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.

Follow these steps:

  1. From the Toolbox, select Classification > Supervised Classification > Minimum Distance Classification. The Minimum Distance Classification dialog appears.
  2. Select an Input Raster and perform optional spatial and spectral subsetting, and/or masking.
  3. Select the Input ROIs that represent the classes. Statistics from the ROIs are used as input to the Minimum Distance calculation.
  4. Optional: In the Threshold Maximum Distance field, specify a pixel value between 0 and 10000000 that applies to all classes, or specify an array of pixel values, one for each class. The number of array elements must equal the number the number of classes. This value represents a distance threshold. The smaller the threshold, the more pixels that are unclassified. The pixel of interest must be within both the threshold for distance to mean and the threshold for the standard deviation for a class. The condition for Minimum Distance reduces to the lesser of the two thresholds. A higher value for each parameter is more inclusive because more pixels are included in a class for a higher threshold.
  5. Optional: In the Threshold Standard Deviation field, specify the number of standard deviations to use around the mean for all classes, or specify an array of values, one for each class. Enter a pixel value between 0 and 10000000. ENVI does not classify pixels outside this range. The lower the value, the more pixels that are unclassified.
  6. Optional: Specify a filename and location for the Output Rule Raster. A rule raster is a greyscale image that shows intermediate classification results, where each band represents a rule raster for each class. With Minimum Distance classification, pixel values represent the Euclidean distance from the class mean.
  7. Specify a filename and location for the Output Raster (the classification raster).
  8. Enable the Display result check box to display the output rule raster and/or output rule raster in the Image window when processing is complete. Otherwise, if the check box is disabled, the raster can be loaded from the Data Manager.
  9. Enable the Preview check box to see a preview of the settings before you click OK to process the data. The preview is calculated only on the area in the Image window. See Preview for details on the results. To preview a different area in your image, pan and zoom to the area of interest and reenable the Preview option.
  10. To run the process on a local or remote ENVI Server, click the down arrow and select Run Task in the Background or Run Task on remote ENVI Server name. The ENVI Server Job Console will show the progress of the job and will provide a link to display the result when processing is complete. See the ENVI Servers topic for more information.

  11. Optional: Click Open in Modeler to see a model-based version of this tool that shows how the tool is constructed from individual tasks.
  12. Click OK. ENVI adds the resulting output to the Data Manager and, if the Display Result check box was enabled, adds the layer to the Layer Manager and displays the output in the Image window.