How can blur an image

Write a function called blur that blurs the input image. The function is to be called like this:

output = blur(img,w);

where img, the input image is a two-dimensional matrix of grayscale pixel values between 0 and 255. Blurring is to be carried out by averaging the pixel values in the vicinity of every pixel. Specifically, the output pixel value is the mean of the pixels in a square submatrix of size 2w+1 where the given pixel sits in the center. For example, if w is 1, then we use a 3x3 matrix, that is, we average all the neighboring pixels of the given pixel and itself. Only use valid pixels when portions of the blurring matrix fall outside the image. For example, the blurred value corresponding to w = 1 at index (1,1) would be the mean of of elements (1,1), (1, 2), (2,1) and (2, 2). Both input img and output output are of type uint8.

You can download the test image here to use in MATLAB.

[Jorge Ortiz]

function [output] = blur(A,w)
[row col] = size(A);
A=uint8(A);
B=nan(size(A) + (2*w));
B(w+1:end-w,w+1:end-w)=A;
output = 0*A;
for i=w+1:row+w
  for j=w+1:col+w
    tmp=B(i-w:i+w,j-w:j+w);
    output(i-w,j-w)=mean(tmp(~isnan(tmp)));
  end
end
output=uint8(output);

[Jorge Ortiz]

[Priyamvada Shankar]

Thank you very much... I got it where I went wrong

[Xenium Adil]

hey guys i have done almost the whole course but i am stuck at that sparse2matrix assignment plz somebody help me out........

[Jorge Ortiz]

What's the question?

[Oyedamola ASIYANBOLA]

Sparse Matrix was quite tricky, as you have to make your code robust to handle alot of input

function matrix = sparse2matrix(cellvec)
r= cellvec{1}(1); c= cellvec{1}(2);
matrix = zeros(r, c) +  cellvec{2};
i =3;
while i <= size(cellvec, 2)
    j=1;
    matrix(cellvec{i}(j),cellvec{i}(j+1)) = cellvec{i}(j+2);
    i = i+1;
end
end

[Fahim MUMAND]

If anyone has solved this problem, please share the hints or solution.

[Image Analyst]

I solved it in my Answer in two different ways. Scroll down to see my Answer.

[Raghav Gupta]

Is it possible to solve this problem using a single for loop?

[Image Analyst]

Yes but it would be a lot harder, and no faster.

[Sana Hafeez]

@Jorge Ortiz please guide me. by using that code i cannot solved my assignment

[Image Analyst]

@Sana Hafeez, post your code and image in a new thread if you can't solve it using any of the code in the answers below.

[Sana Hafeez]

[Sana Hafeez]

[Sana Hafeez]

[Sana Hafeez]

[Image Analyst]

@Sana Hafeez, do what it says and swap lines 12 and 13.

https://www.mathworks.com/matlabcentral/answers/450356-how-can-blur-an-image#comment_1560015

TUTORIAL: How to ask a question (on Answers) and get a fast answer

[Sana Hafeez]

Please send me a correct code.

[Walter Roberson]

Delete the end on line 12. Add an end statement after the assignment statement.

Image Analyst and I have better things to do with our time then to type in code from an image of code just to exchange two lines.

By the way: you have not defined unit8

[Sana Hafeez]

Please guide what method that used to defined unit 8

still I am stucked

I am tired now

anyone please help me.......

Thanks in Advance!

[Walter Roberson]

uint8() not unit8()

[Image Analyst]

You know, there is a little double page icon in the upper left of the code blocks so that you can copy the code. The code blocks I see here all have uint8(), not unit8(). If you had copied, you would not have had that problem.

