File: histomatch.pro

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;+
; NAME:
;       HistoMatch
;
; PURPOSE:
;
;       This is a function for Histogram Matching, in which an image
;       is manipulated in such a way that it's final histogram approximates
;       the histogram of an input image or histogram. Histogram matching
;       allows the user to specify the shape of the histogram of the final
;       product.
;
; AUTHOR:
;
;       FANNING SOFTWARE CONSULTING
;       David Fanning, Ph.D.
;       1645 Sheely Drive
;       Fort Collins, CO 80526 USA
;       Phone: 970-221-0438
;       E-mail: david@idlcoyote.com
;       Coyote's Guide to IDL Programming: http://www.idlcoyote.com
;
; CATEGORY:
;
;       Image Processing
;
; CALLING SEQUENCE:
;
;       output_image = HistoMatch(image, histogram_to_match)
;
; INPUTS:
;
;       image - The input image to be manipulated. Assumed to be a 2D byte array.
;
;       histogram_to_match - Can be either a 1D long vector of 256 elements specifying
;           the histogram to match, or a 2D byte array from which the histogram to
;           match is calculated.
;
; OUTPUTS:
;
;       output_image - The manipulated image adjusted to the histogram specifications.
;
; INPUT KEYWORDS:
;
;       None.
;
; OUTPUT KEYWORDS:
;
;       None.
;
; DEPENDENCIES:
;
;       None.
;
; METHOD:
;
;       Based on the Histogram Matching method on pages 94-102 of Digital
;       Image Processing, 2nd Edition, Rafael C. Gonzalez and Richard E. Woods,
;       ISBN 0-20-118075-8.
;
; EXAMPLE:
;
;       There is an example program at the end of this file. It will require cgImage
;       from the Coyote Library to run. You can also find an explanation of this program
;       at http://www.idlcoyote.com/ip_tips/histomatch.html.
;
; MODIFICATION HISTORY:
;
;       Written by David W. Fanning, January 2003.
;-
;
;******************************************************************************************;
;  Copyright (c) 2008, by Fanning Software Consulting, Inc.                                ;
;  All rights reserved.                                                                    ;
;                                                                                          ;
;  Redistribution and use in source and binary forms, with or without                      ;
;  modification, are permitted provided that the following conditions are met:             ;
;                                                                                          ;
;      * Redistributions of source code must retain the above copyright                    ;
;        notice, this list of conditions and the following disclaimer.                     ;
;      * Redistributions in binary form must reproduce the above copyright                 ;
;        notice, this list of conditions and the following disclaimer in the               ;
;        documentation and/or other materials provided with the distribution.              ;
;      * Neither the name of Fanning Software Consulting, Inc. nor the names of its        ;
;        contributors may be used to endorse or promote products derived from this         ;
;        software without specific prior written permission.                               ;
;                                                                                          ;
;  THIS SOFTWARE IS PROVIDED BY FANNING SOFTWARE CONSULTING, INC. ''AS IS'' AND ANY        ;
;  EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES    ;
;  OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT     ;
;  SHALL FANNING SOFTWARE CONSULTING, INC. BE LIABLE FOR ANY DIRECT, INDIRECT,             ;
;  INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED    ;
;  TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;         ;
;  LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND             ;
;  ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT              ;
;  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS           ;
;  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.                            ;
;******************************************************************************************;
FUNCTION HISTOMATCH, image, histogram_to_match

   ; Error handling.

Catch, theError
IF theError NE 0 THEN BEGIN
   Catch, /Cancel
   ok = cgErrorMsg(/Traceback)
   IF N_Elements(image) NE 0 THEN RETURN, image ELSE RETURN, -1L
ENDIF

   ; We require two input parameters.

IF N_Params() NE 2 THEN Message, 'Two arguments required. Please read the program documentation.'

   ; Must have 2D image array.

IF Size(image, /N_Dimensions) NE 2 THEN Message, 'Image argument must be 2D. Returning.'

   ; Is the histogram_to_match variable a 1D or 2D array? Branch accordingly.

CASE Size(histogram_to_match, /N_Dimensions) OF
   1: BEGIN
      IF N_Elements(histogram_to_match) NE 256 THEN $
         Message, 'Histogram to match has incorrect size. Returning.'
      match_histogram =    histogram_to_match
      END
   2: match_histogram = Histogram(Byte(histogram_to_match), Min=0, Max=255, Binsize=1)
   ELSE: Message, 'Histogram to match has incorrect number of dimensions. Returning.'
ENDCASE

   ; Calculate the histogram of the input image.

h = Histogram(Byte(image), Binsize=1, Min=0, Max=255)

   ; Make sure the two histograms have the same number of pixels. This will
   ; be a problem if the two images are different sizes, you are matching a
   ; histogram from an image subset, etc.

totalPixels = Float(N_Elements(image))
totalHistogramPixels = Float(Total(match_histogram))

IF totalPixels NE totalHistogramPixels THEN $
   factor = totalPixels / totalHistogramPixels ELSE $
   factor = 1.0

match_histogram = match_histogram * factor

   ; Find a mapping from the input pixels to the transformation function s.

s = FltArr(256)
FOR k=0,255 DO BEGIN
  s[k] = Total(h(0:k) / totalPixels)
ENDFOR

   ; Find a mapping from input histogram to the transformation function v.

v = FltArr(256)
FOR q=0,255 DO BEGIN
  v[q] = Total(match_histogram(0:q) / Total(match_histogram))
ENDFOR

   ; Find probablitly density function z from v and s.

z = BytArr(256)
FOR j=0,255 DO BEGIN
   i = Where(v LT s[j], count)
   IF count GT 0 THEN z[j] = (Reverse(i))[0] ELSE z[j]=0
ENDFOR

   ; Create the matched image.

matchedImage = z[Byte(image)]
RETURN, matchedImage
END
; ----------------------------------------------------------------------------



PRO Example

   ; Get an image whose histogram you want to match.

filename = Filepath('ctscan.dat', Subdir=['examples', 'data'])
OpenR, lun, filename, /Get_Lun
image_to_match = BytArr(256, 256)
ReadU, lun, image_to_match
Free_Lun, lun

   ; Get an image to apply the histogram to.

filename = Filepath('worldelv.dat', Subdir=['examples', 'data'])
OpenR, lun, filename, /Get_Lun
image = BytArr(360, 360)
ReadU, lun, image
Free_Lun, lun


Window, 0, XSize=500, YSize=250, Title='Match this Image Histogram', XPos=100, YPos=100
!P.Multi=[0,2,1]
cgImage, image_to_match
Plot, Histogram(image_to_match), Max_Value=5000
!P.Multi=0

Window, 1, XSize=500, YSize=250, Title='Manipulate this Image', XPos=100, YPos=360
!P.Multi=[0,2,1]
cgImage, image
Plot, Histogram(image), Max_Value=5000
!P.Multi=0

Window, 2, XSize=500, YSize=250, Title='Final Result', XPos=100, YPos=630
!P.Multi=[0,2,1]
match = HistoMatch(image, image_to_match)
cgImage, match
Plot, Histogram(match), Max_Value=5000
!P.Multi=0
END