how to apply imhist () for matrix <768x1024x3 uint8> ,how to use imhist for 3d matrix

I = imread('pout.tif'); J = histeq(I); subplot(2,1,1); imhist(I) subplot(2,1,2); imhist(J)

Answer 1

[Laurent]

If you want to make a histogram of all your values together you can do something like this:

testim=uint8(rand(768,1024,3)*255); %just to generate a random 3D matrix
imhist(testim(:));

[achuth]

kindly say how to apply histeq(I) when I is of 768*1024*3

[Image Analyst]

He did. But you might not want to do that since you'd be lumping all the red, green, and blue pixels together. About all this would be good for is to see overall light level and check for saturation (clipping).

[achuth]

help me to apply histeq(image)

[Image Analyst]

Wasn't there an example in the code? Why do you want to use histeq anyway? It's almost never needed.

Answer 2

[Image Analyst]

See my RGB Histogram demo:

%----------------------------------------------------------
% Program to read in all the RGB color images in a folder and 
% display the histograms of each color channel.
%, Feb. 2011
%----------------------------------------------------------

function RGB_Histogram_Demo()

% Change the current folder to the folder of this m-file.
if(~isdeployed)
  cd(fileparts(which(mfilename)));
end
clc;  % Clear command window.
close all;  % Close all figure windows except those created by imtool.
workspace;  % Make sure the workspace panel is showing.
fontSize = 16;

try
% Read in standard MATLAB color demo images.
% Construct the folder name where the demo images live.
imagesFolder = fullfile(matlabroot, '\toolbox\images\imdemos');
if ~exist(imagesFolder, 'dir')
  % That folder didn't exist.  Ask user to specify folder.
   message = sprintf('Please browse to your image folder');
  button = questdlg(message, 'Specify Folder', 'OK', 'Cancel', 'OK');
  drawnow;  % Refresh screen to get rid of dialog box remnants.
  if strcmpi(button, 'Cancel')
     return;
  else
    imagesFolder = uigetdir();
    if imagesFolder == 0
      % Exit if uer clicked Cancel.
      return;
    end
  end
end

% Read the directory to get a list of images.
filePattern = [imagesFolder, '\*.jpg'];
jpegFiles = dir(filePattern);
filePattern = [imagesFolder, '\*.tif'];
tifFiles = dir(filePattern);
filePattern = [imagesFolder, '\*.png'];
pngFiles = dir(filePattern);
filePattern = [imagesFolder, '\*.bmp'];
bmpFiles = dir(filePattern);
% Add more extensions if you need to.
imageFiles = [jpegFiles; tifFiles; pngFiles; bmpFiles];

% Bail out if there aren't any images in that folder.
numberOfImagesProcessed = 0;
numberOfImagesToProcess = length(imageFiles);
if numberOfImagesToProcess <= 0
   message = sprintf('I did not find any JPG, TIF, PNG, or BMP images in the folder\n%s\nClick OK to Exit.', imagesFolder);
  uiwait(msgbox(message));
  return;
end

% Create a figure for our images.
figure;
set(gcf, 'Position', get(0,'Screensize')); % Maximize figure.
set(gcf,'name','Image Analysis Demo','numbertitle','off') 

% Preallocate arrays to hold the mean intensity values of all the images.
redChannel_Mean = zeros(numberOfImagesToProcess, 1);
greenChannel_Mean = zeros(numberOfImagesToProcess, 1);
blueChannel_Mean = zeros(numberOfImagesToProcess, 1);

% We'll be skipping monochrome and indexed images
% and just looking at true color images.
% Keep track of how many we actually look at.
numberOfImagesToProcess2 = numberOfImagesToProcess;

% Loop though all images, calculating and displaying the histograms.
% and then getting the means of the Red, green, and blue channels.
for k = 1 : numberOfImagesToProcess
  % Read in this one file.
  baseFileName = imageFiles(k).name;
  fullFileName = fullfile(imagesFolder, baseFileName);
  rgbImage = imread(fullFileName);

  % Check to see that it is a color image (3 dimensions).
  % Skip it if it is not true RGB color.
  if ndims(rgbImage) < 3
    % Skip monochrome or indexed images.
    fprintf('Skipped %s.  It is a grayscale or indexed image.\n', baseFileName);
    % Decrement the number of images that we'll report that we need to look at.
    numberOfImagesToProcess2 = numberOfImagesToProcess2 - 1;  
    continue;
  end
  
  % If we get to here, it's a true color image.
  subplot(3, 3, 1);
  imshow(rgbImage, []);
  [rows columns numberOfColorBands] = size(rgbImage);
  
  % Create a title for the image.
  caption = sprintf('Original Color Image\n%s\n%d rows by %d columns by %d color channels', ...
    baseFileName, rows, columns, numberOfColorBands);
  % If there are underlines in the name, title() converts the next character to a subscript.
  % To avoid this, replace underlines by spaces.
  caption = strrep(caption, '_', ' ');
  title(caption, 'FontSize', fontSize);
  drawnow;  % Force it to update, otherwise it waits until after the conversion to double.
  
