% 'ima_noise_rms': gives the variance of relative noise by difference to the % filered image in ppm (part per million) (for grey scale image) %------------------------------------------------------------------------ %%%% Use the general syntax for transform fields with a single input and parameters %%%% % OUTPUT: % DataOut: output field structure % %INPUT: % DataIn: input field structure % Param: matlab structure whose field Param.TransformInput contains the filter parameters %======================================================================= % Copyright 2008-2017, LEGI UMR 5519 / CNRS UGA 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_noise_rms(DataIn,Param) %% request input parameters if isfield(DataIn,'Action') && isfield(DataIn.Action,'RUN') && isequal(DataIn.Action.RUN,0) prompt = {'npx';'npy'}; dlg_title = 'get the filter size in x and y'; num_lines= 2; def = { '20';'20'}; if isfield(Param,'TransformInput')&&isfield(Param.TransformInput,'FilterBoxSize_x')&&... isfield(Param.TransformInput,'FilterBoxSize_y') def={num2str(Param.TransformInput.FilterBoxSize_x);num2str(Param.TransformInput.FilterBoxSize_y)}; end answer = inputdlg(prompt,dlg_title,num_lines,def); DataOut.TransformInput.FilterBoxSize_x=str2num(answer{1}); %size of the filtering window DataOut.TransformInput.FilterBoxSize_y=str2num(answer{2}); %size of the filtering window return end DataOut=DataIn; %default %definition of the cos shape matrix filter ix=[1/2-Param.TransformInput.FilterBoxSize_x/2:-1/2+Param.TransformInput.FilterBoxSize_x/2];% iy=[1/2-Param.TransformInput.FilterBoxSize_y/2:-1/2+Param.TransformInput.FilterBoxSize_y/2];% %del=np/3; %fct=exp(-(ix/del).^2); fct2_x=cos(ix/((Param.TransformInput.FilterBoxSize_x-1)/2)*pi/2); fct2_y=cos(iy/((Param.TransformInput.FilterBoxSize_y-1)/2)*pi/2); %Mfiltre=(ones(5,5)/5^2); Mfiltre=fct2_y'*fct2_x; Mfiltre=Mfiltre/(sum(sum(Mfiltre)));%normalize filter Atype=class(DataIn.A);% detect integer 8 or 16 bits B=filter2(Mfiltre,DataIn.A); B(B==0)=1; %set to 1 the zero values C=(double(DataIn.A)-B)./B; C=filter2(Mfiltre,C.*C);% take variance integrated in the filtering area C=1000000*sqrt(C); % take the root and *10^6 to get an image with integer values (parts per million) DataOut.A=feval(Atype,C);%transform to the initial image format