[Sana Hafeez]

Thank you so much

Answer 1

[Dipesh Poudel]

function [output] = blur(A,w)
[row col] = size(A);
A=uint8(A);
B=nan(size(A) + (2*w));
B(w+1:end-w,w+1:end-w)=A;
output = 0*A;
for i=w+1:row+w
  for j=w+1:col+w
    tmp=B(i-w:i+w,j-w:j+w);
    output(i-w,j-w)=mean(tmp(~isnan(tmp)));
  end
end
output=uint8(output);

[Mohammed Shahin P]

output(i-w,j-w)=mean(tmp(~isnan(tmp)))

can anyone explain this statement of the code

[Image Analyst]

It takes the mean of the small tmp window but only for valid values, not NaN values (which should normally not be any). There is a new flag for mean, 'omitnan', so the newest way of doing that would be

output(i - w, j - w)  = mean(tmp(:), 'omitnan');

It then assigns the mean of the window to the output at the cirrent location of the center of the window.

I've corrected a number of errors in that code, and made it more robust. The corrected code is shown below. Though you'd probably be better off using the code in my Answer instead.

% grayImage is the input image.  It may be of any type (uint8, uint16, single, double).
% w is the window width of the scanning filter.
function output = blur(grayImage, w)
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage);
% Make sure it's a gray scale image, not a color image.
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	% Use weighted sum of ALL channels to create a gray scale image.
	grayImage = rgb2gray(grayImage);
	% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
	% which in a typical snapshot will be the least noisy channel.
	% grayImage = grayImage(:, :, 2); % Take green channel.
end
B = nan(size(grayImage) + (2*w)); % Make B larger, padding with NaNs.
B(w+1:end-w, w+1:end-w) = grayImage; % Make central part of B match A.
output = double(grayImage); % Initialize a double array for the output with the size and values of the input.
% Scan the window over the image making the output the average of the input at each pixel location.
for row = w+1:rows+w
	for col = w+1:columns+w
		% Extract the part of the image under the window at the window's current location.
		tmp = B(row-w:row+w, col-w:col+w);
		% Replace the output's value there with the mean of the input.
		output(row-w, col-w) = mean(tmp(:), 'omitnan');
	end
end
% Cast output image to be the same class (uint8, uint16, single, or double) as the input image.
output = cast(output, 'like', grayImage);

[Sourabh Bhange]

clc;

A = imread('xyz.bmp');
B = rgb2gray(A);

A2 = MyBlur(A,2);
B2 = MyBlur(B,2);

subplot(2, 2, 1), imshow(A), title('A');
subplot(2, 2, 2), imshow(B), title('B');
subplot(2, 2, 3), imshow(A2), title('A2');
subplot(2, 2, 4), imshow(B2), title('B2');

How can I modify MyBlur function so it will blur the images without converting to rgb2gray??

[Image Analyst]

Do it one channel at a time

% Split into separate color channels.
[redChannel, greenChannel, blueChannel] = imsplit(A);
% Blur each color channel independently.
blurredR = MyBlur(redChannel, 2);
blurredG = MyBlur(greenChannel, 2);
blurredB = MyBlur(blueChannel, 2);
% Recombine into a single RGB image.
blurredRGBImage = cat(3, blurredR, blurredG, blurredB);

[Sourabh Bhange]

Hello, Thank you for the reply.

Using the function you suggested:

function output = blur(grayImage, w)
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage);
% Make sure it's a gray scale image, not a color image.
if numberOfColorChannels > 1
    % It's not really gray scale like we expected - it's color.
    % Use weighted sum of ALL channels to create a gray scale image.
    grayImage = rgb2gray(grayImage);
    % ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
    % which in a typical snapshot will be the least noisy channel.
    % grayImage = grayImage(:, :, 2); % Take green channel.
end
B = nan(size(grayImage) + (2*w)); % Make B larger, padding with NaNs.
B(w+1:end-w, w+1:end-w) = grayImage; % Make central part of B match A.
output = double(grayImage); % Initialize a double array for the output with the size and values of the input.
% Scan the window over the image making the output the average of the input at each pixel location.
for row = w+1:rows+w
    for col = w+1:columns+w
        % Extract the part of the image under the window at the window's current location.
        tmp = B(row-w:row+w, col-w:col+w);
        % Replace the output's value there with the mean of the input.
        output(row-w, col-w) = mean(tmp(:), 'omitnan');
    end
end
% Cast output image to be the same class (uint8, uint16, single, or double) as the input image.
output = cast(output, 'like', grayImage);

When I used in my code I am able to convert rgb2gray and gray2blur.

