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% mask = auto_mask_find(im,[<name>,<value>])
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%
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% im Input complex valued image
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%
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% Optional parameters:
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%
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% margins Two element array that indicates the (y,x) margins to exclude
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% from the edge of the mask window. For example to exclude the
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% noise around ptychography reconstructions, default 0.
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% smoothing Size of averaging window on the phase derivative, default
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% 10.
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% gradientrange Size of the histogram windown when selecting valid gradient
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% regions, in radians per pixel, default 1;
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% show_bivariate Show the bivariate histogram of the gradient, useful
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% for debugging. Set to the number of figure you'd like
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% it to appear.
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%
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% Morphological operations to remove point details in the mask
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%
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% close_size Size of closing window, removes dark bubbles from the mask,
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% default 15. ( = 1 for no effect)
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% open_size Size of opening window, removes bright bubbles from mask,
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% default 120. ( = 1 for no effect)
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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 mask = auto_mask_find(im,varargin)
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import plotting.franzmap
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% Defaults
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margin = [0 0];
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smoothing = 10;
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gradientrange = 1;
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close_size = 15;
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open_size = 120;
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show_bivariate = 0;
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zero_columns = [];
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% parse the variable input arguments not handled by auto_mask_find
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vararg = cell(0,0);
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for ind = 1:2:length(varargin)
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name = varargin{ind};
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value = varargin{ind+1};
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switch lower(name)
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case 'margin'
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margin = value;
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case 'smoothing'
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smoothing = value;
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case 'gradientrange'
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gradientrange = value;
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case 'close_size'
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close_size = value;
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case 'open_size'
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open_size = value;
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case 'show_bivariate'
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show_bivariate = value;
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case 'zero_columns'
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zero_columns = value;
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otherwise
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vararg{end+1} = name;
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vararg{end+1} = value;
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end
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end
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% Some checks
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if numel(margin)~= 2
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error('Margin variable should have two elements')
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end
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if close_size < 1
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error('erode_size must be an integer 1 or greater')
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end
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if open_size < 1
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error('erode_size must be an integer 1 or greater')
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end
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if gradientrange < 0
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error('gradientrange must be positive')
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end
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mask = true(size(im));
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mask(1:1+margin(1),:) = false;
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mask(end-margin(1):end,:) = false;
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mask(:,1:1+margin(2)) = false;
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mask(:,end-margin(2):end) = false;
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if ~isempty(zero_columns)
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mask(:,zero_columns) = false;
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end
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% Compute phase gradient based on phasor
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ph = exp(1i*angle(im));
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[gx, gy] = gradient(ph);
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gx = -real(1i*gx./ph);
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gy = -real(1i*gy./ph);
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kernel = ones(smoothing);
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gx = conv2(gx,kernel,'same');
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gy = conv2(gy,kernel,'same');
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gaux(:,1) = gy(mask(:));
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gaux(:,2) = gx(mask(:));
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[N,C] = hist3_own(gaux,[100 100]);
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[ny nx] = find(N == max(N(:)),1);
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% masky = (gy>C{1}(ny-gradientrange))&(gy<C{1}(ny+gradientrange));
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% maskx = (gx>C{2}(nx-gradientrange))&(gx<C{2}(nx+gradientrange));
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masky = (gy>C{1}(ny)-gradientrange)&(gy<C{1}(ny)+gradientrange);
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maskx = (gx>C{2}(nx)-gradientrange)&(gx<C{2}(nx)+gradientrange);
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maskxy = maskx&masky;
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% figure(1000); imagesc(masky); axis xy; colormap franzmap
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% % Erosion
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% erodemask = ones(erode_size);
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% maskxy = erode_own(maskxy,erodemask);
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%
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% % Dilation
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% dilatemask = ones(dilate_size);
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% maskxy = dilate_own(maskxy,dilatemask);
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maskxy = close_own(maskxy,ones(close_size));
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maskxy = open_own(maskxy,ones(open_size));
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mask = mask&maskxy;
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if show_bivariate > 0
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figure(show_bivariate);
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imagesc(log10(N));
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colormap franzmap
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end
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end
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function imout = erode_own(im,erodemask)
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% My own erosion to avoid using Image Processing Toolbox
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% Receives a binary image and kernel and performs erosion of the image
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erodemask = erodemask/sum(erodemask(:));
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imout = conv2(double(im),erodemask,'same');
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imout = imout>0.99999;
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end
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function imout = dilate_own(im,dilatemask)
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% My own dilation to avoid using Image Processing Toolbox
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% Receives a binary image and kernel and performs erosion of the image
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dilatemask = dilatemask/sum(dilatemask(:));
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imout = conv2(double(im),dilatemask,'same');
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imout = imout>0;
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end
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function imout = open_own(im,openmask)
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imout = dilate_own(erode_own(im,openmask),openmask);
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end
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function imout = close_own(im,closemask)
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imout = erode_own(dilate_own(im,closemask),closemask);
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end
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function [histout, C] = hist3_own(gaux,bins)
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eps = 0.001; % esther
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min_gaux1 = min(gaux(:,1));
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max_gaux1 = max(gaux(:,1));
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inter_1 = (max_gaux1-min_gaux1)/bins(1);
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min_gaux2 = min(gaux(:,2));
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max_gaux2 = max(gaux(:,2));
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inter_2 = (max_gaux2-min_gaux2)/bins(2);
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indarray1 = floor( (1-eps)*bins(1)*( gaux(:,1)-min_gaux1 )./( max_gaux1-min_gaux1 ) + 1 );
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indarray2 = floor( (1-eps)*bins(2)*( gaux(:,2)-min_gaux2 )./( max_gaux2-min_gaux2 ) + 1 );
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histout = zeros(bins);
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for ii = 1:numel(indarray1)
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histout(indarray1(ii),indarray2(ii)) = histout(indarray1(ii),indarray2(ii)) + 1;
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end
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C{1} = linspace(min_gaux1+inter_1/2,max_gaux1-inter_1/2,bins(1));
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C{2} = linspace(min_gaux2+inter_2/2,max_gaux2-inter_2/2,bins(2));
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end
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