms that use the Candidate field.
The value in the Candidate field can be manually edited to include or exclude specific images.
Syntax
ComputeMosaicCandidates(in_mosaic_dataset, {maximum_overlap}, {maximum_area_loss})| Parameter | Explanation | Data Type |
in_mosaic_dataset | The input mosaic dataset with densely overlapped images. | Mosaic Dataset; Mosaic Layer |
maximum_overlap (Optional) | The maximum amount of overlap that you want between the mosaic dataset and the footprint of each image in the mosaic dataset. If the percentage of overlap is higher than this threshold, the image is excluded since it will have too much redundant information. The percentage is expressed as a decimal. For example, a maximum overlap of 60 percent is expressed as 0.6. | Double |
maximum_area_loss (Optional) | This is the maximum percentage of area that can be excluded by the candidate images. After the tool chooses the best candidate images based on the maximum_overlap, it will then check to see if the maximum excluded area is below the threshold specified. If the excluded area is greater than the specified threshold, the tool will add more candidate images to fill in some of the voids that were missing. Most of these excluded areas will likely be along the border of the mosaic dataset. The percentage is expressed as a double. For example, a maximum excluded area of 5 percent is expressed as 0.05. | Double |
Derived Output
| Name | Explanation | Data Type |
| out_mosaic_dataset | The updated mosaic dataset. | Mosaic Dataset; Mosaic Layer |
Code sample
ComputeMosaicCandidates example (Python window)
This is a Python sample that chooses the candidates with less than 60 percent overlap and less than 5 percent of the area excluded.
Import arcpy
arcpy.ComputeMosaicCandidates_management("c:/data/fgdb.gdb/md", 0.6, 0.05)
Environments
Licensing information
- Basic: No
- Standard: Yes
- Advanced: Yes