The process aligns a source image to a reference image. Its algorithm automatically detects and minimizes misalignments between features using rigid-body transformation. The results are GeoTIFF files of matching optical assets with improved positional accuracy.
Coregistration can be used as a preprocessing step before change detection, data fusion, and DEM generation.
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Examples of input images:
A source image that hasn't been coregistered, with a highlighted reference area
A reference image with better positional accuracy, with a highlighted reference area
The results are the following:
- A GeoTIFF of the coregistered source image
- A GeoTIFF floating point displacement map of calculated misalignment after coregistration
- A GeoTIFF heatmap for displacement, with warmer colors showing greater misalignments
A floating point displacement map and a heatmap won’t be generated in case of too few tie points in the input files.
A coregistered source image, with a highlighted reference area
A map of calculated misalignment overlaid on the coregistered source image
A heatmap for displacement overlaid on the coregistered source image
The coregistration algorithm aligns images accurately, even if they have different resolutions or sensor types. It can handle clouds and land cover changes. It calculates sub-pixel shifts by analyzing local image patches, then aligns the images using rigid-body translation and rotation.
To get the best results, make sure that:
- Both data items have matching geometric and radiometric processing levels.
- The GSD of the two data items doesn’t differ by more than 25%.
Both data items must be CNAM-compatible. CNAM-compatible data meets both criteria:
- The data was added to storage starting in 2023.
- The data comes from a supported collection.
Both data items must come from an optical collection.
Both data items must be georectified or orthorectified.
Both data items must have an asset with the same bands.
The geometries of the data items must overlap by at least 20%.
The cloud coverage of the data items must be less than 25%.
You must specify the data item for the source image you want to coregister.
You must specify the data item for the reference image for coregistration. The positional accuracy of the source image will be improved against this reference.
You must specify the title of the output data item.
Use the coregistration-simularity name ID for the processing API.
{ "inputs": { "title": "Coregistering imagery over Berlin", "sourceItem": "https://api.up42.com/v2/assets/stac/collections/21c0b14e-3434-4675-98d1-f225507ded99/items/23e4567-e89b-12d3-a456-426614174000", "referenceItem": "https://api.up42.com/v2/assets/stac/collections/21c0b14e-3434-4675-98d1-f225507ded99/items/edeb6310-ea9a-4d8e-943d-11a5f3757824" }}| Parameter | Overview |
|---|---|
inputs.title | object | required The title of the output data item. |
inputs.sourceItem | array of strings | required A link to the source data item in the following format: |
inputs.referenceItem | array of strings | required A link to the reference data item in the following format: |