This function implements the temporal speckle contrast matrix [1], the temporal 
  speckle standard deviation matrix and the temporal speckle mean matrix. Use as
  input data a 3D matrix created grouping NTIMES intensity matrices I(k)
  1<=k<=NTIMES

  I(k)=DATA(:,:,k)

  $MU= \frac{1}{NTIMES} \sum\limits_{k=1}^{NTIMES} I(k) \approx E[I(k)]$

  $SIGMA = \sqrt{ \frac{1}{NTIMES} \sum\limits_{k=1}^{NTIMES} (I(k)-MU)^2  }$

  With difference of proposed in [1], here is used the population standard
  deviation. Finally

  $C = SIGMA/MU$

  The function additionally also returns the deviation and expected matrices.

  Reference:
  [1] R. Nothdurft and G. Yao, 'Imaging obscured subsurface inhomogeneity using 
      laser speckle,' Opt. Express  13, 10034-10039 (2005). 


  After starting the main routine just type the following command at the
  prompt:
  C       = stdcont(DATA);
  [C D]   = stdcont(DATA);
  [C D E] = stdcont(DATA);
    
  Input:
  DATA is the speckle data pack. Where DATA is a 3D matrix created grouping NTIMES 
       intensity matrices with NLIN lines and NCOL columns. When N=size(DATA), then
       N(1,1) represents NLIN and
       N(1,2) represents NCOL and
       N(1,3) represents NTIMES.
  SHOW [Optional] If SHOW is equal to string 'off', then do not plot the result.

  Output:
  C    returns the speckle contrast matrix of image Data Pack.
  D    [Optional] Returns the standard deviation matrix (SIGMA) of image Data Pack.
  E    [Optional] Returns the expected matrix (MU) of image Data Pack.


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

Package: bsltl