source: trunk/src/transform_field/ima_remove_particles.m @ 897

Last change on this file since 897 was 897, checked in by sommeria, 9 years ago

sub_background corrected for volume and multilevel cases

File size: 2.5 KB
Line 
1% 'ima_remove_particles': removes particles from an image (keeping 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
11%=======================================================================
12% Copyright 2008-2014, LEGI UMR 5519 / CNRS UJF G-INP, Grenoble, France
13%   http://www.legi.grenoble-inp.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
29function DataOut=ima_remove_particles(DataIn)
30%------------------------------------------------------------------------
31DataOut=[];  %default  output field
32if strcmp(DataIn,'*')
33    return
34   
35end
36
37%parameters
38threshold=200;
39nblock_x=10;%size of image subblocks for analysis
40nblock_y=10;
41%---------------------------------------------------------
42DataOut=DataIn;%default
43
44if ~isfield(DataIn,'A')
45    DataOut.Txt='remove_particles only valid for input images';
46    return
47end
48
49%BACKGROUND LEVEL
50Atype=class(DataIn.A);
51A=double(DataIn.A);
52% Backg=zeros(size(A));
53Aflagmin=sparse(imregionalmin(A));%Amin=1 for local image minima
54Amin=A.*Aflagmin;%values of A at local minima
55% local background: find all the local minima in image subblocks
56sumblock= inline('sum(sum(x(:)))');
57Backg=blkproc(Amin,[nblock_y nblock_x],sumblock);% take the sum in  blocks
58Bmin=blkproc(Aflagmin,[nblock_y nblock_x],sumblock);% find the number of minima in blocks
59Backg=Backg./Bmin; % find the average of minima in blocks
60B=imresize(Backg,size(A),'bilinear');% interpolate to the initial size image
61DataOut.A=B;
62% ImPart=(A-B);
63% ImPart=ImPart.*(ImPart>threshold);
64% DataOut.A=A-ImPart;%
65DataOut.A=feval(Atype,DataOut.A);
66
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