MATLAB: 8 bit depth RGB image(gif)

8 bit depth rgb image

is it possible to separate red ,green and blue channel of a 8 bit depth gif image with the following code?

 redimg=im;
      blueimg=im;
      redimg(:,:,2:3)=0;
      blueimg(:,:,1:2)=0;
      greenimg=im;
      greenimg(:,:,3)=0;
      greenimg(:,:,1)=0;

if not then how can that be achieved?

Best Answer

Copy and paste this example code:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
fontSize = 20;
% Change the filename to your filename!
[gifImage cmap] = imread('C:\Users\yourname\Pictures\whatever.gif');
% Display indexed GIF image.
subplot(2,3, 1);
imshow(gifImage);
% Convert to true color RGB image.
rgbImage = ind2rgb(gifImage, cmap);
title('GIF Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
subplot(2,3, 2);
imshow(rgbImage);
title('After conversion to RGB', 'FontSize', fontSize);
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% Display the three component color channels.
subplot(2,3, 4);
imshow(redChannel);
title('Red Channel', 'FontSize', fontSize);
subplot(2,3, 5);
imshow(greenChannel);
title('Green Channel', 'FontSize', fontSize);
subplot(2,3, 6);
imshow(blueChannel);
title('Blue Channel', 'FontSize', fontSize);

Related Solutions

MATLAB: Crop dark area and display the face only

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;
  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, 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.BoundingBox
croppedImageRGB = 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);

MATLAB: Adaptive Weighted Median Filter

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;
  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);

Best Answer

Related Solutions

MATLAB: Crop dark area and display the face only

MATLAB: Adaptive Weighted Median Filter

Related Question