NAME

     disparity2d - Computes disparity between  neighboring  label
     sites


SYNOPSIS

     disparity2d [ -t1 input_file_1 ] [ -t2 input_file_2 ] [  -t3
     input_file_3  ]  [ -t4 input_file_4 ] [ -t5 input_file_5 ] [
     -O file_out ] [ -coarse coarse ]  [  -halfwin  halfwin  ]  [
     -fmat fmat_file ] [ -bmat bmat_file ] [ -nr nr ] [ [-ks|-ad]
     ] [ -? ]


DESCRIPTION

     disparity2d This program computes the disparity between  all
     pairs  of neighboring label sites.  The two label sites in a
     neighboring pair can be near neighbors or random  neighbors.
     The  disparity for one of these pairs is computed by compar-
     ing the attribute values in the texture analysis  window  of
     one of the label sites with the attribute values in the tex-
     ture analysis window of the other label site.  This  program
     uses the Kolmogorov-Smirnov statistic (or some variant, such
     as the Anderson-Darling statistic) to determine the similar-
     ity  of the cdf's of the attribute values in the two texture
     analysis windows.  If the textures (i.e. the cdf's)  of  the
     two  sites  are  different, then the disparity between these
     two sites is 1.  If the textures of the two sites are  simi-
     lar, then the disparity between the two sites is -1.

     disparity2d gets all its parameters from command line  argu-
     ments.  These arguments specify the input, output, etc.


COMMAND LINE ARGUMENTS

     -t1 input_file_1
          the input file containing the first  attribute  of  all
          the  sites in the data lattice.  The first attribute is
          the data value at the data site.  (optional)

     -t2 input_file_2
          the input file containing the second attribute  of  all
          the sites in the data lattice.  The second attribute is
          the intensity range, i.e.  the  maxval  minval  in  the
          attribute analysis window of the data site.  (optional)

     -t3 input_file_3
          the input file containing the third  attribute  of  all
          the  sites in the data lattice.  The third attribute is
          the boundary residual, i.e. the data value at the  data
          site  minus the average of the data values on the boun-
          dary of the the data site's attribute analysis  window.
          (optional)

     -t4 input_file_4
          the input file containing the fourth attribute  of  all
          the sites in the data lattice.  The fourth attribute is
          the horizontal directional residual,  i.e.  a  gradient
          approximation in the horizontal direction.  (optional)

     -t5 input_file_5
          the input file containing the fifth  attribute  of  all
          the  sites in the data lattice.  The fifth attribute is
          the vertical  directional  residual,  i.e.  a  gradient
          approximation  in  the  vertical direction.  (optional)
          NOTE: at least one of the attributes must  be  used  to
          calculate  the  disparity  values, i.e. at least one of
          the options {t1, t2, ..., t5} must be specified on  the
          command line.

     -O file_out
          the output file which contains  the  disparity  values.
          For  each  label  site  there are num_of_rand_neigh + 4
          disparity values, one for each neighbor  of  the  label
          site.  (Default: stdout)


GENERAL OPTIONS

     -fmat fifn
          the input file containing the forward  index  used  for
          locating  random  neighbors.  The forward index is gen-
          erated by the program randomgraph

     -bmat bifn
          the input file containing the backward index  used  for
          locating  random  neighbors. The backward index is gen-
          erated by the program randomgraph

     [-ks | -ad]
          a pair of optional flags used to specify which statist-
          ical   test   is   used   to   compare  textures.   The
          Kolmogorov-Smirnov test is used when the  -ks  flag  is
          specified.   The Anderson-Darling test is used when the
          -ad flag is specified.   Specification  of  a  test  is
          optional.   If  neither  one  of these flags is set the
          Kolmogorov-Smirnov test is used.  NOTE:  at most one of
          these  flags  can be set on a command line.  NOTE:  The
          Anderson-Darling test is still being refined.   So,  it
          is not implemented in the current version.

     -coarse coarseness
          inverse of the resolution at which the segmentation  is
          performed.   That  is,  the  ratio  of  the  number  of
          samples/traces in the data lattice  to  the  number  of
          samples/traces  in the label lattice.  The data lattice
          is the input to the program texture, and the label lat-
          tice  is  the  output  from any segmentation optimizer,
          such as bethe.  For highest resolution set the  coarse-
          ness to 1.  (Default: 9)

     -nr num_of_rand_neigh
          the number of random neighbors  for  each  label  site.
          The  neighborhood for a label site also includes 4 near
          neighbors.    Thus,   each   label   site   will   have
          num_of_rand_neigh  + 4 neighbors.  The number of random
          neighbors must be a power of two.  (Default: 16)

     -halfwin half_win_size
          half window width used to determine the  width  of  the
          texture  analysis  window over which the cdf's are com-
          puted in the program disparity2d.   The  width  of  the
          texture analysis window is given by 2 * half_win_size +
          1.  (Default: 7)

     -h, -?, -help
          Help.


See Also

     texture2d,  bethe2d,  cogeom2d,  combine2d,   randomgraph2d,
     texstat2d, brightsizing


REFERENCES

     Crawford,  Kelly,  and  Marfurt,  Kurt,  1997.   2D  Texture
     Analysis:   A  User's  Guide, Amoco Geoscience Research Bul-
     letin F97-G-14.

     Hoelting, Cory and Kelly, Ken, 1996.   Texture  Analysis  of
     Spectral  Decomposition Data Using a Segmentation Algorithm,
     Amoco Geoscience Research Bulletin F96-G-21.

     Matheney, Mike and Kelly, Ken, 1995.  Texture-Based  Segmen-
     tation  of  3-D Seismic Data, Amoco Geoscience Research Bul-
     letin F95-G-29.


CONTRACT AGREEMENT

     This product is brought to you by  Research  Agreement  #548
     (The Seismic Coherency Cube). Thank you for your support!


AUTHOR

     Cory Hoelting and Ken Kelly (E&PTG, Tulsa, OK, USA).


COPYRIGHT

     copyright 2001, Amoco Production Company
               All Rights Reserved
          an affiliate of BP America Inc.








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