ANISOR - Compute the orientation information derived from the anisotropic continous scale model of [BBW07].

Contents

Description

Syntax

  kappa = anisor(I);
  kappa = anisor(I, nu, rho, sig, ...
                          'Property', propertyvalue, ...);

Inputs

I : an input image with size (X,Y,C), where C>1 when I is multichannel.

nu : (optional) nonegative integer which influences the propagation of the structures in the normal to the gradient direction; default: nu=4.

rho : post-smoothing width; this parameter sets the integration scale for spatial averaging, that controls the size of the neighbourhood in which an orientation is dominant; it is used for averaging the partial directional derivatives of the tensor with a Gaussian kernel; if rho<0.05, then no smoothing is performed; default: rho=1.

sig : pre-smoothing width; this parameter sets the differentiation scale in the case the image is smoothed prior to the differentiation through Gaussian filtering; sigma typically controls the size of the objects whose orientation has to be estimated; default: sigma=1, i.e. Gaussian regularisation is used for estimating the derivatives.

Property [propertyname propertyvalues]

'der' : string defining the method of pre-smoothing/differentiation used for estimating the directional derivatives of the input image; it is either (see GRDSMOOTH): 'matlab', 'vista', 'fast', 'conv', 'diag', 'tap5', 'sob', 'opt' or 'ana'; default: der='fast'.

'int' : string defining the method used for the post-smoothing of the GST; it is either (see GRD2GST): 'matlab', 'conv' or 'fast' for isotropic Gaussian intoothing, or 'ani' for anisotropic Gaussian (using hour- glass shaped Gaussian kernels) along the edges; this latter better captures edges anisotropy; default: int='fast'.

'samp' : to perform (* samp) interpolation of the estimated gradient to avoid aliasing (should set to 2); default: samp=1, ie no interpolation is performed.

Output

kappa : orientation information in [0,1].

Reference

[BBW07] M. Breuß, B. Burgeth and J. Weickert: "Anisotropic continuous-scale morphology", Proc. IbPRIA, LNCS 4478, pp. 515-522, Springer, 2007. http://www.springerlink.com/content/1hm264w86111m148/

See also

Ressembles: GSTSMOOTH, ANISORFILT. Requires: ANISOR_BASE.

Function implementation

function kappa = anisor(I,varargin)

parsing parameters

error(nargchk(1, 18, nargin, 'struct'));
error(nargoutchk(1, 1, nargout, 'struct'));

% mandatory parameter
if ~isnumeric(I)
    error('anisor:inputerror','a matrix is required in input');
end

% optional parameters
p = createParser('ANISOR');
% principal optional parameters
p.addOptional('nu', 4, @(x)isscalar(x) && x>=0);
p.addOptional('rho', 3, @(x)isscalar(x) && isfloat(x) && x>=0);
p.addOptional('sigma', 1, @(x)isscalar(x) && isfloat(x) && x>=0);
p.addParamValue('der', 'fast', @(x)islogical(x) || (ischar(x) && ...
    any(strcmpi(x,{'matlab','vista','fast','conv','diag', ...
    'tap5','sob','opt','ana'}))));
p.addParamValue('int', 'fast', @(x)islogical(x) || (ischar(x) && ...
    any(strcmpi(x,{'matlab','conv','fast','ani'}))));
p.addParamValue('samp', 2, @(x)isscalar(x) && round(x)==x && x>=1 && x<=5);

% parse and validate all input arguments
p.parse(varargin{:});
p = getvarParser(p);

calculation

kappa = anisor_base(I, p.nu, p.rho, p.sigma, p.der, p.int, p.samp);

display

if p.disp
    figure, imagesc(kappa), colormap gray, axis image off;
    title('orientation indice')
end

end % end of anisor