% 'ima_remove_particles': removes particles from an image (keeping the local minimum) % requires the Matlab image processing toolbox %------------------------------------------------------------------------ %%%% Use the general syntax for transform fields with a single input %%%% % OUTPUT: % DataOut: output field structure % %INPUT: % DataIn: first input field structure %======================================================================= % Copyright 2008-2014, LEGI UMR 5519 / CNRS UJF G-INP, Grenoble, France % http://www.legi.grenoble-inp.fr % Joel.Sommeria - Joel.Sommeria (A) legi.cnrs.fr % % This file is part of the toolbox UVMAT. % % UVMAT is free software; you can redistribute it and/or modify % it under the terms of the GNU General Public License as published % by the Free Software Foundation; either version 2 of the license, % or (at your option) any later version. % % UVMAT is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License (see LICENSE.txt) for more details. %======================================================================= function DataOut=ima_remove_particles(DataIn) %------------------------------------------------------------------------ DataOut=[]; %default output field if strcmp(DataIn,'*') return end %parameters threshold=200; nblock_x=30;%size of image subblocks for analysis nblock_y=30; %--------------------------------------------------------- DataOut=DataIn;%default if ~isfield(DataIn,'A') DataOut.Txt='remove_particles only valid for input images'; return end %BACKGROUND LEVEL Atype=class(DataIn.A); A=double(DataIn.A); Backg=zeros(size(A)); Aflagmin=sparse(imregionalmin(A));%Amin=1 for local image minima Amin=A.*Aflagmin;%values of A at local minima % local background: find all the local minima in image subblocks sumblock= inline('sum(sum(x(:)))'); Backg=blkproc(Amin,[nblock_y nblock_x],sumblock);% take the sum in blocks Bmin=blkproc(Aflagmin,[nblock_y nblock_x],sumblock);% find the number of minima in blocks Backg=Backg./Bmin; % find the average of minima in blocks B=imresize(Backg,size(A),'bilinear');% interpolate to the initial size image ImPart=(A-B); ImPart=ImPart.*(ImPart>threshold); DataOut.A=A-ImPart;% DataOut.A=feval(Atype,DataOut.A);