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93 lines
4.0 KiB
Matlab
93 lines
4.0 KiB
Matlab
% GET_PHASE_GRADIENT_2D get 2D gradient of phase of image IMG.
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% Accept either complex image or just phase
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%
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% [d_X, d_Y] = get_phase_gradient_2D(img, step=0, padding=8)
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%
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% Inputs
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% **img - stack of complex valued input images
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% *optional*
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% **step - step used to calculate the central difference, default=0 (analytic expression)
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% **padding - padding around edges to prevent periodic boundary artefacts
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%
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% *returns*
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% ++d_X,d_Y - horizontal and vertical phase gradient arrays
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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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% proper use and the correctness of the results.
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function [d_X, d_Y] = get_phase_gradient_2D(img, step, padding)
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import utils.*
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import math.*
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if isreal(img)
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img = exp(1i*img);
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end
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if nargin < 2
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step = 0; % step of the difference (too small will amplify noise)
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end
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if nargin < 3
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padding = 8; % pad arrays to avoid edge issues
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end
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% suppress edge issues if phase ramp is not subtracted / there is no
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% air around sample
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if padding > 0
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img = padarray(img,[padding, padding],'symmetric','both');
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img = smooth_edges(img, padding, [1,2]);
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end
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if step == 0
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% analytic formula (sensitive to noise) but faster
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% img = img ./ (abs(img) + eps);
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[d_X, d_Y] = get_img_grad(img); % img is assumed to be complex
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d_X = imag(conj(img).*d_X);
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d_Y = imag(conj(img).*d_Y);
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else
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% finite difference based method
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d_X = angle( imshift_fft_ax(img,-step,2) .* conj( imshift_fft_ax(img,step,2)))/(2*step);
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d_Y = angle( imshift_fft_ax(img,-step,1) .* conj( imshift_fft_ax(img,step,1)))/(2*step);
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end
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if padding > 0
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% remove padding
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ind = {padding:size(d_X,1)-padding-1,padding:size(d_X,2)-padding-1, ':'};
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d_X = d_X(ind{:});
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d_Y = d_Y(ind{:});
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end
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end |