MATLAB Answers

0

Need code for Median Filtering on Color images

Asked by Jagadeesh p on 22 Mar 2012
Latest activity Commented on by Image Analyst
on 13 Jul 2017 at 21:58

Need Code for Median Filtering on Color images

Cheers

Jagadeesh

  1 Comment

http://www.mathworks.com/matlabcentral/answers/6200-tutorial-how-to-ask-a-question-on-answers-and-get-a-fast-answer

Log in to comment.

Products

No products are associated with this question.

4 Answers

Answer by Bjorn Gustavsson on 22 Mar 2012
 Accepted Answer

Either do the median filter on the individual R,G and B planes. Or trasform the RGB image to some other colour format, for example HSV/HSI and do the median filtering on the Hue, Saturaion and Intensity planes and then transfer back to RGB. Matlab has a function for 2-D median filtering:

help medfilt2

HTH

  0 Comments

Log in to comment.


Answer by Image Analyst
on 22 Mar 2012

Here's a demo I've posted before. It gets rid of salt and pepper noise in a color image by median filtering the individual color planes and replacing the "salt" or "pepper" (bad) pixels with pixels taken from the corresponding location in the median filtered image. It's well commented so I'm sure you'll be easily able to follow it and make any modifications that you desire.

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);

  3 Comments

its working fine . without applying salt and pepper i need coding for filtering can u pls modify it and post for me

sir i can't understand this code part..please help me..

% 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);

noiseImage is a binary image that is true for pixels that are pure black or pure white.

Doing noiseFreeRed = redChannel; initializes the output to the noisy input.

Doing

 noiseFreeRed(noiseImage) = redMF(noiseImage);

replaces the pixels that are in the mask (pixels that are pure black or pure white only) with the corresponding pixels in the same location in the median filtered image. So the whole image is not changed to be the median filter, only the corrupted pixels are changed and replaced with the fixed/good median filtered values.

Log in to comment.


Answer by uvan siya on 30 Jan 2013

i need coding for mean shift filtering alone can anyone post for me plsssss

  1 Comment

This should have been a new question since it's not related to the original post. Try the File Exchange: http://www.mathworks.com/matlabcentral/fileexchange/index?utf8=%E2%9C%93&term=%22mean+shift%22

Log in to comment.


Answer by Latha
on 13 Jul 2017 at 13:25

Can we apply the wiener filter(wiener2) in the same way i.e without using rgb2gray

  1 Comment

Log in to comment.


Discover MakerZone

MATLAB and Simulink resources for Arduino, LEGO, and Raspberry Pi

Learn more

Discover what MATLAB® can do for your career.

Opportunities for recent engineering grads.

Apply Today

MATLAB Academy

New to MATLAB?

Learn MATLAB today!