SpectralInformationDivergenceClassification Task

This task performs the Spectral Information Divergence (SID) classification.

Example

This example performs the following steps:

; 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 15 MNF bands to run SID

Subset = ENVISubsetRaster(Task.OUTPUT_RASTER, BANDS=LINDGEN(15))

 

; 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 Spectral Information Divergence (SID) 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

means = [[mean1],[mean2],[mean3]]

 

; Get the task from the catalog of ENVITasks

Task = ENVITask('SpectralInformationDivergenceClassification')

Task.INPUT_RASTER = Subset

Task.MEAN = means

 

; 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('SpectralInformationDivergenceClassification')

Input parameters (Set, Get): CLASS_COLORS, CLASS_NAMES, INPUT_RASTER, MEAN, OUTPUT_RASTER_URI, OUTPUT_RULE_RASTER_URI, THRESHOLD

Output parameters (Get only): OUTPUT_RASTER, OUTPUT_RULE_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

CLASS_COLORS (optional)

This is an array of [3, number of classes] for RGB triplets representing the class colors.

CLASS_NAMES (optional)

This is an array of [number of classes] for unclassified and class names.

INPUT_RASTER (required)

Specify an input raster to process.

MEAN (required)

Specify an array that is [number of bands, number of classes].

OUTPUT_RASTER_URI (optional)

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

OUTPUT_RULE_RASTER_URI (optional)

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

THRESHOLD (required)

Specify a maximum value or array of maximum values (one for each class) for each class is tested against its corresponding maximum spectral divergence. The default value is 0.05.

Output Parameters

OUTPUT_RASTER

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

OUTPUT_RULE_RASTER

This is a reference to the output rule image of filetype ENVI.

This output will not be generated unless its associated URI input parameter is set.

Methods

Execute

Parameter

ParameterNames

Properties

DESCRIPTION

DISPLAY_NAME

NAME

REVISION

TAGS

Version History

ENVI 6.0

Introduced

See Also

ENVITask, Masking Support in ENVITasks