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C++ API

  This function makes a step to synthesis filter bank for each pixel
  of datapacks DATA0 and DATA1. It uses up-samplers in your inputs and
  after FIR filters (G0 and G1) of order (M-1) in non-causal form. If
  H0    = [h0 h1 h2 ... h(M-1)]
  then your Z transform is:
  M2=floor(M/2);
  $H[Z] = h0 Z^{+M2} + h1 Z^{+M2-1} + ...  h(M-1) Z^{+M2-(M-1)}$ 

  The function accepts the filter H0 as input parameter, so that the filters 
  G0 and G1  are calculated as $G0[Z]=H0[Z]$ and $G1[Z]= -H0[-Z]$. 
  H0 should be a low pass FIR filter with cut-off in pi/2 
  (for a 2*pi normalized frequency range) and, DATA0 and DATA1 the outputs of
  an step of a filter bank, as in the function firfilterbank() in MODE='MODE2'.
  In order to get a perfect reconstruction it is necessary that 
  $D[Z]=H0^2[Z]-H0^2[-Z]=A Z^B$ for any A and B.

  
  After starting the main routine just type the following command at the
  prompt:
  DATA=firsynthesisbank(DATA0,DATA1,H0);
  
  Input:
  DATA0  is a speckle data pack. Where DATA0 is a 3D matrix created grouping NTIMES 
         intensity matrices with NLIN lines and NCOL columns. When N=size(DATA0), then
         N(1,1) represents NLIN and
         N(1,2) represents NCOL and
         N(1,3) represents NTIMES.
         DATA0 is obtained after the down-sampler of output of H0 FIR filter in 
         a step of a filter bank with low-pass filter H0.
         DATA0 and DATA1 should have the same size.
  DATA1  is a speckle data pack. Where DATA1 is a 3D matrix created grouping NTIMES 
         intensity matrices with NLIN lines and NCOL columns. When N=size(DATA1), then
         N(1,1) represents NLIN and
         N(1,2) represents NCOL and
         N(1,3) represents NTIMES.
         DATA1 is obtained after the down-sampler of output of H1 FIR filter in 
         a step of a filter bank with low-pass filter H0.
         DATA1 and DATA0 should have the same size.
  H0     is a vector with the parameters of a FIR filter. H0 should be a low 
         pass filter with cut-off in pi/2 (for a 2*pi normalized frequency range).
         In order to ger a perfect reconstruction it is necessary that 
         $D[Z]=H0^2[Z]-H0^2[-Z]=A Z^B$ for any A and B.
  
  Output:
  DATA   is a synthesis of speckle datapacks DATA0 and DATA1. The number of images
         inside DATA is twice of the number of images of DATA0 and DATA1.
  

  For help, bug reports and feature suggestions, please visit:
  http://nongnu.org/bsltl/

Package: bsltl