how to generate background noise in a color image
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generation of background noise in a color image
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Image Analyst
el 17 de Mayo de 2013
How about imnoise()? Or if you have a specific type of noise in mind, then let's hear it.
2 comentarios
Image Analyst
el 17 de Mayo de 2013
Please run my slat and pepper noise removal demo.
% Demo to add "salt and pepper" noise to a color image,
% then restore the image by removing this noise with a
% modified median filter that acts only on the noise pixels
% and not upon "good" non-noise pixels.
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';
% 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'));
% Give a name to the title bar.
set(gcf,'name','Salt and Pepper Noise Removal Demo','numbertitle','off')
% 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('Color 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 individual color 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);
% Display the restored individual color channel images.
subplot(3, 4, 10);
imshow(noiseFreeRed);
title('Restored Red Channel', 'FontSize', fontSize);
subplot(3, 4, 11);
imshow(noiseFreeGreen);
title('Restored Green Channel', 'FontSize', fontSize);
subplot(3, 4, 12);
imshow(noiseFreeBlue);
title('Restored Blue Channel', 'FontSize', fontSize);
% Reconstruct the noise free RGB image
rgbFixed = cat(3, noiseFreeRed, noiseFreeGreen, noiseFreeBlue);
subplot(3, 4, 9);
imshow(rgbFixed);
title('Restored Image', 'FontSize', fontSize);
ARUN SAI
el 18 de Mayo de 2013
1 comentario
Image Analyst
el 18 de Mayo de 2013
Its location. You somehow define foreground and background for your image. For example the girl is the "foreground" and the beach and ocean is the "background." If you want, you can define "background noise" as that noise that occurs in the part of your image that you define as background. Similar for foreground.
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