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Minimum Distance

Minimum Distance

The minimum distance technique uses the mean vectors of each endmember and calculates the Euclidean distance from each unknown pixel to the mean vector for each class. All pixels are classified to the nearest class unless a standard deviation or distance threshold is specified, in which case some pixels may be unclassified if they do not meet the selected criteria.

Reference: Richards, J.A. 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 Minimum Distance classification, along with the ROI file.
  4. Select one of the following:
    • From the Toolbox, select Classification > Supervised Classification > Minimum Distance Classification.
    • From the Endmember Collection dialog menu bar, select Algorithm > Minimum Distance and 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 Minimum Distance 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.

    Minimum Distance requires at least two regions.

  7. Select one of the following thresholding options each from the Set Max stdev from Mean and/or Set Max Distance Error areas.
  8. If you are running the Minimum Distance Classification from within the Endmember Collection dialog, the Max Stdev from Mean area is not available.

    • None: Use no standard deviation threshold.
    • Single Value: Use a single threshold for all classes. Enter a value in the Max stdev from Mean and/or Set Max Distance Error fields. For Max stdev from Mean, enter the number of standard deviations to use around the mean. ENVI does not classify pixels outside this range. For Max Distance Error, enter the value in DNs. ENVI does not classify pixels at a distance greater than this value.

    If you set values for both Set Max stdev from Mean and Set Max Distance Error, the classification uses the smaller of the two to determine which pixels to classify. If you select None for both parameters, then ENVI classifies all pixels.

    • 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 Distance Error 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.

  9. Select classification output to File or Memory.
  10. 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.
  11. If you selected Yes to output rule images, select output to File or Memory.
  12. 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.
  13. Click OK. ENVI adds the resulting output to the Layer Manager. If you selected to output rule images, ENVI creates one for each class with the pixel values equal to the Euclidean distance from the class mean. Areas that satisfied the minimum distance criteria are carried over as classified areas into the classified image.

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