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115 lines
4.6 KiB
Matlab
115 lines
4.6 KiB
Matlab
% IMSHIFT_FFT will apply shift with subpixel accuracy that can be different for each frame.
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%
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% img = imshift_fft(img, x,y, apply_fft = true, weights = [])
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%
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% Inputs:
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% **img - input image stack, can be complex valued
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% **x, y - shifts in number of pixels
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% **apply_fft , if false, then images will be assumed to be in fourier space
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% **weights - 0<W<=1 apply importance weighting to avoid noise in low reliability regions
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% returns:
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% ++img - shifted image stack
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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 img = imshift_fft(img, x,y, apply_fft, weights)
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if nargin < 3
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y = x(:,2); % x can be either Nx1 or Nx2 vector
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x = x(:,1);
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end
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if nargin < 4
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apply_fft = true; % if false, assume that img is already fft transformed
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end
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if nargin < 5
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weights = []; % weights prevents amplitifaction of noise in low reliability regions
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end
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if ~isempty(weights) && ~isscalar(weights)
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eps_ = 1e2*eps(ones(1,'like',img));
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weights = max(eps_, weights); % avoid dividing by zero
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end
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if all(x==0) && all(y==0)
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return
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end
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if ~isempty(weights) && ~isscalar(weights) && apply_fft
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img = img .* weights;
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end
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if all(x==0) % shift only along one axis -> faster
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img = utils.imshift_fft_ax(img, y,1, apply_fft);
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elseif all(y==0)
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img = utils.imshift_fft_ax(img, x,2, apply_fft);
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else
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%% 2D FFT SHIFTING
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real_img = isreal(img);
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Np = size(img);
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if apply_fft
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img = math.fft2_partial(img);
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end
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xgrid = ifftshift(-fix(Np(2)/2):ceil(Np(2)/2)-1)/Np(2);
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X = reshape((x(:)*xgrid)',1,Np(2),[]);
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X = exp((-2i*pi)*X);
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img = bsxfun(@times, img,X);
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ygrid = ifftshift(-fix(Np(1)/2):ceil(Np(1)/2)-1)/Np(1);
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Y = reshape((y(:)*ygrid)',Np(1),1,[]);
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Y = exp((-2i*pi)*Y);
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img = bsxfun(@times, img,Y);
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if apply_fft
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img = math.ifft2_partial(img);
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end
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if real_img
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img = real(img);
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end
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end
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if ~isempty(weights) && ~isscalar(weights) && apply_fft
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weights = utils.imshift_fft(weights, x,y); %% weights needs to be shifted as well
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img = img ./ weights;
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end
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end
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