[950]  1  % 'ima_remove_background': removes backgound from an image (using the local minimum)


 2  % requires the Matlab image processing toolbox


 3  %


 4  %%%% Use the general syntax for transform fields with a single input %%%%


 5  % OUTPUT:


 6  % DataOut: output field structure


 7  %


 8  %INPUT:


 9  % DataIn: first input field structure


 10 


[810]  11  %=======================================================================


[1093]  12  % Copyright 20082021, LEGI UMR 5519 / CNRS UGA GINP, Grenoble, France


[810]  13  % http://www.legi.grenobleinp.fr


 14  % Joel.Sommeria  Joel.Sommeria (A) legi.cnrs.fr


 15  %


 16  % This file is part of the toolbox UVMAT.


 17  %


 18  % UVMAT is free software; you can redistribute it and/or modify


 19  % it under the terms of the GNU General Public License as published


 20  % by the Free Software Foundation; either version 2 of the license,


 21  % or (at your option) any later version.


 22  %


 23  % UVMAT is distributed in the hope that it will be useful,


 24  % but WITHOUT ANY WARRANTY; without even the implied warranty of


 25  % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the


 26  % GNU General Public License (see LICENSE.txt) for more details.


 27  %=======================================================================


 28 


[950]  29  function DataOut=ima_remove_background_blocks(DataIn,Param)


 30  %


 31  %% request input parameters


 32  if isfield(DataIn,'Action') && isfield(DataIn.Action,'RUN') && isequal(DataIn.Action.RUN,0)


 33  prompt = {'block size(pixels)'};


 34  dlg_title = 'get the block size (in pixels) used to calculate the local statistics';


 35  num_lines= 1;


 36  def = { '100'};


 37  if isfield(Param,'TransformInput')&&isfield(Param.TransformInput,'BlockSize')


 38  def={num2str(Param.TransformInput.BlockSize)};


 39  end


 40  answer = inputdlg(prompt,dlg_title,num_lines,def);


 41  DataOut.TransformInput.BlockSize=str2num(answer{1});


[574]  42  return


 43  end


[950]  44  if ~isfield(DataIn,'A')


 45  DataOut.Txt='remove_particles only valid for input images';


 46  return


 47  end


 48  if ~exist('imerode','file');


 49  DataOut.Txt='the function imerode from the image processing toolbox is needed';


 50  return


 51  end


 52 


[574]  53  %


 54  DataOut=DataIn;%default


[950]  55  nblock_y=2*Param.TransformInput.BlockSize;


 56  nblock_x=2*Param.TransformInput.BlockSize;


 57  [npy,npx]=size(DataIn.A);


 58  [X,Y]=meshgrid(1:npx,1:npy);


[574]  59 


[950]  60  %BACKGROUND LEVEL


 61  Atype=class(DataIn.A);


 62  A=double(DataIn.A);


 63  %Backg=zeros(size(A));


 64  %Aflagmin=sparse(imregionalmin(A));%Amin=1 for local image minima


 65  %Amin=A.*Aflagmin;%values of A at local minima


 66  % local background: find all the local minima in image subblocks


 67  fctblock= inline('median(x(:))');


 68  Backg=blkproc(A,[nblock_y nblock_x],fctblock);% take the median in blocks


 69  fctblock= inline('mean(x(:))');


 70  B=imresize(Backg,size(A),'bilinear');% interpolate to the initial size image


[1097]  71  DataOut.A=B;


 72 


 73  % A=(AB);%substract background


 74  % AMean=blkproc(A,[nblock_y nblock_x],fctblock);% take the mean in blocks


 75  % fctblock= inline('var(x(:))');


 76  % AVar=blkproc(A,[nblock_y nblock_x],fctblock);% take the mean in blocks


 77  % Avalue=AVar./AMean;% typical value of particle luminosity


 78  % Avalue=imresize(Avalue,size(A),'bilinear');% interpolate to the initial size image


 79  % DataOut.A=uint16(1000*tanh(A./(2*Avalue)));


[950]  80  %Bmin=blkproc(Aflagmin,[nblock_y nblock_x],sumblock);% find the number of minima in blocks


 81  %Backg=Backg./Bmin; % find the average of minima in blocks


[574]  82 


 83 


[1097]  84 


 85 

