GCPCAND

You can choose from the following options:

• File metadata: Reads the NoData value from the NO_DATA_VALUE metadata tag of the input file. The file-level metadata tag is used as the default for each channel; channel-level tags, when available, override the default. When metadata does not exist, each pixel in the input is considered valid.
• 0: each pixel, in each channel, with a value of 0 is considered NoData.
• None: each pixel, in each channel, is considered valid.
• Specify values: each pixel, in each channel, with a value or values specified in the Source Background Values parameter is considered NoData.
• File metadata, else specify values: Same as File metadata, but uses the value specified for the Source Background Values parameter to define the NoData value for each channel, when metadata does not exist.

The source background value or values when the following options are specified for the Source Background Options parameter:

• Specify values
• File metadata, else specify values

For example:

• File metadata, 0: uses file-level metadata. When metadata is unavailable, pixels with a value of 0 are considered NoData.
• 255: each pixel, in each channel, with a value of 255 is considered NoData.

The syntax for LOCLMASK is:

LOCLMASK = (NONE | BIT | VEC | <n>)

You can specify the value of LOCLMASK using the following:

• NONE: exclude no pixels from the computation
• BIT: use when there are bitmap segments in at least some of the image files that define exclusion regions. When one of the images contains multiple bitmaps, the last one is used. All image pixels covered by the bitmap are excluded from point collection.
• VEC: use when there are vector segments in at least some of the source image files that define exclusion regions. When one of the source images contains multiple vector segments, the last one is used. This vector segment must be a polygon, and all image pixels enclosed by the polygon are excluded from point collection.
• <n>: specifies a particular segment number that contains the desired mask segment to be used.

Available options are:

• SUSAN: sample points are generated automatically by using the SUSAN corner-detection algorithm.
• GRID: (default) sample points are generated automatically by using sample points distributed evenly across the reference image.

• The SUSAN option finds candidates by running a corner-detection algorithm on the image, which looks for corner-like features to use as candidates.
• The GRID option creates candidates in a grid-like pattern. Because this option does not preprocess the image, it tends to be faster, but it also finds fewer matches, because the grid point might fall on a featureless flat patch somewhere in the image that cannot be matched to anything in the overlapping images.

You can choose from the following options:

• MAPSPACING: reads the value of the DISTNUM parameter as the spacing in reference-image map units between each point.
• PIXELSPACING: reads the value of the DISTNUM parameter as the spacing in reference-image pixels between each point.
• ENTIRE: reads the value of the DISTNUM parameter as a target number of points for the entire reference image.

This controls the number of GCPs to find, in the units specified for the DISTRIB (Distribution) parameter. The default value generally produces approximately 100 points evenly distributed over the reference image. When the value of the DISTRIB (Distribution) parameter is MAPSPACING, and the reference image has a projection in degrees, you can specify a string in the format degrees-minutes-seconds. The specific format is as follows:

• DD MM SS.SSS: separated by blanks.
• DDdMM'SS.SSS": delimited by degrees (d), minutes ('), seconds (") tokens
• DDdMM'SS.SSS: delimited by degrees (d), minutes ('), but no token needed for seconds field
• DD.DDD: decimal degrees
• SS.SSS": seconds only