Use this procedure to calculate a synthetic color image from a single gray scale band. This program uses a low-pass filter, high-pass filter, and a saturation value as inputs into an HSV transform to create a synthetic color image.


This example calculates the synthetic color for the first band. It displays the colored image inside a Standard Portal on top of the original image.

; Start ENVI
e = ENVI()
; Open a data file
File = Filepath('qb_boulder_msi', Root_Dir = e.Root_Dir, $
   Subdir = ['data'])
Raster = e.OpenRaster(File)
; Determine an output file
OutFile = e.GetTemporaryFilename()
; Return a file ID
fid = ENVIRasterToFID(Raster)
; Calculate the synthetic color for the
; first band. Set the output band names to
; R, G, and B. Set the low and high pass
; kernels to 10 pixels and use a saturation
; value of 0.5 for the HSV transform.
ENVI_File_Query, fid, DIMS=dims, NB=nb
ENVI_Doit,'ENVI_Synthetic_Color_Doit', $
   FID = fid, $
   DIMS = dims, $
   POS = [0], $
   H_KSIZE = 10, $
   L_KSIZE = 10, $
   SAT_VALUE = 0.5, $
   OUT_BNAME = ['R','G','B'], $
   OUT_NAME = OutFile, $
   R_FID = r_fid
; Pass the R_FID to an ENVIRaster object.
OutRaster = ENVIFIDToRaster(r_fid)
; Display the original data and the result
View = e.GetView()
Layer = View.CreateLayer(Raster)
Portal = View.CreatePortal()


ENVI_DOIT, 'ENVI_SYNTHETIC_COLOR_DOIT', DIMS=array, FID=file ID, H_KSIZE=long integer, /IN_MEMORY, L_KSIZE=long integer, OUT_BNAME=string array, OUT_NAME=string, POS=array, R_FID=variable, SAT_VALUE=floating point



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


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).


Use this keyword to specify the high-pass kernel size for the filter. The high pass filter is the value for the HSV transform. H_KSIZE is a long integer greater than 1.


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).


Use this keyword to specify the low-pass kernel size for the filter. The low pass filter is the hue for the HSV transform. L_KSIZE is a long integer greater than 1.


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


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.


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:

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]
envi_doit, 'cf_doit', dims=dims, fid=fid_array


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.


Use this keyword to specify a saturation value for the HSV transform. SAT_VALUE is a floating-point number from 0.0 to 1.0.

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