Index: trunk/src/transform_field/ima_noise_rms.m
===================================================================
--- trunk/src/transform_field/ima_noise_rms.m	(revision 783)
+++ trunk/src/transform_field/ima_noise_rms.m	(revision 783)
@@ -0,0 +1,55 @@
+% '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
+%-----------------------------------
+
+%-------------------------------------
+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
+    
+
+