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graphavd


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  This function implements the Absolute Value of the Differences (AVD) method [1], 
  only using a pixel-by time, with the normalization of the co-occurrence matrix (COM) 
  proposed by CARDOSO, R.R. et al. [2]. 
  Use as input data a 3D matrix created grouping NTIMES intensity matrices I(k)
  1<=k<=NTIMES

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

  $GAVD=\frac{1}{NTIMES-1}\sum\limits_{k=1}^{NTIMES-1} |I(k)-I(k+1)| \approx E[|I(k)-I(k+1)|]$


  References:
  [1]  BRAGA, R.A. et al. Evaluation of activity through dynamic laser speckle 
       using the absolute value of the differences, Optics Communications, v. 284, 
       n. 2, p. 646-650, 2011.
  [2]  R.R. Cardoso, R.A. Braga, Enhancement of the robustness on dynamic speckle 
       laser numerical analysis, Optics and Lasers in Engineering, 
       Volume 63, December 2014, Pages 19-24, ISSN 0143-8166, 
       http://dx.doi.org/10.1016/j.optlaseng.2014.06.004.


  After starting the main routine just type the following command at the
  prompt:
  GAVD = graphavd(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:
  GAVD returns the GAVD matrix.


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




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  This function implements the Absolute Value of the Differences (AVD) method 



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graphim


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  This function implements the Inertia Moment (IM) [1] method, only on a pixel-by time, 
  with the normalization of the co-occurrence matrix (COM) proposed by 
  CARDOSO, R.R. et al. [2]. The function returns the graphic IM method.
  Use as input data a 3D matrix created grouping NTIMES intensity matrices I(k)
  1<=k<=NTIMES

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

  $GIM=\frac{1}{NTIMES-1}\sum\limits_{k=1}^{NTIMES-1}(I(k)-I(k+1))^2 \approx E[(I(k)-I(k+1))^2]$

  References:
  [1]  ARIZAGA, R. et al. Speckle time evolution characterization by the 
       co-occurrence matrix analysis. Optics and Laser Technology, Amsterdam, 
       v. 31, n. 2, p. 163-169, 1999.
  [2]  R.R. Cardoso, R.A. Braga, Enhancement of the robustness on dynamic speckle 
       laser numerical analysis, Optics and Lasers in Engineering, 
       Volume 63, December 2014, Pages 19-24, ISSN 0143-8166, 
       http://dx.doi.org/10.1016/j.optlaseng.2014.06.004.
 

  After starting the main routine just type the following command at the
  prompt:
  GIM = graphim(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:
  GIM  returns the Generalized Difference matrix.


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




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  This function implements the Inertia Moment (IM) [1] method, only on a pixel



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graphptd


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  This function implements the Parameterized form of Temporal Difference (PTD) 
  [1] technique. Use as input data a 3D matrix created grouping NTIMES intensity 
  matrices I(k), 1<=k<=NTIMES

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

  $PTD=\sum\limits_{k=1}^{NTIMES-1} |I(k)-I(k+1)|^P$

  The function is normalized  with the number of elements in the sum.
  Thus, GPTD matrix represents the expected value of absolute difference 
  $|I(k)-I(k+1)|$ for any k value.

  $GPTD=\frac{PTD}{NTIMES-1} \approx E[|I(k)-I(k+1)|^P]$

  References:
  [1] Preeti D. Minz, A.K. Nirala, Intensity based algorithms for biospeckle 
      analysis, Optik - International Journal for Light and Electron Optics, 
      Volume 125, Issue 14, July 2014, Pages 3633-3636, ISSN 0030-4026, 
      http://dx.doi.org/10.1016/j.ijleo.2014.01.083.


  After starting the main routine just type the following command at the
  prompt:
  GPTD = graphptd(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.
  P    is a parameter whose value may be positive integer as well as fraction.
  SHOW [Optional] If SHOW is equal to string 'off', then do not plot the result.

  Output:
  GPTD returns the GPTD matrix.


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




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  This function implements the Parameterized form of Temporal Difference (PTD)



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graphrvd


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  This function implements the Regular Value of the Differences method [1],
  only on a pixel-by time, with the normalization of the co-occurrence matrix (COM) 
  proposed by CARDOSO, R.R. et al. [2].

  Use as input data a 3D matrix created grouping NTIMES intensity matrices I(k)
  1<=k<=NTIMES

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

  $GRVD=\frac{1}{NTIMES-1}\sum\limits_{k=1}^{NTIMES-1} (I(k)-I(k+1))$


  References:
  [1]  Pujaico Rivera Fernando. Paper coming soon.
  [2]  CARDOSO, R.R.; BRAGA R.A. Enhancement of the robustness on dynamic speckle 
       laser numerical analysis. Optics and Lasers in Engineering, 
       63(Complete):19-24, 2014.


  After starting the main routine just type the following command at the
  prompt:
  GRVD = graphrvd(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:
  GRVD returns the GRVD matrix.


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




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  This function implements the Regular Value of the Differences method [1],
 





