How to remove the RGB noise from image?

Question

Muhamed Sewidan 2019-1-19

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/440523-how-to-remove-the-rgb-noise-from-image

评论： nathiya v 2019-3-27

I have some RGB images that contain many red, green and blue dots, How can I reomve them without affecting the quality, contrast or the colour of the image?

Is there any free code that I can use?

Here is an example

Thanks in advance

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Answer 1

Image Analyst 2019-1-19

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https://ww2.mathworks.cn/matlabcentral/answers/440523-how-to-remove-the-rgb-noise-from-image#answer_357147

Looks like salt and pepper noise. See my attached demos. They do a modified median filter.

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Muhamed Sewidan 2019-1-20

在 MATLAB Online 中打开

Here is how i edit it. Please correct me if it is wrong.

% 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.
clear all
clc
fontSize = 15;
addpath 'R:\Data\Fizeau\Nylon 6\1.537 & Conversion';
I = imread ('Parallel (3).bmp') ;
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(I);
% Display the original color image.
subplot(3, 4, 1), imshow(I), title('Original Color Image','Font size', font size);
% Extract the individual red, green, and blue color channels.
redChannel = I(:, :, 1);
greenChannel = I(:, :, 2);
blueChannel = I(:, :, 3);
% Display the individual red, green, and blue color channels.
subplot(3, 4, 2), imshow(redChannel), title('Red Channel');
subplot(3, 4, 3), imshow(greenChannel), title('Green Channel');
subplot(3, 4, 4), imshow(blueChannel), title('Blue Channel');
% Median Filter the channels:
redMF = medfilt2(redChannel, [9 9]);
greenMF = medfilt2(greenChannel, [9 9]);
blueMF = medfilt2(blueChannel, [9 9]);
% 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 R');
subplot(3, 4, 11), imshow(noiseFreeGreen), title('Restored G');
subplot(3, 4, 12), imshow(noiseFreeBlue), title('Restored B');
% Reconstruct the noise free RGB image
rgbFixed = cat(3, noiseFreeRed, noiseFreeGreen, noiseFreeBlue);
subplot(3, 4, 9), imshow(rgbFixed), title('Restored Image');