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Sieve Classes

Sieve Classes

Use Sieve Classes to solve the problem of isolated pixels occurring in classification images. Sieving classes removes isolated classified pixels using blob grouping. Low pass or other types of filtering could be used to remove these areas, but the class information would be contaminated by adjacent class codes. The sieve classes method looks at the neighboring 4 or 8 pixels to determine if a pixel is grouped with pixels of the same class. If the number of pixels in a class that are grouped is less than the value that you enter, those pixels will be removed from the class. When pixels are removed from a class using sieving, black pixels (unclassified) will be left.

Tip: Use the Clump Classes function after sieving to replace the black pixels.

You can also write a script to perform classification sieving using the ENVIClassificationSievingTask routine.

  1. From the Toolbox, select Classification > Post Classification > Sieve Classes. The Classification Input File dialog appears.
  2. Select an input file, perform any optional spatial subsetting, and then click OK to display the Classification Sieving dialog. Sieving can only be performed on classification images, identified by a file type of "ENVI Classification" in the image header file.
  3. Choose 4 or 8 from the Pixel Connectivity drop-down list. This option specifies the number of neighboring pixels (4 or 8) to look at when determining the number of pixels in a class group. The four-neighbor region around a pixel consists of the two adjacent horizontal and two adjacent vertical neighbors. The eight-neighbor region around a pixel consists of all the immediately adjacent pixels.
  4. Use the Class Order list to identify which classes will have sieving applied. Classes may be added, removed or reordered. If no changes are made, all classes have sieving applied and are processed from first to last.
  5. Specify a Minimum Size to determine the minimum size of a blob grouping to keep. A value of 2 is used unless otherwise specified.
  6. Use Output Raster to specify an output location and filename.
  7. Click OK.

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