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
