[783]  1  % 'ima_noise_rms': gives the variance of relative noise by difference to the


 2  % filered image in ppm (part per million) (for grey scale image)


 3  %


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


 5  % OUTPUT:


 6  % DataOut: output field structure


[810]  7  %


[783]  8  %INPUT:


 9  % DataIn: input field structure


 10  % Param: matlab structure whose field Param.TransformInput contains the filter parameters


 11 


[810]  12  %=======================================================================


[908]  13  % Copyright 20082015, LEGI UMR 5519 / CNRS UJF GINP, Grenoble, France


[810]  14  % http://www.legi.grenobleinp.fr


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


 16  %


 17  % This file is part of the toolbox UVMAT.


 18  %


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


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


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


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


 23  %


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


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


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


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


 28  %=======================================================================


 29 


[783]  30  function DataOut=ima_noise_rms(DataIn,Param)


 31 


 32  %% request input parameters


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


 34  prompt = {'npx';'npy'};


 35  dlg_title = 'get the filter size in x and y';


 36  num_lines= 2;


 37  def = { '20';'20'};


 38  if isfield(Param,'TransformInput')&&isfield(Param.TransformInput,'FilterBoxSize_x')&&...


 39  isfield(Param.TransformInput,'FilterBoxSize_y')


 40  def={num2str(Param.TransformInput.FilterBoxSize_x);num2str(Param.TransformInput.FilterBoxSize_y)};


 41  end


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


 43  DataOut.TransformInput.FilterBoxSize_x=str2num(answer{1}); %size of the filtering window


 44  DataOut.TransformInput.FilterBoxSize_y=str2num(answer{2}); %size of the filtering window


 45  return


 46  end


 47 


 48  DataOut=DataIn; %default


 49 


 50  %definition of the cos shape matrix filter


 51  ix=[1/2Param.TransformInput.FilterBoxSize_x/2:1/2+Param.TransformInput.FilterBoxSize_x/2];%


 52  iy=[1/2Param.TransformInput.FilterBoxSize_y/2:1/2+Param.TransformInput.FilterBoxSize_y/2];%


 53  %del=np/3;


 54  %fct=exp((ix/del).^2);


 55  fct2_x=cos(ix/((Param.TransformInput.FilterBoxSize_x1)/2)*pi/2);


 56  fct2_y=cos(iy/((Param.TransformInput.FilterBoxSize_y1)/2)*pi/2);


 57  %Mfiltre=(ones(5,5)/5^2);


 58  Mfiltre=fct2_y'*fct2_x;


 59  Mfiltre=Mfiltre/(sum(sum(Mfiltre)));%normalize filter


 60 


 61  Atype=class(DataIn.A);% detect integer 8 or 16 bits


 62  B=filter2(Mfiltre,DataIn.A);


 63  B(B==0)=1; %set to 1 the zero values


 64  C=(double(DataIn.A)B)./B;


 65  C=filter2(Mfiltre,C.*C);% take variance integrated in the filtering area


 66  C=1000000*sqrt(C); % take the root and *10^6 to get an image with integer values (parts per million)


 67  DataOut.A=feval(Atype,C);%transform to the initial image format


 68 


 69 


[810]  70 

