This task performs the Mixture Tuned Target-Constrained Interference-Minimized Filter (MTTCIMF) target analysis.

Example


This example performs the following steps:

  • Opens an AVIRIS hyperspectral image subset.

  • Runs a forward minimum noise transform (MNF) to reduce noise in the data.

  • Defines three regions of interest (ROIs), each containing nine pixels of a common material.

  • Retrieves the spectra from the ROIs and uses their means as targets for Mixture Tuned Target-Constrained Interference-Minimized Filter.

  • Runs the MTTCIMF task, which performs mixture tuned target-constrained interference-minimized filtering.

  • Displays the result. To see all of the bands, open the Data Manager.

 
; Start the application
e = ENVI()
 
; Open an input file
File = Filepath('AVIRISReflectanceSubset.dat', $
  SUBDIR=['data', 'hyperspectral'], $
  ROOT_DIR=e.Root_Dir)
Raster = e.OpenRaster(File)
 
; First run a Forward MNF on the data
Task = ENVITask('ForwardMNFTransform')
Task.INPUT_RASTER = Raster
Task.Execute
 
; Use the first 25 MNF bands to run MTTCIMF
Subset = ENVISubsetRaster(Task.OUTPUT_RASTER, BANDS=LINDGEN(25))
 
; Define three ROIs, each containing 9 pixels of a common material.
nSpectra = 9d
roi1 = ENVIROI(NAME='Green Field')
pixelAddr1 = [[77,182],[78,182],[79,182], $
  [77,183],[78,183],[79,183], $
  [77,184],[78,184],[79,184]]
roi1.AddPixels, pixelAddr1, SPATIALREF=Subset.SPATIALREF
 
roi2 = ENVIROI(NAME='Soil')
pixelAddr2 = [[386,285],[387,285],[388,285], $
  [386,286],[387,286],[388,286], $
  [386,287],[387,287],[388,287]]
roi2.AddPixels, pixelAddr2, SPATIALREF=Subset.SPATIALREF
 
roi3 = ENVIROI(NAME='Ground')
pixelAddr3 = [[296,326],[297,326],[298,326], $
  [296,327],[297,327],[298,327], $
  [296,328],[297,328],[298,328]]
roi3.AddPixels, pixelAddr3, SPATIALREF=Subset.SPATIALREF
 
; Retrieve the spectra from the ROIs and use their mean as targets
; for the Mixture Tuned Target-Constrained Interference-Minimized Filter (MTTCIMF) task
spectra1 = Subset.GetData(ROI=roi1)
mean1 = Total(spectra1,1) / nSpectra
spectra2 = Subset.Getdata(ROI=roi2)
mean2 = Total(spectra2,1) / nSpectra
spectra3 = Subset.GetData(ROI=roi3)
mean3 = Total(spectra3,1) / nSpectra
targets = [[mean1],[mean2],[mean3]]
 
; Get the task from the catalog of ENVITasks
Task = ENVITask('MixtureTunedTargetConstrainedInterferenceMinimizedFilter')
Task.INPUT_RASTER = Subset
Task.TARGET = targets
 
; Run the task
Task.Execute
 
; Get the data collection
dataColl = e.Data
 
; Add the output to the data collection
dataColl.Add, Task.OUTPUT_RASTER
 
; Display the result
View = e.GetView()
Layer = View.CreateLayer(Task.OUTPUT_RASTER)

Syntax


Result = ENVITask('MixtureTunedTargetConstrainedInterferenceMinimizedFilter')

Input parameters (Set, Get): BACKGROUND, BACKGROUND_THRESHOLD, COVARIANCE, INPUT_RASTER, NAMES, OUTPUT_RASTER_URI, REGULARIZATION_METHOD, REGULARIZATION_TOLERANCE, TARGET, USE_SUBSPACE_BACKGROUND

Output parameters (Get only): OUTPUT_RASTER

Parameters marked as "Set" are those that you can set to specific values. You can also retrieve their current values any time. Parameters marked as "Get" are those whose values you can retrieve but not set.

Input Parameters


BACKGROUND (optional)

Specify the background spectra. It is a floating-point array. The array size is [number of bands, number of background spectra]. If not defined, at least two target spectra are needed.

BACKGROUND_THRESHOLD (optional)

This is a float value indicating the fraction of the background in the anomalous image to use when calculating statistics using subspace background. It ranges from 0.500 to 1.000 (the entire image), with the default 0.9.

COVARIANCE (optional)

Specify an array that is the covariance matrix of the input bands. The array size must be [number of bands, number of bands].

INPUT_RASTER (required)

Specify an input raster to process.

NAMES (optional)

Specify an array of target names. The array size must be [number of targets].

OUTPUT_RASTER_URI (optional)

Specify a string with the fully qualified filename and path of the associated OUTPUT_RASTER.

  • If you do not specify this parameter, or set it to an exclamation symbol (!), ENVI creates a temporary file.
  • If you set it to the hash symbol (#), ENVI creates a file in the temporary directory, but this file will not be deleted when ENVI closes.

REGULARIZATION_METHOD (optional)

Specify a method for regularizing the autocorrelation matrix:

  • Diagonal: Diagonal loading, increasing all singular values by the tolerance value.
  • Dominant: Dominant mode rejection, setting singular values less than the tolerance value to their mean.
  • None: No regularization is used.
  • Shrink: Shrinkage of singular values based on the tolerance value.
  • Threshold: Singular values less than the tolerance value are set to the tolerance value.
  • Truncate (default): Singular values less than the tolerance value are set to zero.

REGULARIZATION_TOLERANCE (optional)

Specify the tolerance value to use for matrix regularization. If not set, the following values will be used based on the regularization method

  • Diagonal: Ten times the smallest nonzero singular value.
  • Dominant: The value prescribed by Gavish & Donoho.
  • None: N/A
  • Shrink: The Oracle Approximating Shrinkage (OAS) estimator.
  • Threshold: The largest singular value times the machine precision.
  • Truncate (default): The largest singular value times the machine precision.

TARGET (required)

Specify the target spectra. It is a floating-point array. The array size is [number of bands, number of target spectra].

USE_SUBSPACE_BACKGROUND (optional)

Specify whether to use subspace background in statistics calculation.

Output Parameters


OUTPUT_RASTER

This is a reference to the output raster of filetype ENVI.

Methods


Execute

Parameter

ParameterNames

Properties


DESCRIPTION

DISPLAY_NAME

NAME

REVISION

TAGS

Version History


ENVI 6.0

Introduced

ENVI 6.2

Added the NAMES, REGULARIZATION_METHOD, and REGULARIZATION_TOLERANCE parameters.

See Also


ENVITask