How I can modify this function if I want to conver rgb2blur?

[Image Analyst]

Your MyBlur() function, which takes an RGB image needs to call imsplit() and call your blur(), which deals with monochrome images:

function blurredRGBImage = MyBlur(rgbImage, windowWidth)
% Split into separate color channels.
[redChannel, greenChannel, blueChannel] = imsplit(rgbImage);
% Blur each color channel independently.
blurredR = blur(redChannel, windowWidth);
blurredG = blur(greenChannel, windowWidth);
blurredB = blur(blueChannel, windowWidth);
% Recombine into a single RGB image.
blurredRGBImage = cat(3, blurredR, blurredG, blurredB);

Then call it:

rgbImage = imread('peppers.png');
blurredRGBImage = uint8(MyBlur(rgbImage, 9));
imshow(blurredRGBImage)

Answer 2

[Yaksha SJ]

function out = blur(img,w)
    % convert to double for doing calculations
    imgD = double(img);
    [row, col] = size(img);
    out = zeros(row, col);
    for ii = 1:row
        for jj = 1:col
            % Get the indices for a submatrix
            r1 = ii-w;
            r2 = ii+w;
            c1 = jj-w;
            c2 = jj+w;
            % Test that indices are valid
            % If not, set to min/max that is valid
            if r1 < 1
                r1 = 1;
            end
            if r2 > row
                r2 = row;
            end
            if c1 < 1
                c1 = 1;
            end
            if c2 > col
                c2 = col;
            end
            % Get the submatrix and assign the mean to the output pixel
            m = imgD(r1:r2, c1:c2);
            out(ii,jj) = mean(m(:));
        end
    end
    % convert back to uint8
    out = uint8(out);
end

[Walter Roberson]

hint:

r1 = max(1, ii-w);

[Kartik agarwal]

Hey, if I produce this change in the last segment of your code, I am getting errors :

Original code :

% Get the submatrix and assign the mean to the output pixel

m = imgD(r1:r2, c1:c2);

out(ii,jj) = mean(m(:));

end

end

% convert back to uint8

out = uint8(out);

end

Changed code :

% Get the submatrix and assign the mean to the output pixel

m = imgD(r1:r2, c1:c2);

out(ii,jj) = uint8(mean(m(:))); % uint8 conversion done here itself%

end

end

end

The error says that Variable output must be of data type uint8. It is currently of type double.

I am new to Matlab. I can't understand the error in doing conversion the way I did in changed code. Please help

Answer 3

[KSSV]

I = imread('peppers.png') ;
for i = 1:3
    I(:,:,i) = uint8(conv2(I(:,:,i),ones(20)/20^2,'same'));
end
imshow(I) ;

[Image Analyst]

I think you mean

conv2(double(I(:,:,i)),ones(2*w+1)/(2*w+1)^2,'same') % Need to cast from uint8 to double in order to use conv2()

[Jorge Ortiz]

Already done!! Above in the question is the solution I chose.

Thank you very much anyway.

[Gloria Paul]

Hello Jorge, I really need help figuring this code out

[Image Analyst]

What code? Jorge's or KSSV's? Or one of the other multitude of places where code appears on this page?

Answer 4

[Image Analyst]

Can your function call the built-in functions conv2() or imfilter()?

If not, see, and adapt, my attached manual convolution program.

[Jorge Ortiz]

Already done!! Above in the question is the solution I chose.

Thank you very much anyway.

[Image Analyst]

Well the solution you chose is not very robust, but it will work in some cases, not all cases.

