INFORGBEDGE - Visualization of edge magnitude and orientation of color images.

Contents

Description

Provide edge magnitude and orientation of multispectral images based on their derivatives, using multichannel approach (gradient structure tensor), and reduced (RGB or LAB) approach (gradient). Used for simple visual comparison of both approaches.

Syntax

   [E, M, O, rE, rM, rO] = INFORGBEDGE(I, 'disp', true);
   [E, M, O, rE, rM, rO] = INFORGBEDGE(I, reduce, rho, sig, der, int);

Inputs

I : an input image with size (X,Y,C), where C=3 when I is multichannel.

reduce : optional string setting the method used for reducing the input image into a scalar (graylevel) one; it is either 'rgb' for calling RGB2GRAY or 'lab' for calling RGB2LAB; default: reduce='rgb'.

rho : optional integration scale (see GTSMOOTH); default: rho=0, ie. in order to compare both multichannel and reduced approaches, we skip in principle the spatial averaging of the tensor.

sig : optional differentiation scale (see GTSMOOTH); default: sig=1, i.e. Gaussian regularisation is used for estimating the derivatives.

der : optional string for pre-smoothing/differentiation (see GRDSMOOTH): 'matlab', 'vista', 'fast', 'conv', 'fleck', 'tap5', 'tap7', 'sob', 'opt' or 'ana'; default: der='matlab'.

int : optional string for post-smoothing (see GRD2GST): 'matlab', 'conv' or 'fast'; default: int='fast'.

Outputs

E, rE : edge maps obtained through multichannel and reduced approaches.

M, O : magnitude and orientation using the multichannel approach.

rM, rO : ibid reducing the image first.

Displays the overlapped gradient magnitudes and edge maps of a color image using both multispectral and reduced approaches.

See also

Ressembles: EDGECORNER, KOETHEDGE, CANNYEDGE. Requires: INFORGBEDGE_BASE.

Function implementation

function [E, M, O, rE, rM, rO] = inforgbedge(I, varargin)

parsing parameters

error(nargchk(1, 19, nargin, 'struct'));
error(nargoutchk(0, 4, nargout, 'struct'));

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

% optional parameters
p = createParser('GSTSMOOTH');
% principal optional parameters
p.addOptional('reduce', 'rgb', @(x)ischar(x) && any(strcmpi(x,{'rgb','lab'})));
p.addOptional('rho', 0, @(x)isscalar(x) && isfloat(x) && x>=0);
p.addOptional('sigma', 1, @(x)isscalar(x) && isfloat(x) && x>=0);
p.addOptional('der', 'matlab', @(x)islogical(x) || (ischar(x) && ...
    any(strcmpi(x,{'matlab','vista','fast','conv','fleck', ...
    'tap5','tap7','sob','opt','ana'}))));
p.addOptional('int', 'fast', @(x)islogical(x) || (ischar(x) && ...
    any(strcmpi(x,{'matlab','conv','fast'})))); % 'ani' not allowed here

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

checking/setting variables

if size(I,3)~=3
    error('inforgbedge:inputerror', 'matrix (m x n x 3) required in input');
end

I = rescale(I,0,1);

if strcmpi(p.reduce,'rgb')
    R = rgb2gray(I);
elseif strcmpi(p.reduce,'lab')
    C = makecform('srgb2lab');
    R = applycform(I,C);
    R = R(:,:,1);
    % R = rgb2lab(I);
end

main calculations

[E, M, O, rE, rM, rO] = inforgbedge_base(I, R, p.rho, p.sigma, p.der, p.int);

display

if p.disp
    %  figure, colormap gray
    %  subplot(1,2,1), imagesc(mag), axis image off, title('multichannel')
    %  subplot(1,2,2), imagesc(rmag), axis image off, title('reduced')
    figure,
    subplot(1,2,1), imagesc(rescale(cat(3, M, rM, rM),0,1))
    title('magnitude: R multichannel - GB reduced'), axis image off
    subplot(1,2,2), imagesc(rescale(cat(3, E, rE, rE),0,1))
    title('edge map: R multichannel - GB reduced'), axis image off
end

end % end of inforgbedge