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    Computes  the  cross histogram of two input images/cubes. The output has
    the same rank as the input arrays : 2 if images as input,  3  if  cubes.
    Both  inputs  must  have  the  same rank. If the input cubes are 3D data
    cubes, the third axis must be the same for both. If n1 and  n2  are  the
    numbers  of  bins  for the first and the second input cube respectively,
    the result has dimensions [n1,n2] or [n1,n2,nchan] where  nchan  is  the
    third  dimension  of the input cubes. The value at a given (I,J) is thus
    the number of pixels in the input images that have the value correspond-
    ing  to  slot I in the first image and to slot J in the second one.  For
    cubes, this is done in each plane. You can then sum (see SIC\COMPUTE) to
    have the cross histrogram for the whole cube.

    If  the tolerance on the blanking value is positive, the task takes into
    account the blanking values of the input cubes.

    The output image can be used as input to  task  REGRESSION  to  evaluate
    some statistical parameters of the correlation. See also HISTO_CLOUD for
    a slightly different information.

Gildas manager 2014-07-01