Answer 5

[Jaimin Motavar]

can someone help me to figure out what is wrong in this code?

function output = blur(img,w)
B=double(img);

[m,n] = size(B);
k=2*w+1;
for i = 1:m
    for j = 1:n
        p=i-fix(k/2);
        q=i+fix(k/2);
        r=j-fix(k/2);
        s=j+fix(k/2);
        if p<1
            p=1;
        end
        if q>m
            q=m;
        end
        if r<1
            r=1;
        end
        if s>n
            s=n;
        end
        A=B([p:q],[r:s]);
        B(i,j)=mean(A(:));
    end
end

output=uint8(B);
end

[KSSV]

It works fine...what problem you have?

[Jaimin Motavar]

it is not giving proper answer.

[Image Analyst]

Attach your images (input and blurred output) and say WHY it's not giving the proper answer.

[Namarta Kapil]

Can somebody please tell me what is wrong with this code? it gives the following error:

• Assessment result: incorrectSimple testVariable output has an incorrect value. Tested with a 5x5 uint8 matrix with all 255-s in the first and last rows and columns and zeros everywhere else and w = 1
• Assessment result: incorrectUsing image fileVariable output has an incorrect value. Tested with the vandy.png file and w = 1

[Walter Roberson]

You are overwriting your input data in B as you do the calculation, so your calculation is being based upon the already-smoothed pixels above and to the left instead of on the original pixels above and to the left.

Answer 6

[Brandon McLaughlin]

Help! I'm almost done with this course but for some reason I can't get this function to work. I have my code all set, but it keeps saying I'm doing it wrong. What am I doing wrong?

