Orthogonal Subspace Projection (OSP) first designs an orthogonal subspace projector to eliminate the response of non-targets, then Matched Filter is applied to match the desired target from the data. OSP is efficient and effective when target signatures are distinct. When the spectral angle between the target signature and the non-target signature is small, the attenuation of the target signal is dramatic and the performance of the OSP could be poor.

  1. From the Toolbox, select Classification > Supervised Classification > Orthogonal Subspace Projection Classification. The Orthogonal Subspace Projection Input File dialog appears.
  2. Select the input file and perform optional spatial and spectral subsetting, then click OK. The Endmember Collection:OSP dialog appears.
  3. Import spectra to match. For details, see Endmember Options and Manage Endmember Spectra.
  4. Click Apply. The Orthogonal Subspace Projection Parameters dialog appears.
  5. Select output to File or Memory.
  6. Click OK.

Orthogonal Subspace Projection Results

The results of OSP appear as a series of gray scale images, one for each selected endmember.

The default stretch setting provides good visibility for small features. If needed, you can apply a different stretch so that larger features in the image are visible.

Note: You can set a default stretch range so that you do not have to stretch the data each time they are displayed.