This task performs a clumping method on a classification image. This operation clumps adjacent similar classified areas using morphological operators. Classified images often suffer from a lack of spatial coherency (speckle or holes in classified areas). Low pass filtering could be used to smooth these images, but the class information would be contaminated by adjacent class codes. Clumping classes solves this problem. The selected classes are clumped together by first performing a dilate operation then an erode operation on the classified image using one specified kernel (structuring element) for each operation.

Example


The following example performs an unsupervised classification, followed by a sieving, then clumping operation to remove the remaining black pixels.

; Start the application
e = ENVI()
 
; Open an input file
File = Filepath('qb_boulder_msi', Subdir=['data'], $
  Root_Dir=e.Root_Dir)
Raster = e.OpenRaster(File)
 
; Create a classification ENVIRaster
ClassTask = ENVITask('ISODATAClassification')
ClassTask.INPUT_RASTER = Raster
ClassTask.Execute
 
; Get the collection of data objects currently available in the Data Manager
DataColl = e.Data
 
; Add the class image to the Data Manager
DataColl.Add, ClassTask.OUTPUT_RASTER
 
; Display the result
View = e.GetView()
Layer = View.CreateLayer(ClassTask.OUTPUT_RASTER)
 
; Run the sieving task
SievingTask = ENVITask('ClassificationSieving')
SievingTask.INPUT_RASTER = ClassTask.OUTPUT_RASTER
SievingTask.Execute
 
; Run the clumping task
ClumpingTask = ENVITask('ClassificationClumping')
ClumpingTask.INPUT_RASTER = SievingTask.OUTPUT_RASTER
ClumpingTask.Execute
 
; Add the output to the Data Manager
DataColl.Add, ClumpingTask.OUTPUT_RASTER
 
; Display the result
Layer2 = View.CreateLayer(ClumpingTask.OUTPUT_RASTER)
 
; Flicker between the original classification and the result
; after clumping
Portal = View.CreatePortal()
Portal.Animate, 2.0, /FLICKER

Syntax


Result = ENVITask('ClassificationClumping')

Input parameters (Set, Get): CLASS_ORDER, DILATE_KERNEL, ERODE_KERNEL, INPUT_RASTER, OUTPUT_RASTER_URI

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


CLASS_ORDER (optional)

Specify the order of class names in which clumping is applied to the classification image. If you do not specify this parameter, the classes are processed from first to last.

DILATE_KERNEL (required)

Specify a 2D array of zeros and ones that represents the structuring element (kernel) used for a dilate operation. If no kernel is specified, a 3 x 3 array will be used with a value of 1 for all of the array elements. Dilation is a morphological operation that uses a structuring element to expand the shapes contained in the input image.

ERODE_KERNEL (required)

Specify a 2D array of zeros and ones that represents the structuring element (kernel) used for a erode operation. If no kernel is specified, a 3 x 3 array will be used with a value of 1 for all of the array elements. Erosion is a morphological operation that uses a structuring element to reduce the shapes contained in the input image.

INPUT_RASTER (required)

Specify a raster on which to perform classification clumping.

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.

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 5.2.1

Introduced

See Also


ENVITask, ENVISubsetRaster, ISODATAClassification Task, ClassificationSmoothing Task, ClassificationAggregation Task, ClassificationSieving Task