next up previous contents index
Next: MAP_AVER Up: Image Processing Tasks Previous: INTERPOLATE   Contents   Index


MAKE_CUBE

        MAKE_CUBE

    This  is  an  image  construction  task  which  is  able  to  produce  a
    filled image from one containing many blanked pixels.  The reconstructed
    filled image is not constrained to fit exactly the observed data points.
    On  the  opposite, the construction is made by the analogy to a flexible
    plate attached to fixed points by springs:  the plate is  the  analogous
    of  the  surface  represented by the image, and the fixed points are the
    analogous of the observed data points.  By adjusting the parameter P
                          P = (plate stiffness) / (springs stiffness)
    it is possible to control the fidelity to  the  original  data  and  the
    amount of smoothing involved in the image reconstruction.  Low values of
    P mean  high  fidelity  to  observed  data,  and  negligible  amount  of
    smoothing.

    The original grid is first expanded by  a  factor  EXPANSION$,  new pix-
    els   being   attributed   the  blanking  value.  Then, the minimization
    proceeds iteratively to adjust the final  image,  until  convergence  is
    reached.   Initially  blanked  pixels  are  ignored  in  the convergence
    criterium.

    The algorithm works on cubes, processing each plane  independently.   It
    can  be  used as an alternative to FILL_CUBE for oversampled images, but
    works also for undersampled data.


Gildas manager 2014-07-01