filter2D function error

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I supposed was the function getGaussianKernel() but I don t know how to se t his paramethers :ksize and sigma. I suppose the ktype must be the same of the input array of filter2D

sigma you can set to -1, then the ideal sigma to your kernel size is computed, thus the larger you chose the kernel to be the larger you'll blur/smooth your image. Kernel-type can be different from the destination-image-depth (ddepth) of filter2d, see http://docs.opencv.org/modules/imgproc/doc/filtering.html?highlight=blur#filter2d

What I have to do is translating from Matlab:

GaussKernel=fspecial('gaussian',maxhw,sigma);

conspic=filter2(GaussKernel,conspic,'same'); //Gaussian snoothing in each orientation

What I did is:

GaussianBlur(maxhw,GaussKernel,Size(0,0),1,1,BORDER_DEFAULT;

//setting 1,1 ; i m setting the Gaussian kernel standard deviation as the paramether sigma in Matlab first line

filter2D(GaussKernel,conspic1,GaussKernel.depth(),split(GaussKernel,KernelAchrSplit),Point(-1,-1),0,BORDER_DEFAULT); //I know I don t have to use split for the kernel paramether, but I suppose I have to use GaussKernel Mat object's kernel and I don t know how get it

So can you help me with the code of second line? Is it better I use getGaussianKernel doing something like: ilter2D(GaussKernel,conspic1,GaussKernel.depth(),getGaussianKernel(5,-1.0,GaussKernel.type()),Point(-1,-1),0,BORDER_DEFAULT) How I have to set the getGaussianKernel's paramether?

I can only point to my original post. EITHER use GaussianBlur OR use getGaussianKernel together with filter2D, i.e. your last comment should be correct and you can omit your other lines of your second last comment.

MATLAB CODE : %Softening Gaussian filter % Gaussian parameters as functions of image size

   maxhw = max(0,floor(min(r/2,c/2) - 1));  
   sigma = max(r,c)*0.025; 
   GaussKernel=fspecial('gaussian',maxhw,sigma); 

     % Gaussian smoothing in each orientation 
     conspic=filter2(GaussKernel,conspic,'same'); 
     conspic1 = conspic1 + conspic;

C++ CODE just: GaussianBlur(maxhw,GaussKernel,Size(0,0),1,1,BORDER_DEFAULT);

Right? P.S. Thanks to help me!

You are pretty close, however try to read the documentation better. GaussianBlur wants the input image as first parameter, the output image as second parameter, the kernel-size as third (that is maxhw) and the sigma as fourth parameter (for the other parameters you can leave the default-parameters), i.e. it follows:

GaussianBlur(input_img, blurred_output_img, Size(maxhw,maxhw), sigma);

of course you have to compute maxhw and sigma as in the matlab implementation. I hope it is clear now! Please also mark the answer as solved.

      maxhw=max(0,(int)floor(min(r/2,c/2) - 1));
      sigma = max(r,c)*0.025;
      GaussianBlur=(conspic,conspic,Size(maxhw,maxhw),sigma,sigma,BORDER_DEFAULT);
      conspic1=conspic1+conspic

for i_orient =1: achrOrient

stack=cat(3,resp{i_orient,:});
inComp=reshape(stack,r*c,achrScales)
Tsquared=whitening_sqr_meanDistance(inComp);
conspic=(reshape(Tsquared,r,c));
  % Gaussian softening of orientation conspicuities
conspic=conspic/max(conspic(:));

   % Softening Gaussian filter
   % Gaussian parameters as functions of image size 
maxhw=max(0,floor(min(r/2,c/2) - 1));
sigma=max(r,c)*0.025;
GaussKernel=fspecial('gaussian',maxhw,sigma);
     % Gaussian snoothing in each orientation
 conspic=filter2(GaussKernel,conspic,'same');
 conspic1=conspic1+conspic;
   end

conspic1=conspic1/max(conspic1(:));
conspic1=filter2(GaussKernel,conspic1,'same');

I suppose that what I wrote (thanks to you) is right,but now I have doubt for the second filter2 it use, I have to use another time GaussianBlur? This is the Chromatic Saliency of a picture, after I work fot the Achromatic Saliceny and it use in matlab filter2 2 times for the softening.So what have I to use to the other filter2 functions. I have some problems to translate stack=cat(3,resp{i_orient,:});

Sorry for all this problems I m giving to you and thanks for helps