MinimumDistanceClassification Task

This task performs a Minimum Distance supervised classification. Minimum Distance uses the mean vectors for each class and calculates the Euclidean distance from each unknown pixel to the mean vector for each class. The pixels are classified to the nearest class.

Example

; Start the application

e = ENVI()

; Open an input raster and vector

File = Filepath('qb_boulder_msi', Subdir=['data'], $

Root_Dir=e.Root_Dir)

Raster = e.OpenRaster(File)

File2 = Filepath('qb_boulder_msi_vectors.shp', Subdir=['data'], $

Root_Dir=e.Root_Dir)

Vector = e.OpenVector(File2)

; Get training statistics

StatTask = ENVITask('TrainingClassificationStatistics')

StatTask.INPUT_RASTER = Raster

StatTask.INPUT_VECTOR = Vector

StatTask.Execute

; Get the task from the catalog of ENVITasks

Task = ENVITask('MinimumDistanceClassification')

; Define inputs

Task.INPUT_RASTER = Raster

Task.MEAN = StatTask.Mean

Task.STDDEV = StatTask.STDDEV

; Run the task

Task.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, Task.OUTPUT_RASTER

; Display the result

View = e.GetView()

Layer = View.CreateLayer(Task.OUTPUT_RASTER)

Syntax

Result = ENVITask('MinimumDistanceClassification')

Input parameters (Set, Get): CLASS_COLORS, CLASS_NAMES, INPUT_RASTER, MEAN, OUTPUT_RASTER_URI, OUTPUT_RULE_RASTER_URI, STDDEV, THRESHOLD_MAX_DISTANCE, THRESHOLD_STDEV

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 RGB triplets representing the class colors as defined by the input vector.

CLASS_NAMES (optional)

This is a string array of class names as defined by the input vector.

INPUT_RASTER (required)

Specify a raster on which to perform supervised classification.

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.

If you do not specify this parameter, the OUTPUT_RASTER will not be created.
If you set this parameter to an asterisk symbol (*), the OUTPUT_RASTER will be virtual and not written to disk.
To force the creation of a temporary file, set this parameter to an exclamation symbol (!).
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.

OUTPUT_RULE_RASTER_URI (optional)

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

If you do not specify this parameter, the OUTPUT_RULE_RASTER will not be created.
To force the creation of a temporary file set the parameter to an exclamation symbol (!).
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.

STDDEV (optional)

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

THRESHOLD_MAX_DISTANCE (optional)

Specify a value that applies to all classes, or an array of values, one for each class. The smaller the threshold value, the more pixels will be unclassified.

THRESHOLD_STDDEV (optional)

Specify the number of standard deviations to use around the mean for all classes, or specify an array of values, one for each class. Enter a pixel value between 0 and 10000000. ENVI does not classify pixels outside this range. The lower the value, the more pixels that are unclassified.