MATLAB: 7×7 arithmetic mean filter

blurringImage Processing Toolboxmanual convolutionmeanfilterspatial filtering

How can I apply 7×7 arithmetic mean filter to following image?

Best Answer

You can do this:

windowWidth = 7;
kernel = ones(windowWidth) / windowWidth^2;
outputImage = imfilter(grayImage, kernel);

If you use conv2() you'll need to make sure your input image is not of integer class, so cast it to double first:

outputImage = conv2(double(grayImage), kernel, 'same');

imfilter() does not require casting to double in advance. Also imfilter() does not flip the kernel like convolution does, though for a symmetric filter like this box filter, it doesn't matter if it's flipped or not.

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MATLAB: Trying to do retinal vessel segmentation with mean-c thresholding

You are converting a double image to uint8 format due to which you are unable to visualize the segmentation. Keep in double format. For example, run the below code:

%objective : retinal blood vessel segmentation with thresholding
%%Pre-Processing%%

I=imread('image.png');
subplot(2,2,1),imshow(I);
title('a');
%green channel image
greenI=I(:,:,2);
subplot(2,2,2),imshow(greenI);
title('b');
%CLAHE
clahed = adapthisteq(greenI);
subplot(2,2,3),imshow(clahed);
title('c');
%median filter
medfiltered=medfilt2(clahed);
subplot(2,2,4),imshow(medfiltered);
title('d');
%%Pre-Processing%%
%%Segmentation%%
%create a 13x13 mean filter
meanfilter=[1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1;1 1 1 1 1 1 1 1 1 1 1 1 1]/169;
%convolve the enhanced image with mean filter
meanfiltered=(conv2(medfiltered,meanfilter,'same'));
figure,imshow(meanfiltered);
title('meanfiltered');
diff=double(medfiltered)-meanfiltered;
figure,imshow(diff);
title('difference');
%threshold the image with C = 0.042
thresholded = imbinarize(diff,-15);  %%%%% check will other threshold
%complement the thresholded image
complemented = imcomplement(thresholded);
figure,imshow(complemented);

You will get the image as given below. After this, try to apply some morphological operation to remove the smaller component. Also, check with the algorithm if it is correct or not. Hope it will help!

Best Answer

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