Recomputing footprints to remove unwanted pixel data

The Recompute Footprint By Radiometry option redefines the shape of the footprint based on a pixel value range. This option is generally used to redefine footprints so that they exclude border areas, which do not define valid data. Such border areas that are mostly in black or white occur on rotated raster datasets or scenes that were rectified, but not mosaicked. The footprint is redefined based on the radiometry of the border pixel value. This computation is performed at the image service definition level. You can use the Recompute Footprint By Radiometry option to remove unwanted pixels, which is much more efficient than using transparency. For NoData areas with different colors other than black and white, you will have to apply a Classify Pixel process, then use the Recompute Footprint By Radiometry option to remove the NoData areas. See About using transparency in an image service definition on how to remove such NoData areas.

The Recompute Footprint By Radiometry dialog box has two tabs: General and Advanced. The values set on the General tab will redefine the advanced parameters that are used by this process. The following Image type and Image compression options are provided on the General tab.

The image type options define various types of datasets that sometimes have NoData borders. The Image type options are as follows:

• Regular and clipped to sheets—Used for datasets where the data pixels in each image form a rotated rectangular area. The resulting imagery will be clipped to a new sheet or tile. Such datasets are typically created by reprojection of images or scenes, then cut to map sheets or tiles with little or no overlap. The parameters are set such that the footprint will contain only a few vertices. An analysis of the edges is performed to maintain the sheet or tile boundaries.
• Irregular and clipped to sheets—Used for datasets where the data pixels do not form rectangular areas. The resulting imagery can be cut into map sheets or tiles. Such datasets are typical for imagery along pipelines or other linear features. Here the pixel areas cover the linear feature, and the images are then mosaicked and cut into tiles. The parameters are set to allow larger numbers of vertices to define the border. An analysis of the edges of the resulting footprint is performed to maintain the sheet or tile boundaries.
• Rotated rectangle—Used for images that form a rotated rectangle. Such datasets are typically created when individual scenes or map sheets have been rotated and the sides of the footprint remain straight. The parameters are set to define the footprint only by four vertices.
• Reprojected rectangle—Used for rotated images that have been reprojected, which form rectangular footprints with curved edges. Such datasets are typically created when individual scenes or map sheets have been reprojected. The parameters are set to define the footprint with sufficient numbers of vertices to represent the curves.
• Orthorectified image in flat terrain—Used when the origin of the raster dataset is a scene or image that has been orthorectified to a flat terrain. The edges of such images form simple curves caused by smooth changes in the elevation.
• Orthorectified image in hilly terrain—Used when the raster dataset is being orthorectified in an area that encounters large changes in elevation. The edges of such images are irregular and caused by sudden changes in the elevation. More vertices are required to define such footprints.

The image compression options are as follows:

• Noncompressed imagery—Used with raster datasets that have not been uncompressed
• Lossy compressed imagery—Used with lossy compressed raster datasets, using compressions such as MrSID or JPEG

The values you set in the General tab will automatically update the appropriate values in the Advanced tab. You can also review and redefine the values to improve the results. The following parameters can be set using the Advanced tab:

• Image resolution—Approximate number of rows and columns extracted from the service to create a new footprint polygon. You can increase or decrease this value based on the complexity of your raster data. Greater image resolution provides more detail in the raster dataset and thereby increases the processing time.
• Approximate number of vertices—Approximate number of vertices with which the new footprint polygon will be created. The greater this value, the more accurate and irregular the polygon and the longer the processing time.
• Minimum data value—Lowest value representing valid image data. Any value less than this value will be considered NoData. A value around 0 represents very dark colors, like black border pixels. When you specify 1, it defines that only black (0) will be considered as NoData. If the imagery is compressed using a lossy compression method, setting a value greater than 1 will consider black as NoData. For dark areas, such as shadows that have been incorrectly defined as NoData, this value should be decreased.
• Maximum data value—Highest value representing valid data. Any value greater than this value will be considered NoData. A value around 255 represents very bright colors in an 8-bit raster dataset, such as white clouds and snow. If white areas such as snow or cloud are incorrectly defined as NoData, then this value should be increased.
• Shrink distance—Number of units by which the overall polygon will be reduced in size. Shrinking of the polygon is used to counteract effects of lossy compression, which causes the edge of the image to overlap into NoData areas.
• Shrink distance unit—Shrinks the footprint distance by Pixel, Meter, or Percent units. Shrinking by pixel ensures that the extreme edges of an image are not seen. Shrinking by meter is used for satellite or aerial imagery where a specific edge of the image needs to be excluded. Shrinking by percent is used for aerial photography that has a large amount of overlap that needs to be reduced.
• Maintain sheet edges—Check when using raster datasets that have been tiled and are butt-joined (or line up along the seams with little to no overlap). An analysis of the image edges is performed so that the sheet edges are not removed by setting a shrink distance.
• Skip derived images—If checked, any derived images, such as service overviews, will not be adjusted. If unchecked, the footprints of any derived images will be adjusted.

手順:

1. Open an existing image service definition or use one that is already open in ArcMap.
2. Optionally, select the raster to be processed.

   Learn more about selecting footprints

3. Right-click the Footprint layer in the table of contents and click Recompute Footprint → By Radiometry.

   The Recompute Footprint By Radiometry dialog box is displayed with default values for each of the parameters.

4. Click the Image type drop-down arrow and click an option.
5. Click the Image compression drop-down arrow and click to select Noncompressed imagery or Lossy compressed imagery.
6. Optionally, click the Advanced tab and make changes to the parameters.
7. Click OK.

注意:

This operation is performed on the data at the image service definition level. You can also recompute the footprint of an image service after applying processes. For example, If the NoData value does not conform to black or white, you may need to apply the Classify Pixel process on an image service before recomputing the footprints, which can be removed later.

注意:

For images with alpha channel bands, you can use the Recompute Footprint By Radiometry option to display alpha channel bands as NoData.

ヒント:

The Shrink Footprint feature can be used to reduce the footprints to a greater extent.