mirror of
https://github.com/c-sooyoung/fold_slice.git
synced 2026-09-17 17:29:09 +09:00
91 lines
3.8 KiB
Matlab
91 lines
3.8 KiB
Matlab
% GET_PHASE_GRADIENT_1D get 1D gradient of phase of an image stack.
|
||
% Accept either complex image or just phase
|
||
%
|
||
% [d_img] = get_phase_gradient_1D(img, ax=2, step=0)
|
||
%
|
||
% Inputs
|
||
% **img - stack of complex valued input images
|
||
% *optional*
|
||
% **ax - axis of derivative, default = 2
|
||
% **step - step used to calculate the central difference, default=0 (analytic expression)
|
||
%
|
||
% *returns*
|
||
% ++d_img - phase gradient array
|
||
|
||
|
||
|
||
|
||
%*-----------------------------------------------------------------------*
|
||
%| |
|
||
%| Except where otherwise noted, this work is licensed under a |
|
||
%| Creative Commons Attribution-NonCommercial-ShareAlike 4.0 |
|
||
%| International (CC BY-NC-SA 4.0) license. |
|
||
%| |
|
||
%| Copyright (c) 2017 by Paul Scherrer Institute (http://www.psi.ch) |
|
||
%| |
|
||
%| Author: CXS group, PSI |
|
||
%*-----------------------------------------------------------------------*
|
||
% You may use this code with the following provisions:
|
||
%
|
||
% If the code is fully or partially redistributed, or rewritten in another
|
||
% computing language this notice should be included in the redistribution.
|
||
%
|
||
% If this code, or subfunctions or parts of it, is used for research in a
|
||
% publication or if it is fully or partially rewritten for another
|
||
% computing language the authors and institution should be acknowledged
|
||
% in written form in the publication: “Data processing was carried out
|
||
% using the “cSAXS matlab package” developed by the CXS group,
|
||
% Paul Scherrer Institut, Switzerland.”
|
||
% Variations on the latter text can be incorporated upon discussion with
|
||
% the CXS group if needed to more specifically reflect the use of the package
|
||
% for the published work.
|
||
%
|
||
% A publication that focuses on describing features, or parameters, that
|
||
% are already existing in the code should be first discussed with the
|
||
% authors.
|
||
%
|
||
% This code and subroutines are part of a continuous development, they
|
||
% are provided “as they are” without guarantees or liability on part
|
||
% of PSI or the authors. It is the user responsibility to ensure its
|
||
% proper use and the correctness of the results.
|
||
|
||
function d_img = get_phase_gradient_1D(img, ax, step, shift)
|
||
|
||
import utils.*
|
||
import math.*
|
||
|
||
if isreal(img)
|
||
img = exp(1i*img);
|
||
end
|
||
if nargin < 2
|
||
ax = 2;
|
||
end
|
||
if nargin < 3
|
||
step = 0.5; % step of the difference (too small will amplify noise)
|
||
end
|
||
if nargin < 4
|
||
shift = 0; % perform shift and gradient calculation in single step
|
||
end
|
||
assert(step >= 0, 'Difference step has to be > 0')
|
||
|
||
% suppress edge issues if phase ramp is not subtracted / there is no
|
||
% air around sample
|
||
|
||
pad_distance = 8;
|
||
img = padarray(img,circshift([pad_distance,0,0], ax-1),'symmetric','both');
|
||
img = smooth_edges(img, pad_distance, ax);
|
||
|
||
if step == 0
|
||
% analytic formula (sensitive to noise) but faster
|
||
img = img ./ (abs(img) + eps);
|
||
d_img = get_img_grad(img, ax); % img is assumed to be complex
|
||
d_img = imag(conj(img).*d_img);
|
||
else
|
||
d_img = angle( imshift_fft_ax(img,-step+shift,ax) .* conj( imshift_fft_ax(img,step+shift,ax)))/(2*step);
|
||
end
|
||
% remove padding
|
||
ind = circshift({pad_distance:size(d_img,ax)-pad_distance-1,':', ':'},ax-1);
|
||
d_img = d_img(ind{:});
|
||
|
||
|
||
end |