This routine is obsolete and has been replaced by the ClassificationClumping and ClassificationSieving tasks.

Use this procedure to clump or sieve a classification image. The sieve operation uses a blob technique to eliminate all blobs smaller than the value set by the SIEVE_MIN keyword. The clump process uses the morphological operators dilate and erode.

Syntax

ENVI_DOIT, 'CLASS_CS_DOIT', DIMS=array, DKERN=value, /EIGHT, EKERN=value, FID=file ID, /IN_MEMORY, METHOD={0 | 1}, ORDER=value, OUT_BNAME=string array, OUT_NAME=string, POS=array, R_FID=variable, SIEVE_MIN=value

Keywords

DIMS

The “dimensions” keyword is a five-element array of long integers that defines the spatial subset (of a file or array) to use for processing. Nearly every time you specify the keyword FID, you must also specify the spatial subset of the corresponding file (even if the entire file, with no spatial subsetting, is to be processed).

  • DIMS[0]: A pointer to an open ROI; use only in cases where ROIs define the spatial subset. Otherwise, set to -1L.
  • DIMS[1]: The starting sample number. The first x pixel is 0.
  • DIMS[2]: The ending sample number
  • DIMS[3]: The starting line number. The first y pixel is 0.
  • DIMS[4]: The ending line number

To process an entire file (with no spatial subsetting), define DIMS as shown in the following code example. This example assumes you have already opened a file using ENVI_SELECT or ENVI_PICKFILE:

  envi_file_query, fid, dims=dims

DKERN

Use only with the clump method. This is the dilate kernel used for the classification clump. This kernel is passed to the IDL morphology procedures.

EIGHT

Use only with the sieve method. If you set this keyword, the sieve function searches the eight-neighbor region around a pixel, rather than the four-neighbor region, for continuous blobs. The four-neighbor region around a pixel consists of two adjacent horizontal and two adjacent vertical neighbors. The eight-neighbor region around a pixel consists of all the immediately adjacent pixels.

EKERN

Use only with the clump method. This is the erode kernel used for the classification clump. This kernel is passed to the IDL morphology routines.

FID

The file ID (FID) is a long-integer scalar with a value greater than 0. An invalid FID has a value of -1. The FID is provided as a named variable by any routine used to open or select a file. Often, the FID is returned from the keyword R_FID in the ENVIRasterToFID routine. Files are processed by referring to their FIDs. If you work directly with the file in IDL, the FID is not equivalent to a logical unit number (LUN).

IN_MEMORY

Set this keyword to specify that output should be stored in memory. If you do not set IN_MEMORY, output will be stored on disk and you must specify OUT_NAME (see below).

METHOD

Set this keyword to a value of 0 to use the clump method, or to 1 to use the sieve method.

ORDER

Use this keyword to specify the order in which clump or sieve is applied to the classification image. If you do not specify this keyword, the classes are processed from first to last.

OUT_BNAME

Use this keyword to specify a string array of output band names.

OUT_NAME

Use this keyword to specify a string with the output filename for the resulting data. If you set the keyword IN_MEMORY, you do not need to specify OUT_NAME.

POS

Use this keyword to specify an array of band positions, indicating the band numbers on which to perform the operation. This keyword indicates the spectral subset of bands to use in processing. POS is an array of long integers, ranging from 0 to the number of bands minus 1. Specify bands starting with zero (Band 1=0, Band 2=1, etc.) For example, to process only Bands 3 and 4 of a multi-band file, POS=[2, 3].

POS is typically used with individual files. The example code below illustrates the use of POS for a single file with four bands of data:

  pos=[0,1,2,3]
                  
envi_doit, 'envi_stats_doit', dims=dims, fid=fid, pos=pos, $
                  
comp_flag=3, dmin=dmin, dmax=dmax, mean=mean, stdv=stdv, hist=hist

But what if you need to create an output file consisting of data from different bands, each from different files? Library routines such as CF_DOIT and ENVI_LAYER_STACKING_DOIT can accomplish this, but they use the POS keyword differently. Suppose you have four files, test1, test2, test3, and test4, with corresponding FIDs of fid1, fid2, fid3, and fid4, respectively. In the following example, you want Band 3 from test1 in the first position, Band 2 from test2 in the second position, Band 6 from test3 in the third position, and Band 4 from test4 in the fourth position. The code should be as follows:

  fid_array = [fid1,fid2,fid3,fid4]
                  
pos=[2,1,5,3]
                  
envi_doit, 'cf_doit', dims=dims, fid=fid_array
                  
out_name='test_composite_file'

R_FID

ENVI Classic library routines that result in new images also have an R_FID, or “returned FID.” This is simply a named variable containing the file ID to access the processed data. Specifying this keyword saves you the step of opening the new file from disk.

SIEVE_MIN

Use only with the sieve method. Use this keyword to specify the minimum size of a blob to keep. All blobs smaller than this value will be removed. Set the EIGHT keyword to specify the pixel neighbors from which to build blobs.