SpectralAdaptiveCoherenceEstimatorUsingSubspaceBackgroundStatistics Task

This task performs Adaptive Coherence Estimator (ACE) target detection analysis, using the mean and covariance from subspace background statistics.

Example

ACE target detection involves multiple steps, as this code example demonstrates:

Open a spectral library.
Open a hyperspectral image.
Get the wavelength values and units from the image.
Choose an individual spectrum from the spectral library.
Resample the spectrum to the wavelengths of the image.
Compute subspace background statistics.
Run ACE target detection.
Display the resulting image. Brighter pixels represent a close match to the Dry Grass spectrum.

This example takes several minutes to complete. Copy and paste the following code into the IDL Editor:

; Launch the application

e = ENVI()

; Open a spectral library

specLibFile = FILEPATH('veg_2grn.sli', ROOT_DIR=e.ROOT_DIR, $

SUBDIR=['resource', 'speclib', 'veg_lib'])

specLib = ENVISpectralLibrary(specLibFile)

; Open a hyperspectral image

file = FILEPATH('AVIRISReflectanceSubset.dat', $

ROOT_DIR=e.ROOT_DIR, $

SUBDIRECTORY = ['data', 'hyperspectral'])

raster = e.OpenRaster(file)

; Get wavelength values and units from raster

metadata = raster.METADATA

wavelengths = metadata['Wavelength']

wavelengthUnits = metadata['Wavelength Units']

; Get the selected spectrum from spectral library

Task1 = ENVITask('GetSpectrumFromLibrary')

Task1.INPUT_SPECTRAL_LIBRARY = specLib

Task1.SPECTRUM_NAME = 'Dry Grass'

Task1.Execute

; Get the resample spectrum task from the catalog of ENVITasks

Task2 = ENVITask('ResampleSpectrum')

; Define inputs

; Spectrum from library to be resampled

Task2.INPUT_SPECTRUM = Task1.SPECTRUM

; Wavelengths from spectral library

Task2.INPUT_WAVELENGTHS = Task1.WAVELENGTHS

; Wavelength units from spectral library

Task2.INPUT_WAVELENGTH_UNITS = Task1.WAVELENGTH_UNITS

; Wavelengths from raster

Task2.RESAMPLE_WAVELENGTHS = wavelengths

; Wavelength units from raster

Task2.RESAMPLE_WAVELENGTH_UNITS = wavelengthUnits

; Run the resample spectrum task

Task2.Execute

; Get the ACE task from the catalog of ENVITasks

ACETask = ENVITask('SpectralAdaptiveCoherenceEstimatorUsingSubspaceBackgroundStatistics')

; Define inputs

ACETask.INPUT_RASTER = raster

ACETask.SPECTRA = Task2.OUTPUT_SPECTRUM

ACETask.THRESHOLD = 0.6

; Run the task

ACETask.Execute

; Get the collection of data objects currently available in the Data Manager

DataColl = e.Data

; Add the output to the Data Manager

DataColl.Add, ACETask.OUTPUT_RASTER

; Display the result

View = e.GetView()

Layer = View.CreateLayer(ACETask.OUTPUT_RASTER)

Syntax

Result = ENVITask('SpectralAdaptiveCoherenceEstimatorUsingSubspaceBackgroundStatistics')

Input parameters (Set, Get): INPUT_RASTER, NAMES, OUTPUT_RASTER_URI, REGULARIZATION_METHOD, REGULARIZATION_TOLERANCE, SPECTRA, THRESHOLD

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

INPUT_RASTER (required)

Specify a raster on which to perform the target detection.

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 covariance 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.

SPECTRA (required)

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

THRESHOLD (optional)

Specify the fraction of the background to use for calculating the subspace background statistics. The data type is floating-point. The allowable range is 0.5 to 1.0 (the entire image).