Super Registration module

Description

The Super Registration module gathers a dense collection of match points and offsets from the reference image and the input image, and then resamples the input orthorectified image to match the reference image.

Parameters

Name	Caption
Input Orthos	The set of orthorectified imagery to process
Output Folder	Output folder
Save Intermediate Files	Save intermediate files
Overwrite Results	Overwrite existing results
Send Email	Email notification settings
Reference Images	Reference images to use
Reference Channel for Matching	Reference image channel to use for matching
Matching Channels	The channels from the input images to use for matching
Search Radius	Search radius (pixels)
Grid Spacing	The grid spacing for matching on the reference image
FFT Size	FFT template matching size
Generate Offsets For Every Pixel	Whether to generate X/Y offsets for every pixel or at a coarser resolution interpolating and resampling between pixels
Minimum Score	Minimum score (percentage)
Point Matching Strategy	The matching point strategy to select a point when multiple overlapping reference images exist
Point Cleaning Level	Level of filtering that is applied to the match points
Exclusion Masks To Use	Choose exclusion masks to use
Create Accuracy Assessment Map	Create accuracy assessment map

Parameter descriptions

Input Orthos

The name of the folder that contains valid, GDB-supported orthorectified images.

This parameter can be specified by using any of the following:

Path and name of a folder of input orthorectified images; for example, C:\data
Path and name of a folder with a wildcard to filter the imagery by file name or type; for example, C:\data\*ORTHO_MS.pix
You can also specify an MFILE as input. An MFILE is a text file with an .mfile file name extension. For more information on this type of file, see About the MFILE format.

Output Folder

The path and name of the folder to which to write the output files.

Save Intermediate Files

Select this check box to save any supporting files created during processing.

By keeping the files, you can use them to analyze intermediate results and, if necessary, fix any minor issues. You can then restart the job without having to regenerate all the supporting data, thereby reducing processing time.

Note: Intermediate files can consume a large quantity of disk space, thus it is a good idea to delete them when they are no longer needed.

Overwrite Results

Select this check box to overwrite the existing output files, if any exist. If this check box is left clear, and an output file exists in the relevant folder, the status of the job displays a message informing you of the existence and name of the output file. The message is also written to the event log of the job.

Send Email

If necessary, you can set up CATALYST Enterprise to send an email notification on job start and job completion.

With this check box selected, an email message is sent to each address specified in the Email Addresses box after the job starts and on completion.

You can specify one or more addresses, and each must be separated by a comma or a semi-colon. The email address of the user currently logged in displays by default.

Reference Images

Geocoded reference ortho image or images to compare against. This can be a single file name, directory path with wild card, or name of a text file (.txt) that contains the names of files. For best results it is recommended to use reference images in the same projection and resolution as input images.

Reference Channel for Matching

The channel from reference image to use for matching when collecting ground control points (GCPs). Channel 1 is the default.

Matching Channels

The input channels that contain the imagery to be used in matching.

Typically this is a single channel. Up to three channels can be specified. If extra channels are specified then matching is attempted on all channels and the results are used to cross check for blunders, potentially resulting in better accuracy, though at the cost of significantly higher processing time.

If you do not specify a value for this parameter, channel 1 is used, by default.

Search Radius

The distance in the x and y directions from a starting location on the reference image over which the search for the best match with a fixed point on the input image is conducted.

The search radius is an estimation of error with the raw image's positional information and the digital elevation model (DEM) accuracy. If you know that your image is accurate to within 80 meters, and your DEM is accurate to within 200 meters, set the search radius to 280 meters. A larger search radius requires more processing time, because more locations are evaluated to determine the best match for a ground control point (GCP).

If this parameter is not specified, the function uses a default search radius based on the resolution of input data.

Grid Spacing

The spacing in pixels between the points on a grid, for matching on the reference image.

Values between 1 and 500 are supported and typically a value between 10 and 50 is used. Smaller grid spacings can model finer mismatch detail and take longer to run. In most cases a value of 25 is a good balance between detail and running time. If the orthorectified imagery is far apart in time (for example 5 years) and looks quite different, a smaller grid may be necessary since many of the grid locations may fail to find a match.

If you do not specify a value for this parameter, 25 is used, by default.

FFT Size

Specifies the FFT template matching size in pixels. Larger sizes tend to have fewer blunders, but are less precise and run more slowly.

Generate Offsets For Every Pixel

Select this check box to to generate X/Y offsets all valid pixels.

Generating an offset for every pixel produces better overall results, at the cost of more processing time and increased disk space.

Minimum Score

The threshold value that controls whether a candidate ground control point (GCP) is accepted as a GCP or rejected. This parameter specifies the minimum-match quality that is considered acceptable, with 1.0 indicating a perfect match.

When using the Fast Fourier Transform Phase matching algorithm, this value is converted internally to a minimum acceptable phase-shift peak value.

When using the Normalized Cross-Correlation matching algorithm, this value specifies the minimum match score value required to accept a local match between the input and reference images as a GCP. The default value is 0.75.

Point Matching Strategy

The strategy to be used for managing matching points when multiple reference images are provided.

First: This strategy is fastest by choosing the matching point from the first reference processed.
Best: This strategy selects the highest quality matching points from all available reference images.

Point Cleaning Level

Level of filtering, to eliminate bad matches, that is applied to the match points. Filtering removes blunders and smooths the results. The more filtering applied, the more blunders are removed and smoothing is done, resulting in potentially less accurate results.

Low: apply only a small amount of filtering. Use this option sparingly. Only use it if the input images and reference images are taken at nearly the same time and are extremely similar. Eliminating most of filtering for such images can improve performance with very little degradation in quality.
Medium: apply only a medium amount of filtering. This option should almost always be used.
High: apply a high amount of filtering. This option should be used when the input images and the reference images might have large differences.
None: do not apply any filtering. This option should almost never be used. Only use it if the input images and reference images are taken at nearly the same time and are extremely similar. Eliminating filtering for such images can improve performance with very little degradation in quality.

Exclusion Masks To Use

Whether to exclude match points due to the bitmap exclusion masks in the reference image or input image.

In Both Input and Reference Image: use the bitmap exclusion masks in both the input images and the reference images.
In Reference Image Only: only use the exclusion mask in the reference image.
In Input Image Only: only use the exclusion mask in the input images.
None: do not use any exclusion masks.

Create Accuracy Assessment Map

Create accuracy assessment map by comparing orthorectified images against reference images.

Details

General job details

Preprocessing requirements

Before running this module, the following requirements must be met to ensure the job processes successfully and produces accurate results:

The input imagery must consist of orthorectifed images.
All input files must be in PCIDSK format (.pix).
All exclusion masks, in both the input orthos and the input reference images, must be bitmaps.

Module details

The Super Registration module gathers a dense collection of match points between the reference image and the input orthorecitified image, and then coregisters the input orthorecitified image to the reference image. The module is recommended for use when the input orthorectified images are in close proximity. The coregistration between orthorecitified images is improved to the level of accuracy required for Analysis Ready Data (ARD).

Job results

On successful completion, the Super Registration module creates a super-registered orthorectified image for each valid input orthorectified image. The output file is written to the specified output folder using the name of the original file.