Array dimensions must match for binary array op.

Hi, im trying to do image noise redution using various low pass filter but i'm getting this error for most of the images i load. This error does not come when i use the cameraman.tif image and the coins.png image

This is the error:

Array dimensions must match for binary array op.

Error in Lowpassfull>gaussianLPFilter (line 81)

C=L.*Hi;

Error in Lowpassfull (line 23)

C=gaussianLPFilter(L,rows,columns);

THIS THE CODE:
clc;
clear;
close all;
im=im2double(imread('noisy.jpg')); % convert int double
im = imresize(im,[256,256]);
im = imnoise(im,'gaussian', 0.1);


subplot(3,3,1);
imshow(im);
title('original image');

fftImage=fft2(im);

Y = fftshift(fftImage);
subplot(3,3,2);
imshow(real(log(Y)), []);
title('In Frequency Domain');

[rows columns] = size(Y);
L=Y;
B=idealLPFilter(L,rows,columns);
C=gaussianLPFilter(L,rows,columns);
D=butterworthLPFilter(L,rows,columns);


subplot(3,3,3);
imshow(real(log(B)), [])
title('Ideal Low Pass Filter(Frequency Domain)');


subplot(3,3,4);
imshow(log(abs(C)),[]);
title('Gaussian Low Pass Filter(Frequency Domain)');

subplot(3,3,5);
imshow(log(abs(D)), []);
title('Butterworth Low Pass Filter(Frequency Domain)');


filteredImage = real(ifft2(ifftshift(B)));
subplot(3,3,6);
imshow(real(filteredImage), []);
title('Output: Ideal Low Pass Filter');


GfilteredImage = real(ifft2(ifftshift(C)));
subplot(3,3,7);
imshow(real(GfilteredImage), []);
title('Output: Gaussain Low Pass Filter');

BfilteredImage = real(ifft2(ifftshift(D)));
subplot(3,3,8);
imshow(real(BfilteredImage), []);
title('Output: Butterworth Low Pass Filter');


err = immse(real(BfilteredImage), im);
fprintf('\n The mean-squared error is %0.4f\n', err);


function B = idealLPFilter(L,rows,columns)
    window = 100;
    B=L;
    B(1:end, 1:window) = 0;%top left
    B(1:window,1:end) = 0;
    B(1:end, end-window:end) = 0; %top right
    B(end-window:end, 1:end) = 0;%down right
end

function C = gaussianLPFilter(L,rows,columns)
    R=20; %Filter size parameter
    X=0:columns-1;
    Y=0:rows-1;
    [X Y]=meshgrid(X,Y);

    Cx=0.5*columns;
    Cy=0.5*rows;

    Hi = exp(-((X-Cx).^2+(Y-Cy).^2)./(2*R).^2);
    C=L.*Hi;
end

function D = butterworthLPFilter(L,rows,columns)
    n=1;
    D0=20;
    [p q]=meshgrid(-floor(columns/2):floor(columns/2)-1,-floor(rows/2):floor(rows/2)-1);
    D = sqrt(p.^2 + q.^2);
    hhp = 1 ./ (1 + ((D ./ D0).^(2 * n)));
    size(L)
    size(hhp)
    D=L.*hhp;
end

Answer 1

[Tommy]

'cameraman.tif' and 'coins.png' are both grayscale, meaning your im is a NxM array and your code works.

For any image with color, such as 'pears.png', im is a NxMx3 array. Per the documentation for size():

"When dim is not specified and fewer than ndims(A) output arguments are listed, then all remaining dimension lengths are collapsed into the last argument in the list. For example, if A is a 3-D array with size [3 4 5], then [sz1,sz2] = size(A) returns sz1 = 3 and sz2 = 20."

Therefore, columns equals M*3, not M, and you get the error.

If you are open to the possibility of im being a 3D array, i.e.

[rows, columns, ~] = size(Y);

instead of

[rows, columns] = size(Y);

then you won't get an error for images with color. However, to be honest, I've got no idea if this one change alone would give you the correct results. I believe making this change alone would pass each channel of your image (red, green, and blue) through each of your filters separately. Maybe that is correct?