Assignment has more non-singleton rhs dimensions than non-singleton subscripts

Hi

I have problem with this program, it should be primitive image denoising filter, but I'm not very experienced at matlab and I'm getting this error

clear all;
clc;
%Source image load
IM = imread('LenaNoise.png');
S=size(IM);
MaxR=S(1);
MaxC=S(2);
FIM=IM;
for i=1 : MaxR
  for j=1:MaxC
      x=impixel(FIM,i,j);
      x1=impixel(FIM,(i+1),j);
      x2=impixel(FIM,(i-1),j);
      x3=impixel(FIM,i,(j+1));
      x4=impixel(FIM,i,(j-1));
      if x==0|255
          if x1==x | x2==x | x3==x | x4==x
              AVG=(x1+x2+x3+x4)/4;
              FIM(i,j)=AVG;

            end
        end
    end
end
imshow(FIM);

Answer 1

[Image Analyst]

x through x4 are RGB triplets so you need to compare them correctly. Or else just convert from RGB to single or double like below:

%Source image load
rgbImage = imread('LenaNoise.png');
[rows columns numberOfColorChannels] = size(rgbImage)
FIM= single(rgb2gray(rgbImage));
for column = 2 : columns-1
  for row = 2 : rows-1
    x=FIM(row,column);
    x1=FIM((row+1),column);
    x2=FIM((row-1),column);
    x3=FIM(row,(column+1));
    x4=FIM(row,(column-1));
    if x == 0 || x == 255
      %if x1==x | x2==x | x3==x | x4==x
      AVG=(x1+x2+x3+x4)/4;
      FIM(row,column)=AVG;
      %end
    end
  end
end
imshow(FIM, []);
title('Denoised Image', 'FontSize', 25);

Anyway, this could be done better with conv2.

Or, if you want to see how I do modified median filter of salt and pepper noise, see below:

clc;  % Clear command window.
clear;  % Delete all variables.
close all;  % Close all figure windows except those created by imtool.
imtool close all;  % Close all figure windows created by imtool.
workspace;  % Make sure the workspace panel is showing.
fontSize = 15;

% Read in a standard MATLAB color demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'peppers.png';
fullFileName = fullfile(folder, baseFileName);
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows columns numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(3, 4, 1);
imshow(rgbImage);
title('Original color Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'Position', get(0,'Screensize')); 

% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);

% Display the individual red, green, and blue color channels.
subplot(3, 4, 2);
imshow(redChannel);
title('Red Channel', 'FontSize', fontSize);
subplot(3, 4, 3);
imshow(greenChannel);
title('Green Channel', 'FontSize', fontSize);
subplot(3, 4, 4);
imshow(blueChannel);
title('Blue Channel', 'FontSize', fontSize);

% Generate a noisy image.  This has salt and pepper noise independently on
% each color channel so the noise may be colored.
noisyRGB = imnoise(rgbImage,'salt & pepper', 0.05);
subplot(3, 4, 5);
imshow(noisyRGB);
title('Image with Salt and Pepper Noise', 'FontSize', fontSize);

% Extract the individual red, green, and blue color channels.
redChannel = noisyRGB(:, :, 1);
greenChannel = noisyRGB(:, :, 2);
blueChannel = noisyRGB(:, :, 3);

% Display the noisy channel images.
subplot(3, 4, 6);
imshow(redChannel);
title('Noisy Red Channel', 'FontSize', fontSize);
subplot(3, 4, 7);
imshow(greenChannel);
title('Noisy Green Channel', 'FontSize', fontSize);
subplot(3, 4, 8);
imshow(blueChannel);
title('Noisy Blue Channel', 'FontSize', fontSize);

% Median Filter the channels:
redMF = medfilt2(redChannel, [3 3]);
greenMF = medfilt2(greenChannel, [3 3]);
blueMF = medfilt2(blueChannel, [3 3]);

% Find the noise in the red.
noiseImage = (redChannel == 0 | redChannel == 255);
% Get rid of the noise in the red by replacing with median.
noiseFreeRed = redChannel;
noiseFreeRed(noiseImage) = redMF(noiseImage);

% Find the noise in the green.
noiseImage = (greenChannel == 0 | greenChannel == 255);
% Get rid of the noise in the green by replacing with median.
noiseFreeGreen = greenChannel;
noiseFreeGreen(noiseImage) = greenMF(noiseImage);

% Find the noise in the blue.
noiseImage = (blueChannel == 0 | blueChannel == 255);
% Get rid of the noise in the blue by replacing with median.
noiseFreeBlue = blueChannel;
noiseFreeBlue(noiseImage) = blueMF(noiseImage);

% Reconstruct the noise free RGB image
rgbFixed = cat(3, noiseFreeRed, noiseFreeGreen, noiseFreeBlue);
subplot(3, 4, 9);
imshow(rgbFixed);
title('Restored Image', 'FontSize', fontSize);