how to avoid for loops or faster way for compute 3x3 avarage value of an image

I have a few pixels in an image and I want to calculate the average values ​​of a 3x3 window centred on those pixels in Matlab. It should be noted that not all over the image, just a few desired pixels.

I tried this code and it works but I prefer to avoid using for loops. Is there another way for doing that?

clc
clear
close all

img = imread('cameraman.tif');
x= [10,15,20];
y= [15,25,35];
m=-1;
n=-1;
window = zeros(3,3);
Avg = zeros(max(size(x)),1)
for k=1:max(size(x))
    for i = 1:3
        for j=1:3
            window(i,j) = img(x(k)+m,y(k)+n);
            n=n+1;
        end
        n=-1;
        m=m+1;
    end
    Avg(k) = mean(window,'all')
end

Answer 1

[Image Analyst]

If you're only doing it at 3 locations, don't worry about using for loops. It will be fast.

If you insist on using built-in functions to process the whole image, then...

Use imfilter():

kernel = ones(3)/9;
outputImage = imfilter(grayImage, kernel);

Or you can use conv2():

kernel = ones(3)/9;
outputImage = conv2(double(grayImage), kernel, 'same');

then you can reference outputImage(row, col) for the desired locations. Just be aware that y comes first, not x, so it's outputImage(y(1), x(1)), NOT outputImage(x(1), y(1)).

[ali eskandari]

Are you sure this works? I guess it's something else.

[ali eskandari]

For instance, I have some x&y positions and I want to compute a 3x3 avarage window around each pixel. Your code will do another thing.

[ali eskandari]

Thank you for your answer, the problem is that I have around 100 images and I want to apply this method on all of them and honestly there are more than three locations. Besides, I should add this code to other computations so the speed of computation is so important for me, that is why I am looking for a faster way. I just applyed it on one image to see how does it work.

[Image Analyst]

Try this:

grayImage = imread('cameraman.tif');
x = [10, 15, 20];
y = [15, 25, 35];
windowWidth = 3;
halfWidth = floor(windowWidth/2)
Avg = zeros(length(x), 1);
for k = 1 : length(x)
	% Convert x and y into row and column.
	row = y(k);
	col = x(k);
	% Get subimage centered about the (x, y) location.
	window = grayImage(row - halfWidth : row + halfWidth, col - halfWidth : col + halfWidth);
	% Compute the mean of that subimage.
	Avg(k) = mean(window,'all')
end

If you have more than a few thousand points in the images to inspect, then it's best to just filter the whole image with conv2() or imfilter() like I originally said, and pluck out the locations you want.

To process a sequence of images, see the FAQ.