You can publish a collection of images as a hosted dynamic imagery layer in your organization. After publishing, you can modify the visualization of a hosted imagery layer and optimize its performance with tools that can build image footprints and overviews, calculate statistics, and define NoData pixel values. The following sections describe how you can modify a hosted imagery layer with these tools.
Caution:
These tools are only available for dynamic imagery layers with the collection type attribute. They are not available for dynamic imagery layers that do not have the collection type attribute or tiled imagery layers.
Build footprints
Footprints contain the outline of each raster or image in the image collection. This outline is not always the extent of each raster dataset but can be the extent of the valid raster data in the dataset. To build footprints for a hosted imagery layer published with an image collection, complete the following steps:
- Sign in to your organization and open the item page for the image collection imagery layer.
Sign in as the layer owner or a member of the default administrator role.
- Click the Image Management tab, and click the Build Footprints button.
- Optionally, modify one or more of the following settings:
Method
The footprint computation method:
- Radiometry—Exclude pixels with a value outside of a defined range. This option is generally used to exclude border areas that do not contain valid data. If you choose this option, you can also specify the minimum and maximum values. This is the default.
- Geometry—Restore the footprint to its original geometry.
Approximate number of vertices
The complexity of the footprints is defined by the number of vertices. Valid values range from 4 to 10,000, or you can set the value to -1 for no generalization. A higher number of vertices will result in more accurate, and likely more irregular, footprints.
Shrink distance
Clip the footprint by this distance. This can eliminate artifacts from using lossy compression, which causes the edges of the image to overlap into NoData pixels.
Simplification method
Reduce the number of vertices in the footprint to improve performance.
- None—Do not limit the number of vertices. This is the default.
- Convex hull—Use the minimum bounding box to simplify the footprint.
- Envelope—Use the envelope of each mosaic dataset item to simplify the footprint.
Skip overviews
Adjust the footprints of overviews.
- Checked—Do not adjust the footprints of overviews. This is the default.
- Unchecked—Adjust the footprints of overviews and associated raster datasets.
Update boundary
Update the boundary of the mosaic dataset if you added or removed imagery that changes the extent.
- Checked—Update the boundary. This is the default.
- Unchecked—Do not update the boundary.
Maintain sheet edges
Alter the footprints of raster datasets that have been tiled and are adjacent (line up along the seams with little to no overlap).
- Unchecked—Remove the sheet edges from all the footprints. This is the default.
- Checked—Maintain the footprints in their original state.
- Optionally, click Show more settings and modify one or more of the following:
Request size
Set the resampled extent (in columns and rows) for the raster when building footprints. Greater image resolution provides more detail in the raster dataset but increases the processing time. A value of -1 will compute the footprint at the original resolution.
Minimum region size (pixels)
Avoid small holes in the imagery when using pixel values to create a mask. For example, the imagery may have a range of values from 0 to 255, and to mask clouds, you've excluded values from 245 to 255, which may cause other, noncloud pixels to be masked as well. If those areas are smaller than the number of pixels specified here, they will not be masked out.
Minimum thinness ratio
Define the thinness of slivers on a scale from 0 to 1.0 in which 1.0 represents a circle and 0.0 represents a polygon that approaches a straight line.
Polygons that are below both the Maximum sliver size and Minimum thinness ratio values will be removed from the footprint.
Maximum sliver size
Identify all polygons that are smaller than the square of this value. The value is specified in pixels and is based on the Request size value, not the spatial resolution of the source raster.
Polygons that are below both the Maximum sliver size and Minimum thinness ratio values will be removed from the footprint.
- Click Run.
Build overviews
Overviews are lower-resolution images created to increase display speed and reduce CPU usage when viewing the image collection at a larger (zoomed-out) scale. To build overviews for a hosted imagery layer published with an image collection, complete the following steps:
- Sign in to your organization and open the item page for the image collection imagery layer.
Sign in as the layer owner or a member of the default administrator role.
- Click the Image Management tab, and click the Build Overviews button.
- Click Run.
Compute seamlines
Seamlines control the mosaic boundary of the input images in an imagery layer. When input images overlap, you can use seamlines to define and control how the input images are blended and used to avoid sharp changes in the mosaicked imagery. To compute seamlines, complete the following steps:
- Sign in to your organization and open the item page for the image collection imagery layer.
Sign in as the layer owner or a member of the default administrator role.
