I need to compute a background model using the information below can someone please help me in understanding and implementing the idea below

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Maria 2012-8-2

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To compute this background model all of the pixels in the image are histogrammed-namely, for each pixel its color intensity is placed in the proper bin of a preferred possible 256 intensity levels. This is preferably done for each of the red, green and blue (RGB) channels thus generating three separate histograms. Alternately, one histogram could be generated using some joint space rep- resentation of the channels. Once the histogram has been computed, a Gaussian distribution for each histogram is calculated to provide the mean pixel intensity of the background and the vari- ance.

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Answer 1

Image Analyst 2012-8-2

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编辑：Image Analyst 2012-8-2

在 MATLAB Online 中打开

Depends on what your background image is. I use polyfitn ( http://www.mathworks.com/matlabcentral/fileexchange/34765-polyfitn) to get a smooth illumination profile that I can use to correct for non-uniform lighting. But if you had, say a street scene with a bunch of people on it, then you wouldn't use that method, you'd take the mode or use GMM models or something.

I don't see how your proposed method would work at all. I don't even know what it does, except maybe get the mean color of the image, but you don't need to fit histograms to Gaussians to do that, or even to take histograms at all. Basically your method is just the same as:

meanRedValue = mean(rgbImage(:,:,1));
meanGreenValue = mean(rgbImage(:,:,2));
meanBlueValue = mean(rgbImage(:,:,3));

That's all your algorithm does, which is not even as locally adaptive as a blurring with conv2(). That's not really background correction at all.

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Maria 2012-8-2

编辑：Maria 2012-8-4

在 MATLAB Online 中打开

like this?

rgbImage=imread(images);

[rows columns numberOfColorBands] = size(rgbImage);

%I am using loop to to initialize with 0 in spite of using zeros function because the index starts with 1 by default

for i=1:256

   rhistogram(i)=0;
   ghistogram(i)=0;
   bhistogram(i)=0;

end

for i=1:rows

    for j=1:columns
        % this can also be done using rgbvalues=impixel(rgbImage,j,i);
        %r=pixel(1);g=pixel(2);b=pixel(3);
        r=rgbImage(i,j,1);
        g=rgbImage(i,j,2);
        b=rgbImage(i,j,3);
        if r==0
            r=256;
            rhistogram(r)=rhistogram(r)+1;
       else
            rhistogram(r)=rhistogram(r)+1;
        end
        if g==0
            g=256;
            ghistogram(g)=ghistogram(g)+1;
      else
            ghistogram(g)=ghistogram(g)+1;
        end
        if b==0
            b=256;
            bhistogram(b)=bhistogram(g)+1;
       else
            bhistogram(b)=bhistogram(g)+1;
        end
    end
end
lastCol=rhistogram(columns);

rhistogram=rhistogram(1:columns-1);

rhistogram=[lastCol rhistogram];

lastCol=ghistogram(columns);

ghistogram=ghistogram(1:columns-1);

ghistogram=[lastCol ghistogram];

lastCol=bhistogram(columns);

bhistogram=bhistogram(1:columns-1);

bhistogram=[lastCol bhistogram];

imhist(rhistogram);

imhist(ghistogram);

imhist(bhistogram); If I have to do for multiple images how do I have do I mean would I be continuing incrementing values in same arrays or concatenate the previous values into other variable.And what is the next step after this?

Maria 2012-8-4

Can you give me a complete code for this since I am completely blank now.I need to do this for couple of images not for a single image. I have lets say 10 images and I have to compute background model this way using all 10 images.