filter_gauss_nD

PURPOSE ^

n-dimensional Gaussian filter.

SYNOPSIS ^

function G = filter_gauss_nD( dims, mu, C, show )

DESCRIPTION ^

 n-dimensional Gaussian filter. 

 Creates an image of a Gaussian with arbitrary covariance matrix. The point [x,y,z]
 refers to the x-th column and y-th row, at the t-th frame.  So for example mu should
 have the format [col,row,t].

 If mu==[], it is calculated to be the center of the image.  C can be a full nxn
 covariance matrix, or an nx1 vector of variance.  In the latter case C is calculated as
 C=diag(C).  If C=[]; then C=(dims/6).^2, ie it is transformed into a vector of variances
 such that along each dimension the variance is equal to (siz/6)^2.  

 INPUTS
   dims    - n element vector of dimensions of final Gaussian
   mu      - [optional] n element vector specifying the mean or []
   C       - [optional] nxn covariance matrix, nx1 set of variances, or variance, or []
   show    - [optional] figure to use for display (no display if == 0)

 OUTPUTS
   G   - image of the created Gaussian

 EXAMPLE
   % 2D
   sigma=3; G = filter_gauss_nD( 4*[sigma sigma] + 1, [], [sigma sigma].^2, 1 );
   % 3D
   R = rotation_matrix3D( [1,1,0], pi/4 ); 
   C = R'*[10^2 0 0; 0 5^2 0; 0 0 16^2]*R;
   G = filter_gauss_nD( [50,50,50], [25,25,25], C, 1 );

 DATESTAMP
   29-Sep-2005  2:00pm

 See also FILTER_GAUSS_1D

CROSS-REFERENCE INFORMATION ^

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