mirror of
https://github.com/c-sooyoung/fold_slice.git
synced 2026-09-17 19:39:08 +09:00
80 lines
4.4 KiB
Matlab
80 lines
4.4 KiB
Matlab
% weight_sino = estimate_reliability_region(complex_projection, probe_size, subsample)
|
||
% Estimates the region where the complex projections are good enough to be unwrapped. Assumes that outside
|
||
% of the measured FOV the amplitude of the object will be zero. This assumes that ptychography reconstruction
|
||
% did not add any values, due to those pixels never been reached by any probe element. Then the region is reduced
|
||
% by half the probe size using something akin to erosion. This function is only useful if the FOV is not square,
|
||
% such as the case of the elliptical FOV of laminography.
|
||
%
|
||
% Pseudo code example:
|
||
% weights = imerode(abs(object) > 0, ones(probe_size/2))
|
||
%
|
||
% Inputs:
|
||
% **complex_projection - (3D array) complex valued reconstructions
|
||
% **probe_size - (int, int) size of the illumination probe
|
||
% **subsample - (int) subsample the resulting array to save memory
|
||
% Outputs:
|
||
% ++weight_sino - weights, 1 for full quality, 0<=W<1 for poor regions
|
||
|
||
|
||
%*-----------------------------------------------------------------------*
|
||
%| |
|
||
%| 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) 2018 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 weight_sino = estimate_reliability_region(complex_projection, probe_size, subsample)
|
||
% simple reliability estimation based on amplitude of the
|
||
% reconstruction
|
||
|
||
Npix = size(complex_projection);
|
||
Npix_new = ceil(Npix(1:2)/subsample/2)*2;
|
||
|
||
%% SOLVE THE PROBLEM IN LOW RESOLUTION
|
||
weight_sino = tomo.block_fun(@utils.interpolateFT, complex_projection,Npix_new, struct('use_GPU', false, 'use_fp16', false));
|
||
probe_size = round(probe_size .* Npix_new ./ Npix(1:2));
|
||
weight_sino =abs(weight_sino);
|
||
weight_sino = single(weight_sino > 0.1*quantile(weight_sino(:),0.9));
|
||
|
||
%% only CPU is supported -> gather and move abck to GPU afterwards
|
||
weight_sino = gpuArray(utils.imcrop_outliers(gather(weight_sino))); % leave only single largest compact object
|
||
|
||
|
||
[Y,X] = meshgrid(-ceil(probe_size(1)/2):floor(probe_size(1)/2), -ceil(probe_size(2)/2):floor(probe_size(2)/2));
|
||
probe = (X/probe_size(1)*2).^2+(Y/probe_size(2)*2).^2 < 1;
|
||
|
||
kernel = probe/sum(probe(:));
|
||
weight_sino = convn(weight_sino, kernel , 'same');
|
||
weight_sino = weight_sino > 0.95;
|
||
weight_sino = uint8(imgaussfilt(single(weight_sino), 1)*255);
|
||
|
||
end
|