Adaptive Coherence Estimator Classification

Adaptive Coherence Estimator (ACE) is derived from the Generalized Likelihood Ratio (GLR) approach. The ACE is invariant to relative scaling of input spectra and has a Constant False Alarm Rate (CFAR) with respect to such scaling. Similar to Constrained Energy Minimization (CEM) and Matched Filtering (MF), ACE does not require knowledge of all the endmembers within an image scene.

You can also write a script to perform ACE target detection using the SpectralAdaptiveCoherenceEstimator task.

  1. From the Toolbox, select Classification > Supervised Classification > Adaptive Coherence Estimator Classification. The Adaptive Coherence Estimator Classification dialog appears.
  2. Select an Input Raster and perform optional spatial and spectral subsetting, and/or masking.
  3. Select the Input ROIs file that represents the classes. Statistics from the ROIs are used as input to the Adaptive Coherence Estimator calculation.
  4. Specify a filename and location for the Output Raster (the classification raster).
  5. 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 view and uses the resolution level at which you are viewing the image. See Preview for details on the results. To preview a different area in your image, pan and zoom to the area of interest and re-enable the Preview option.
  6. Enable the Display result check box to display the output in the view when processing is complete. Otherwise, if the check box is disabled, the result can be loaded from the Data Manager.

  7. To see a model-based version of this tool that shows how the tool is constructed from individual tasks, click Open in Modeler.

  8. To reuse these task settings in future ENVI sessions, save them to a file. Click the down arrow and select Save Parameter Values, then specify the location and filename to save to. Note that some parameter types, such as rasters, vectors, and ROIs, will not be saved with the file. To apply the saved task settings, click the down arrow and select Restore Parameter Values, then select the file where you previously stored your settings.

  9. To run the process in the background, click the down arrow and select Run Task in the Background. If an ENVI Server has been set up on the network, the Run Task on remote ENVI Server name is also available. 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 ENVI Servers for more information.

  10. To see a model-based version of this tool that shows how the tool is constructed from individual tasks, click Open in Modeler.

  11. Click OK.

The results of ACE 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.