function output=blur(img,w)
img=double(img);
d=w*2+1
s=size(img)
output=[]
for r=1:d:s(1)
    row=[];
    for c=1:d:s(2)
        if r+w<=s(1) && c+w<=s(2) && r-w>=1 && c-w>=1
        tot=sum(sum(img((r-w):(r+w),(c-w):(c+w))));
        val=tot/(d*d);
        nxt=ones(d,d);
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif c+w<=s(2) && r-w>=1 && c-w>=1
            tot=sum(sum(img((r-w):end,(c-w):(c+w))));
        val=tot/(d*(s(1)-r+w));
        nxt=ones((s(1)-r+w),d);
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif r+w<=s(1) && r-w>=1 && c-w>=1
        tot=sum(sum(img((r-w):(r+w),(c-w):end)));
        val=tot/(d*(s(2)-c+w));
        nxt=ones(d,(s(2)-c+w));
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif r+w<=s(1) && c+w<=s(2) && r-w>=1
            tot=sum(sum(img((r-w):(r+w),1:(c+w))));
        val=tot/(d*(c+w));
        nxt=ones(d,(c+w));
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif r+w<=s(1) && c+w<=s(2) && c-w>=1
            tot=sum(sum(img(1:(r+w),(c-w):(c+w))));
        val=tot/(d*(r+w));
        nxt=ones((r+w),d);
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif r+w<=s(1) && c+w<=s(2)
            tot=sum(sum(img(1:(r+w),1:(c+w))));
        val=tot/((r+w)*(c+w));
        nxt=ones((c+w),(r+w));
        nxt(1:end,1:end)=val;
        row=[row nxt];
         elseif r-w>=1 && c-w>=1
        tot=sum(sum(img((r-w):end,(c-w):end)));
        val=tot/((s(1)-r+w)*(s(2)-c+w));
        nxt=ones((s(1)-r+w),(s(2)-c+w));
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif r+w<=s(1) && c-w>=1
        tot=sum(sum(img(1:(r+w),(c-w):end)));
        val=tot/((r+w)*(s(2)-c+w));
        nxt=ones((r+w),(s(2)-c+w));
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif c+w<=s(2) && r-w>=1
        tot=sum(sum(img((r-w):end,1:(c+w))));
        val=tot/((s(1)-r+w)*(c+w));
        nxt=ones((s(1)-r+w),(c+w));
        nxt(1:end,1:end)=val;
        row=[row nxt];        
        end
    end
    output=[output;row];
end
row=[]
s2=size(output)
if s2(1)<s(1)
    for c=1:d:s(2)
        if c+w<=s(2) && c-w>=1
        tot=sum(sum(img((s2(1)+1):s(1),(c-w):(c+w))));
        val=tot/((s(1)-s2(1))*d);
        nxt=ones((s(1)-s2(1)),d);
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif c+w<=s(2)
        tot=sum(sum(img((s2(1)+1):s(1),1:(c+w))));
        val=tot/((s(1)-s2(1))*(c+w));
        nxt=ones((s(1)-s2(1)),(c+w));
        nxt(1:end,1:end)=val;
        row=[row nxt];
        elseif c-w>=1
        tot=sum(sum(img((s2(1)+1):s(1),(c-w):end)));
        val=tot/((s(1)-s2(1))*(s2(2)-c+w));
        nxt=ones((s(1)-s2(1)),(s2(2)-c+w));
        nxt(1:end,1:end)=val;
        row=[row nxt];
        end
    end
    output=[output;row];
end
row=[]
col=[]
s3=size(output)
if s3(2)<s(2)
    for r=1:d:s(1)
        if r+w<=s(1) && r-w>=1
            tot=sum(sum(img((r-w):(r+w),(s3(2)+1):s(2))));
            val=tot/(d*(s(2)-s3(2)));
            nxt=ones(d,(s(2)-s3(2)));
            nxt(1:end,1:end)=val;
            col=[col;nxt];
        elseif r+w<=s(1)
            tot=sum(sum(img(1:(r+w),(s3(2)+1):s(2))));
            val=tot/((r+w)*(s(2)-s3(2)));
            nxt=ones((r+w),(s(2)-s3(2)));
            nxt(1:end,1:end)=val;
            col=[col;nxt];
        elseif r-w>=1
            tot=sum(sum(img((r-w):(r+w),(s3(2)+1):s(2))));
            val=tot/((s3(1)-r+w)*(s(2)-s3(2)));
            nxt=ones((s3(1)-r+w),(s(2)-s3(2)));
            nxt(1:end,1:end)=val;
            col=[col;nxt];
        end
    end
    s4=size(col)
    if s4(1)<s3(1) || s4(1)<s(1)
        tot=sum(sum(img((s2(1)+1):s(1),(s3(2)+1):s(2))));
        val=tot/((s(1)-s2(1))*(s(2)-s3(2)));
        nxt=ones((s(1)-s2(1)),(s(2)-s3(2)));
        nxt(1:end,1:end)=val;
        col=[col;nxt];
    end
    output=[output col];
end
output=uint8(output);

[Walter Roberson]

You asked that in https://www.mathworks.com/matlabcentral/answers/472917-i-cannot-pass-one-of-the-final-matlab-problems-on-the-coursera-matlab-course-what-is-wrong-with-my and I gave you some hints there.

[Brandon McLaughlin]

never mind i figured it out

[Image Analyst]

Glad you got it figured out.

Answer 7

[Image Analyst]

See my manual convolution routine, attached.

Answer 8

[shreyansh pitroda]

%% can some one find what is error in this code
function [output] = blur(img,w)
img = uint8(img);
[a,b] = size(img);
output = zeros(a,b);
h = 2*w+1;
for i = 1:a-h
    for j = 1:b-h
        value = img(i:(h+i-1),j:(h+j-1));
        output(i,j) = mean(value(:));
    end
end
output = uint8(output);
end

[Image Analyst]

Try this:

grayImage = imread('cameraman.tif');
hFig = figure;
subplot(1, 2, 1);
imshow(grayImage);
title('Original', 'FontSize', 20);
hFig.WindowState = 'maximized';
windowHalfWidth = 9;
output = blur(grayImage, windowHalfWidth);
subplot(1, 2, 2);
imshow(output);
title('Blurred', 'FontSize', 20);

% can some one find what is error in this code
function output = blur(img, w)
img = uint8(img);
[rows, columns] = size(img);
output = img; % Initialize output to be the same size as the input image.
h = 2 * w + 1;
fprintf('Filter is %d rows by %d columns.\n', h, h);
for col = h : columns-h
	for row = h : rows-h
		value = img(row : (h+row-1), col : (h+col-1));
		output(row, col) = mean(value(:));
	end
end
output = uint8(output);
end

[shreyansh pitroda]

still getting the same error

[Walter Roberson]

What error are you getting, on what inputs?

