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91 lines
3.9 KiB
Matlab
91 lines
3.9 KiB
Matlab
% SMOOTH_EDGES takes stack of 2D images and smooths boundaries to avoid sharp edge artefacts during imshift_fft
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%
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% img = smooth_edges(img, win_size, dims)
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%
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% Inputs:
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% **img - 2D stacked array, smoothing is done along first two dimensions
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% **win_size - size of the smoothing region, default is 3
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% **dims - list of dimensions along which will by smoothing done
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% Outputs:
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% ++img - smoothed array
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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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%
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%
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function img = smooth_edges(img, win_size, dims)
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if nargin < 3
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dims = [1,2]; % default is smooth along first 2 dimensions
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end
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if nargin < 2
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win_size = 5;
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end
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try
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Npix = size(img);
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for i = dims
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ind = {':',':',':'};
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if Npix(i) <= 2*win_size ; continue; end
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win_size = max(win_size, 3);
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% get indices of the edge regions
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ind{i} = [Npix(i)-win_size+1:Npix(i),1:win_size];
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ker_size = [1,1];
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ker_size(i) = win_size;
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img_tmp = img(ind{:});
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kernel = reshape(gausswin(win_size,2.5), ker_size);
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% smooth across the image edges
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img_tmp = convn(img_tmp, kernel, 'same');
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% avoid boundary issues from convolution
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boundary_shape = [1,1];
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boundary_shape(i) = length(ind{i});
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img_tmp = bsxfun(@rdivide, img_tmp, conv(ones(boundary_shape), kernel, 'same'));
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img(ind{:}) = img_tmp;
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end
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catch err
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warning('Smooth edges failed: %s', err.message)
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end
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end
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function w = gausswin(L, a)
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% Compute window according to [1]
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N = L-1;
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n = (0:N)'-N/2;
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w = exp(-(1/2)*(a*n/(N/2)).^2);
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end
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