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72 lines
3.4 KiB
Matlab
72 lines
3.4 KiB
Matlab
% GET_IMG_GRAD_CONV get image gradients along all 3 axis using real space convolution
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%
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% [dX, dY, dZ] = get_img_grad_conv(img, win_size, axis)
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%
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% Inputs:
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% **img - stack of images
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% **win_size - size of the window used for approximation of the FFT gradient
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% **axis - direction of the derivative
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% *returns*
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% ++[dX, dY, dZ] - 3D gradients
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%*-----------------------------------------------------------------------*
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%| |
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%| Except where otherwise noted, this work is licensed under a |
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%| Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
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%| International (CC BY-NC-SA 4.0) license. |
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%| |
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%| Copyright (c) 2017 by Paul Scherrer Institute (http://www.psi.ch) |
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%| |
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%| Author: CXS group, PSI |
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%*-----------------------------------------------------------------------*
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% You may use this code with the following provisions:
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%
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% If the code is fully or partially redistributed, or rewritten in another
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% computing language this notice should be included in the redistribution.
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%
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% If this code, or subfunctions or parts of it, is used for research in a
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% publication or if it is fully or partially rewritten for another
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% computing language the authors and institution should be acknowledged
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% in written form in the publication: “Data processing was carried out
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% using the “cSAXS matlab package” developed by the CXS group,
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% Paul Scherrer Institut, Switzerland.”
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% Variations on the latter text can be incorporated upon discussion with
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% the CXS group if needed to more specifically reflect the use of the package
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% for the published work.
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%
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% A publication that focuses on describing features, or parameters, that
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% are already existing in the code should be first discussed with the
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% authors.
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%
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% This code and subroutines are part of a continuous development, they
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% are provided “as they are” without guarantees or liability on part
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% of PSI or the authors. It is the user responsibility to ensure its
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%
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function [dX, dY, dZ] = get_img_grad_conv(img, win_size, axis)
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%% get vertical and horizontal gradient of the image
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if ~isreal(img); error('Not implemented'); end
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ker = get_kernel(win_size);
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if isa(img, 'gpuArray'); ker = gpuArray(ker); end
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if nargin < 3 || any(axis == 2)
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dX = convn(img, reshape(ker,1,[],1), 'same');
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end
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if nargout > 1 || (nargin > 2 && any(axis == 1))
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dY = convn(img, reshape(ker,[],1,1), 'same');
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if nargout == 1; dX = dY; end
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end
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if nargout > 2 || (nargin > 2 && any(axis == 3))
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dZ = convn(img, reshape(ker,1,1,[]), 'same');
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if nargout == 1; dX = dZ; end
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end
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end
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function ker = get_kernel(win_size)
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N = max(9,2*win_size +1);
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grid = 2i*pi*(fftshift((0:N-1)/(N))-0.5);
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ker = -real(fftshift(fft(grid)))/length(grid);
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ker = ker( ceil(end/2)+(-ceil(win_size):ceil(win_size)));
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ker = utils.Garray(single(ker));
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end |