Note that your blur function will only work for grayscale images, not for RGB images.

[Sana Hafeez]

@Image Analyst by using that code still i getting an error

Please Help

Undefined function 'blur' for input arguments of type 'uint8'.

[Image Analyst]

@Sana Hafeez, post your code, because I just copied and pasted my code above and it works great. You must have defined blur() differently. Is it in the same file as your script, or a separate m-file. What does this show:

>> which -all blur

Again, here is my code that works perfectly fine.

grayImage = imread('cameraman.tif');
hFig = figure;
subplot(1, 2, 1);
imshow(grayImage);
title('Original', 'FontSize', 20);
hFig.WindowState = 'maximized';
windowHalfWidth = 9;
output = blur(grayImage, windowHalfWidth);
subplot(1, 2, 2);
imshow(output);
title('Blurred', 'FontSize', 20);

% can some one find what is error in this code
function output = blur(img, w)
img = uint8(img);
[rows, columns] = size(img);
output = img; % Initialize output to be the same size as the input image.
h = 2 * w + 1;
fprintf('Filter is %d rows by %d columns.\n', h, h);
for col = h : columns-h
	for row = h : rows-h
		value = img(row : (h+row-1), col : (h+col-1));
		output(row, col) = mean(value(:));
	end
end
output = uint8(output);
end

[Sana Hafeez]

Thanks a lot!!

Answer 9

[David Gonzalez]

function output = blur(img,w)
    mirror = -1*ones(size(img) + 2*w);
    mirror(w+1:end-w,w+1:end-w) = img;
    output = zeros(size(img));
    
    for ii = w+1:size(mirror,1)-w
        for jj = w+1:size(mirror,2)-w
            submatrix = mirror(ii-w:ii+w,jj-w:jj+w);
            sum_values = sum(submatrix(submatrix>=0));
            valid = sum(submatrix(:)>=0);
            output(ii-w,jj-w) = sum_values/valid;
        end
    end
    output = uint8(output);

Answer 10

[Divya Ratna]

i figured it out by myself...

i know its too lengthy..

function out = blur (img, w)
temp = img;
s = size(img);
if s(1) > w && s(2) > w
    %1
    for i = 1 : w
        for j = 1 : w
            temp (i,j) = sum(sum(img(1:i+w , 1:j+w))') / ((i+w)*(j+w));
        end
    end
    %2
    for i = 1 : w
        for j = w+1 : s(2)-w
            temp (i,j) = sum(sum(img(1:i+w , j-w:j+w))') / ((i+w)*(w+w+1));
        end
    end
    %3
    for i = 1 : w
        for j = s(2)-w+1 : s(2)
            temp (i,j) = sum(sum(img(1:i+w , j-w:s(2)))') / ((i+w)*(s(2)-j+1+w));
        end
    end
    %4
    for i = w+1 : s(1)-w
        for j = 1 : w
            temp (i,j) = sum(sum(img(i-w:i+w , 1:j+w))') / ((w+w+1)*(j+w));
        end
    end
    %5
    for i = w+1 : s(1)-w
        for j = w+1 : s(2)-w
            temp (i,j) = sum(sum(img(i-w:i+w , j-w:j+w))') / ((w+w+1)*(w+w+1));
        end
    end
    %6
    for i = w+1 : s(1)-w
        for j = s(2)-w+1 : s(2)
            temp (i,j) = sum(sum(img(i-w:i+w , j-w:s(2)))') / ((w+w+1)*(s(2)-j+1+w));
        end
    end
    %7
    for i = s(1)-w+1 : s(1)
        for j = 1 : w
            temp (i,j) = sum(sum(img(i-w:s(1) , 1:j+w))') / ((s(1)-i+1+w)*(j+w));
        end
    end
    %8
    for i = s(1)-w+1 : s(1)
        for j = w+1 : s(2)-w
            temp (i,j) = sum(sum(img(i-w:s(1) , j-w:j+w))') / ((s(1)-i+1+w)*(w+w+1));
        end
    end
    %9
    for i = s(1)-w+1 : s(1)
        for j = s(2)-w : s(2)
            temp (i,j) = sum(sum(img(i-w:s(1) , j-w:s(2)))') / ((s(1)-i+1+w)*(s(2)-j+1+w));
        end
    end
end
out = temp;
end