- Click the Image Management tab, and click the Compute Seamlines button.
- For Seamline computation method, choose one of the following:
Radiometry
Based on spectral patterns of features in the imagery
Geometry
Based on the intersection of footprints
Edge detection
Based on edges of features in the area
Disparity
Based on the disparity images of stereo pairs
Voronoi
Based on the area Voronoi diagram
- Provide the Seamline blend width value and define the units.
- Optionally, click Show more settings and modify one or more of the following:
Minimum region size
Any seamline polygons smaller than this specified threshold will be removed in the seamline result.
Blend type
Define how many pixels will be blended relative to the seamline.
Request size
Specify the number of columns and rows for downsampling the imagery used to determine the seamlines.
Minimum thinness ratio
Define how thin a polygon can be before it is considered a sliver.
Maximum sliver size
Specify the maximum size a polygon can be to still be considered a sliver.
- Click Run.
Compute color corrections
To balance and color correct variations among input images to improve the visual mosaic, complete the following steps:
- Sign in to your organization and open the item page for the image collection imagery layer.
Sign in as the layer owner or a member of the default administrator role.
- Click the Image Management tab, and click the Compute Color Corrections button.
- For Color balance method, choose one of the following:
Dodging
Change each pixel's value toward a target color. This option requires choosing the type of target color. Dodging tends to provide the best result in most cases.
Histogram
Change each pixel's value according to its relationship with the histogram of a referenced image.
Standard deviation
Change each pixel's values according to its relationship with the histogram of the target raster, within one standard deviation.
- If you chose Dodging in the previous step, specify the Color balancing (dodging) surface type value. Choose one of the following:
Single color
Use when there are only a small number of images and a few different types of ground features.
Color grid
Use when you have a large number of images or images containing a large number of diverse ground objects.
First order
Use to create a smoother color change. This option can take longer to process, as all pixels are altered toward the target colors from a two-dimensional polynomial parabolic surface.
Second order
Use to create a smoother color change. This option can take longer to process, as all pixels are altered toward a set of multiple target colors from a two-dimensional polynomial parabolic surface.
Third order
Use to create a smoother color change. This option can take longer to process, as all pixels are altered toward multiple target colors obtained from the cubic surface.
- Optionally, click Show more settings and check Recalculate statistics to recalculate the statistics of the color-corrected images.
You can set Number of rows to skip and Number of columns to skip to control the portion of the image that is used to calculate the statistics.
- Click Run.
Calculate statistics
Statistics are required for imagery to perform certain tasks, such as applying a contrast stretch or classifying data. Calculating statistics allows a better display. To calculate statistics for the images published as an image collection, complete the following steps:
- Sign in to your organization and open the item page for the image collection imagery layer.
Sign in as the layer owner or a member of the default administrator role.
- Click the Image Management tab, and click the Calculate Statistics button.
- Optionally, modify one or more of the following:
Number of rows to skip
The number of vertical pixels between pixel samples. This value controls the portion of each image that is used when calculating the statistics. A value of 1 uses every pixel in each column, and a value of 10 uses every tenth pixel.
Number of columns to skip
The number of horizontal pixels between pixel samples. This value controls the portion of each image that is used when calculating the statistics. A value of 1 uses every pixel in each row, and a value of 10 uses every tenth pixel.
Ignore values
The pixel values that are not to be included in the statistics calculation.
- Click Run.
Define NoData pixel values
You can specify one or more values to be represented as NoData in the image collection. NoData values can be used to define pixel values that surround an image or to set transparent values. To set NoData values for the images published as an image collection, complete the following steps:
- Sign in to your organization and open the item page for the image collection imagery layer.
Sign in as the layer owner or a member of the default administrator role.
- Click the Image Management tab, and click the Define NoData Pixel Values button.
- Provide an integer pixel value for the NoData pixel value parameter.
Alternatively, check the Define valid pixel value range check box to specify a minimum and maximum valid pixel value. Any pixel value that falls outside of the valid range will be set as NoData.
- Optionally, if you are working with multi-band imagery, check A pixel represents a void only when the NoData criteria is met for all bands.
- Checked (default)—If a pixel is classified as NoData in all bands, classify that pixel as NoData in the multiband imagery layer.
- Unchecked—If that pixel is classified as NoData in any band, classify that pixel as NoData in the multiband imagery layer.
- Click Run.