I don't understand what h is. It's just a big image of zeros with values padded around the edge. What's the point of that? Correcting the line
[xdim xdim]=size(pict) ;
to
[rows columns] = size(pict);
and then fixing up h to use rows and columns won't help the fact that h is weird. Your h is not a low pass filter like you wanted. For one thing it's the same size as the image and should be a lot smaller unless you wanted to totally, and I mean totally, erase all image structure, which is why your left side of the image is nothing but uniform noise.
Try it like this:
clc;
close all;
fontSize = 20;
% 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(2, 2, 1);
imshow(rgbImage, []);
title('Original Color Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
pict=rgb2gray(rgbImage) ;
[rows columns numberOfColorChannels] = size(pict) ;
subplot(221)
imagesc(pict);
colormap(gray);
caption = 'Before degradation';
title(caption, 'FontSize', fontSize);
axis off
% Create Gaussian noise, mean = 0, variance comes from input (No)
No = 80;
noise = sqrt(No)*randn(rows,columns);
subplot(2, 2, 2);
imshow(noise, []);
title('Pure Noise', 'FontSize', fontSize);
% Run image through low pass filter.
windowSize = 15;
h = ones(windowSize, windowSize)/windowSize^2;
% Blur the image by applying the low pass filter.
blurredImage = imfilter(pict,h);
subplot(2, 2, 3);
imshow(blurredImage, []);
title('Low pass filtered image', 'FontSize', fontSize);
% Add Gaussian noise.
degradedImage =double(blurredImage)+noise;
% Display degraded image
subplot(2, 2, 4)
imagesc(degradedImage);
colormap(gray);
caption = sprintf('Degraded image with additive\nGaussian Noise (mean=0, var=%f)', No);
title(caption, 'FontSize', fontSize);
% axis square
axis off