[para preethi]

This is not working

Answer 11

[Chandrashekhar Dhangar]

%can someone pls help with this?
%Error=Variable output has an incorrect value.
%Tested with a 5x5 uint8 matrix with all 255-s in the first and last rows and columns and zeros everywhere else and w = 1



function output=blur(img,w)
[m, n]=size(img);
im=double(img);
S=zeros(2*w+1,2*w+1);
out=zeros(m,n);
for i=1:m
    for j=1:n
        for u=1:2*w+1
            for v=1:2*w+1
                if i-w>0 && j-w>0 && i-w+u-1<=m && j-w+v-1<=n
                S(u,v)=im(i-w+u-1,j-w+v-1);
                else
                    S(u,v)=0;
                end
            end
        end
        out(i,j)=sum(S(:))/(2*w+1)^2;
    end
end
output=uint8(out);
end
            

[Image Analyst]

This ran without error for me:

img = zeros(5, 5, 'uint8');
img([1, end],:) = 255;
img(:, [1, end]) = 255
w = 1;
output=blur(img,w)

function output=blur(img,w)
[m, n]=size(img);
im=double(img);
S=zeros(2*w+1,2*w+1);
out=zeros(m,n);
for i=1:m
	for j=1:n
		for u=1:2*w+1
			for v=1:2*w+1
				if i-w>0 && j-w>0 && i-w+u-1<=m && j-w+v-1<=n
					S(u,v)=im(i-w+u-1,j-w+v-1);
				else
					S(u,v)=0;
				end
			end
		end
		out(i,j)=sum(S(:))/(2*w+1)^2;
	end
end
output=uint8(out);
end

[Chandrashekhar Dhangar]

Thanks for the response. Its working in Matlab software but showing the above error on website..

[Image Analyst]

Huh? What website? As you can see, the code does run without error but probably doesn't do what you expect.

[Chandrashekhar Dhangar]

I'm agree with you. But the code is doing what we expect here. It was an assignment on Coursera.com

[Image Analyst]

Look at the result:

img =
  5×5 uint8 matrix
   255   255   255   255   255
   255     0     0     0   255
   255     0     0     0   255
   255     0     0     0   255
   255   255   255   255   255
output =
  5×5 uint8 matrix
     0     0     0     0     0
     0   142    85   142   113
     0    85     0    85    85
     0   142    85   142   113
     0   113    85   113    85

You're going from row/col 2 to the very end. How are you supposed to handle edge effects? Were you supposed to replace the 255's on the top row with the average of the first two rows? Or were you supposed to leave it as 255? Were you supposed to compute the averages all the way to the end, or were you supposed to quit a line before the last row or column?

[Chandrashekhar Dhangar]

ohh sorry. Got it. Thanks a lot.

[Sana Hafeez]

@Image Analyst that code does not ran. Please help me I am tired to solve image blur problem...

