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Parallelepiped

Parallelepiped

Parallelepiped classification uses a simple decision rule to classify multispectral data. The decision boundaries form an n-dimensional parallelepiped classification in the image data space. The dimensions of the parallelepiped classification are defined based upon a standard deviation threshold from the mean of each selected class. If a pixel value lies above the low threshold and below the high threshold for all n bands being classified, it is assigned to that class. If the pixel value falls in multiple classes, ENVI assigns the pixel to the first class matched. Areas that do not fall within any of the parallelepiped classes are designated as unclassified.

Reference: Richards, J. Remote Sensing Digital Image Analysis, Berlin: Springer-Verlag (1999), 240 pp.

  1. Use the ROI Tool to define training regions for each class. The more pixels and classes, the better the results will be.
  2. Use the ROI Tool to save the ROIs to an .roi file.
  3. Display the input file you will use for Parallelepiped classification, along with the ROI file.
  4. Select one of the following:
    • From the Toolbox, select Classification > Supervised Classification > Parallelepiped Classification.
    • From the Endmember Collection dialog menu bar, select Algorithm > Parallelepiped. Click Apply.
    • The Classification Input File dialog appears.

  5. Select an input file and perform optional spatial and spectral subsetting, and/or masking, then click OK. The Parallelepiped Parameters dialog appears.

  6. In the Select Classes from Regions list, select ROIs and/or vectors as training classes. The ROIs listed are derived from the available ROIs in the ROI Tool dialog. The vectors listed are derived from the open vectors in the Available Vectors List.
  7. Select one of the following thresholding options from the Set Max stdev from Mean area:
    • None: Use no standard deviation threshold.
    • Single Value: Use a single threshold for all classes. Enter a value in the Max stdev from Mean field to designate the number of standard deviations to use around the mean.
    • Multiple Values: Enter a different threshold for each class. Use this option as follows:
    1. In the list of classes, select the class or classes to which you want to assign different threshold values and click Multiple Values. The Assign Max stdev from Mean dialog appears.
    2. Select a class, then enter a threshold value in the field at the bottom of the dialog. Repeat for each class. Click OK when you are finished.
    3. Select classification output to File or Memory.
  8. Use the Output Rule Images? toggle button to select whether or not to create rule images. Use rule images to create intermediate classification image results before final assignment of classes. You can later use rule images in the Rule Classifier to create a new classification image without having to recalculate the entire classification.
  9. If you selected Yes to output rule images, select output to File or Memory.
  10. Click Preview to see a 256 x 256 spatial subset from the center of the output classification image. Change the parameters as needed and click Preview again to update the display.
  11. Click OK. ENVI adds the resulting output to the Layer Manager. The pixel values of the resulting rule images range from 0 to n (where n is the number of bands) and represent the number of bands that satisfied the parallelepiped criteria. There is one rule image for each selected class. Areas that match all bands for a particular class are carried over as classified areas into the classified image. If more than one match occurs, the first class to evaluate (the first ROI from the selected list) carries over into the classified image.

Previewing the Output Classification Image


Click Preview in the Parameters dialog to open a preview window within the dialog. The preview window in the Parameters dialog allows you to quickly see a 256 x 256 spatial subset from the center of the output classification image. You can adjust your classification parameters and update the preview window to determine how these changes affect the resulting classification.

Below the preview window is a Change View button and a label describing the x and y pixel ranges of the spatial subset. Clicking the Change View button initiates a Select Spatial Subset dialog, where you can modify the location of the spatial subset interactively or by using a specified value.

For SAM classification, the preview window is only available after you click Apply in the Endmember Collection dialog.



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