[Restored question]
Hello there,
I need help please. I want a matlab code that detect salt & pepper noise in grayscale image using Fuzzy technique. Then apply median filter to all noisy pixels.
appreciate your help.
Anwar
MATLAB: [Restored title] Fuzzy impulse detection in grayscale image
Related Solutions
Lots of things could be called that - there are maybe a dozen, or more, variants. Here's an example of how I use an adaptive median filter to remove salt and pepper noise. Feel free to adapt it to your particular algorithm.
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; endendrgbImage = 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);Convert to grayscale and then threshold and find the bounding box
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
imtool close all; % Close all imtool figures.
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 20;% Read in the color image.
folder = pwd;baseFileName = 'm2.bmp';% 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; endendrgbImage = imread(fullFileName);% Get the dimensions of the image. numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);% Display the original color image.
subplot(2, 3, 1);imshow(rgbImage, []);axis on;title('Original Color Image', 'FontSize', fontSize);drawnow;% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);% Histogram the red channel, but there is a huge spike at 255 so let's not count those.
subplot(2, 3, 2);grayImage = rgb2gray(rgbImage);imshow(grayImage, []);title('Gray Scale version', 'FontSize', fontSize);subplot(2, 3, 3);histogram(grayImage(grayImage<255))grid on;title('Histogram of Gray Scale Image', 'FontSize', fontSize);someThresholdValue = 150;binaryImage = grayImage > someThresholdValue;% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);subplot(2, 3, 4);imshow(binaryImage);grid on;title('Binary Image', 'FontSize', fontSize);% Label the binary image.
labeledImage = bwlabel(binaryImage);props = regionprops(labeledImage, 'BoundingBox');bbox = props.BoundingBoxcroppedImageRGB = imcrop(rgbImage, bbox);subplot(2, 3, 5);imshow(croppedImageRGB);grid on;title('Cropped RGB Image', 'FontSize', fontSize);% Gray scale version of cropped image
croppedImageGray = imcrop(grayImage, bbox);subplot(2, 3, 6);imshow(croppedImageGray);grid on;title('Cropped Gray Scale Image', 'FontSize', fontSize);
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