[Sana Hafeez]

[Sana Hafeez]

Answer 12

[aniket GIRI]

function out = blur(img,w) 
% convert to double for doing calculations 
imgD = double(img); 
[row, col] = size(img);
out = zeros(row, col); 
for ii = 1:row 
    for jj = 1:col
        % Get the indices for a submatrix 
        r1 = ii-w;
        r2 = ii+w; 
        c1 = jj-w;
        c2 = jj+w;
        % Test that indices are valid % If not, set to min/max that is valid 
        if 1 < 1     
            r1 = 1; 
        end 
        if r2 > row 
            r2 = row; 
        end 
        if c1 < 1
            c1 = 1; 
        end 
        if c2 > col     
            c2 = col; 
        end 
        % Get the submatrix and assign the mean to the output pixel 
        m = imgD(r1:r2, c1:c2); 
        out(ii,jj) = mean(m(:)); 
    end 
end
% convert back to uint8 
out = uint8(out); 
end

[Deepthi Thomas]

This is the same image blur question that I'm trying

Here is my code

but I'm getting an error saying this:

Index exceeds the number of array elements (1).

Error in blur (line 11)

mean=mean(sub_matrix)

Can anyone tell me what's wrong with my code?

I have seen the solution above but Im still trying to modify my code since I dont want to copy paste the solution. So pls help if its possible to improve my code to get to the solution.

here is my code:

function output = blur(img,w)
    mean=0;
    img1=double(img);
    [r,c]=size(img1);
    
for row=1:r
    for col=1:c
        if row-w <=0 && col-w<=0 
            sub_matrix= img1(1:row+w, 1:col+w);
            mean=mean(sub_matrix);
        elseif row+w>= r && col+w>=c
            sub_matrix= img1(row-w:r,col-w:c);
            mean=mean(sub_matrix);
        elseif row-w<0 && col+w>=c
            sub_matrix=img1(1:row+w,col-w:c);
            mean=mean(sub_matrix);
        elseif row+w>=r && col-w<0
            sub_matrix=img1(row-w:r, col:col+w);
            mean=mean(sub_matrix);
        else 
            sub_matrix= img1(row-w:row+w,col-w:col+w);
            mean=mean(sub_matrix);
        end
    end
    output=uint8(mean);
end

[Walter Roberson]

            mean=mean(sub_matrix);

That replaces the function named mean() with a variable named mean . After you do that you can no longer use mean() as a function.

[Deepthi Thomas]

I changed the mean variable to another name 'mean1'. I checked with the debugger and the loop is running till row=1 and col=3.

But it then stops with another error message:

Index in position 1 is invalid. Array indices must be positive integers or logical values.

Error in blur (line 22)

sub_matrix= img1(row-w:row+w,col-w:col+w);

The sub_matrix remains a 3X4 double and the mean1 is a 1X1 double, 255, since I changed mean1= mean(sub_matrix(:)). But the debugger goes to the else statement and shows this error message.

[Image Analyst]

If row is 1, then row-w is zero or negative. You can't start at row 1 unless you check for the case where the window would be off the image, in which case you'd have to truncate the window. See my attached manual convolution.

Answer 13

[Josh Yaksich]

This is what I did and it worked. Please don't copy it directly, as you will only be hurting yourself. Hopefully it helps when deciding what approach to take:

function output = blur(img,w)
%save dimensions of img
y = size(img,1);
x = size(img,2);
%make a duplicate img for modification
imgdup = img;
%create a larger matrix of all -1's that's the same size as image plus a border 
bsquare = ones(y + 2 * w,x + 2 * w) * -1;
%copy img inside of larger matrix
bsquare((w + 1):end - w, w + 1:end - w) = img;
for i = 1:y
    for j = 1:x        
%make a small matrix for an individual pixel plus its surrounding pixels
        pixelraw = bsquare([i:2 * w + i],[j:2 * w + j]);
%calculate the average value in the small matrix while ignoring -1
        pixelavg = mean(pixelraw(pixelraw ~= -1));
%copy the average value to an individual pixel in the duplicate image
        imgdup(i,j) = pixelavg;     
    end
end
%convert duplicate image to unint8 and assign to output
output = uint8(imgdup);