NAME

       grdhisteq - Histogram equalization for grd files


SYNOPSIS

       grdhisteq  in_grdfile [ -Gout_grdfile ] [ -Cn_cells ] [ -D ] [ -N[norm]
       ] [ -Q ] [ -V ]


DESCRIPTION

       grdhisteq allows the user to find the data values which divide a  given
       grdfile  into patches of equal area.  One common use of grdhisteq is in
       a kind of histogram equalization of an image.  In this application, the
       user  might  have  a  grdfile of flat topography with a mountain in the
       middle.  Ordinary gray shading of this  file  (using  grdimage/grdview)
       with  a  linear mapping from topography to graytone will result in most
       of the image being very dark  gray,  with  the  mountain  being  almost
       white.   One  could  use  grdhisteq to write to stdout an ASCII list of
       those data values which divide the range of the data into n_cells  seg-
       ments,  each  of  which  has  an equal area in the image.  Using awk or
       makecpt one can take this output and build a cpt file; using  the  cpt-
       file  with  grdimage  will  result  in an image with all levels of gray
       occurring equally.  Alternatively, see grd2cpt.
            The second common use of grdhisteq is in writing  a  grdfile  with
       statistics  based on some kind of cumulative distribution function.  In
       this application, the output has relative highs and lows  in  the  same
       (x,y)  locations  as  the  input  file,  but  the values are changed to
       reflect their place in some cumulative distribution.  One example would
       be  to  find the lowest 10% of the data:  Take a grdfile, run grdhisteq
       and make a grdfile using n_cells = 10, and then contour the  result  to
       trace  the  1  contour.   This will enclose the lowest 10% of the data,
       regardless of their original values.  Another example is in  equalizing
       the output of grdgradient.  For shading purposes it is desired that the
       data have a smooth distribution, such as a gaussian.  If you  run  grd-
       histeq  on  output  from grdgradient and make a grdfile output with the
       Gaussian option, you will have a grdfile whose values  are  distributed
       according  to a gaussian distribution with zero mean and unit variance.
       The locations of these values will correspond to the locations  of  the
       input;  that  is,  the  most negative output value will be in the (x,y)
       location of the most negative input value, and so on.
            No space between the option flag  and  the  associated  arguments.
       Use upper case for the option flags and lower case for modifiers.

       in_grdfile
              2-D binary grd file to be equalized.



OPTIONS

       -C     Sets how many cells (or divisions) of data range to make.

       -D     Dump level information to standard output.

       -G     Name of output 2-D grd file.  Used with -N only.

       -N     Gaussian  output.   Use  with  -G to make an output grdfile with
              standard normal scores.  Append norm to force the scores to fall
              in the <-1,+1> range [Default is standard normal scores].

       -Q     Use quadratic intensity scaling.  [Default is linear].

       -V     Selects verbose mode, which will send progress reports to stderr
              [Default runs "silently"].


EXAMPLES

       To find the height intervals that divide the file heights.grd  into  16
       divisions of equal area, try

       grdhisteq heights.grd -C16 -D > levels.d

       To  make  the poorly distributed intensities in the file raw_intens.grd
       suitable for use with grdimage or grdview, try

       grdhisteq raw_intens.grd -Gsmooth_intens.grd -N -V


RESTRICTIONS

       If you use grdhisteq to make a gaussian output for gradient shading  in
       grdimage  or grdview, you should be aware of the following:  the output
       will be in the range [-x, x], where x is based on the number of data in
       the  input  grdfile  (nx * ny) and the cumulative gaussian distribution
       function F(x).  That is, let N = nx * ny.  Then x will be  adjusted  so
       that  F(x)  =  (N  -  1 + 0.5)/N.  Since about 68% of the values from a
       standard normal distribution fall within +/- 1, this will  be  true  of
       the output grdfile.  But if N is very large, it is possible for x to be
       greater than 4.  Therefore, with the grdimage program  clipping  gradi-
       ents  to the range [-1, 1], you will get correct shading of 68% of your
       data, while 16% of them will be clipped to -1 and 16% of  them  clipped
       to  +1.  If this makes too much of the image too light or too dark, you
       should take the output of grdhisteq and rescale it  using  grdmath  and
       multiplying by something less than 1.0, to shrink the range of the val-
       ues, thus bringing more than 68% of the image into the range  [-1,  1].
       Alternatively, supply a normalization factor with -N.


SEE ALSO

       gmtdefaults(l),  gmt(l),  grd2cpt(l), grdgradient(l), grdimage(l), grd-
       math(l), grdview(l), makecpt(l)



VERSION                              DATE                         GRDHISTEQ(l)

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