  % Extract the individual red, green, and blue color channels.
  redChannel = rgbImage(:, :, 1);
  greenChannel = rgbImage(:, :, 2);
  blueChannel = rgbImage(:, :, 3);
  
  % Red image:
  subplot(3, 3, 4);
  imshow(redChannel, []); % Display the image.
  % Compute mean
  redChannel_Mean(k) = mean(redChannel(:));
  caption = sprintf('Red Image.  Mean = %6.2f', redChannel_Mean(k));
  title(caption, 'FontSize', fontSize);
  % Compute and display the histogram for the Red image.
  pixelCountRed = PlotHistogramOfOneColorChannel(redChannel, 7, 'Histogram of Red Image', 'r');

  % Green image:
  subplot(3, 3, 5);
  imshow(greenChannel, []); % Display the image.
  % Compute mean
  greenChannel_Mean(k) = mean(greenChannel(:));
  caption = sprintf('Green Image.  Mean = %6.2f', greenChannel_Mean(k));
  title(caption, 'FontSize', fontSize);
  % Compute and display the histogram for the Green image.
  pixelCountGreen = PlotHistogramOfOneColorChannel(greenChannel, 8, 'Histogram of Green Image', 'g');

  % Blue image:
  subplot(3, 3, 6);
  imshow(blueChannel, []); % Display the image.
  numberOfImagesProcessed = numberOfImagesProcessed + 1;
  % Compute mean
  blueChannel_Mean(k) = mean(blueChannel(:));
  caption = sprintf('Blue Image.  Mean = %6.2f', blueChannel_Mean(k));
  title(caption, 'FontSize', fontSize);
  % Compute and display the histogram for the Blue image.
  pixelCountBlue = PlotHistogramOfOneColorChannel(blueChannel, 9, 'Histogram of Blue Image', 'b');
  
  % Plot all three histograms on the same plot.
  subplot(3, 3, 2:3);
  lineWidth = 2;
  hold off;
  plot(pixelCountRed, 'r', 'LineWidth', lineWidth);
  hold on;
  grid on;
  plot(pixelCountGreen, 'g', 'LineWidth', lineWidth);
  plot(pixelCountBlue, 'b', 'LineWidth', lineWidth);
  title('All the Color Histograms (Superimposed)', 'FontSize', fontSize);
  % Set the x axis range manually to be 0-255.
  xlim([0 255]); 
  
  % Prompt user to continue, unless they're at the last image.
  if k < numberOfImagesToProcess
    promptMessage = sprintf('Currently displaying image #%d of a possible %d:\n%s\n\nDo you want to\nContinue processing, or\nCancel processing?',...
      numberOfImagesProcessed, numberOfImagesToProcess2, baseFileName);
    button = questdlg(promptMessage, 'Continue?', 'Continue', 'Cancel', 'Continue');
    if strcmp(button, 'Cancel')
      break;
    end
  end
end

% Crop off any unassigned values:
redChannel_Mean = redChannel_Mean(1:numberOfImagesProcessed);
greenChannel_Mean = greenChannel_Mean(1:numberOfImagesProcessed);
blueChannel_Mean = blueChannel_Mean(1:numberOfImagesProcessed);

% Print to command window
fprintf(1, '                Filename,   Red Mean, Green Mean, Blue Mean\n');
for k = 1 : length(redChannel_Mean)
  baseFileName = imageFiles(k).name;
  fprintf(1, '%24s    %6.2f,   %6.2f,     %6.2f\n', ...
    baseFileName, redChannel_Mean(k), greenChannel_Mean(k), blueChannel_Mean(k));
end

if numberOfImagesProcessed == 1
  caption = sprintf('Done with demo!\n\nProcessed 1 image.\nCheck out the command window for the results');
else
  caption = sprintf('Done with demo!\n\nProcessed %d images.\nCheck out the command window for the results', numberOfImagesProcessed);
end
msgbox(caption);
catch ME
  errorMessage = sprintf('Error in function RGB_Hist_Demo.\n.\n\nError Message:\n%s', ME.message);
  uiwait(warndlg(errorMessage));
end

%----------------------------------------------------------
% Plots a bar chart of the histogram of the color channel.
function pixelCount = PlotHistogramOfOneColorChannel(oneColorChannel, subplotNumber, caption, color)
  try
    % Let's get its histogram into 256 bins.
    [pixelCount grayLevels] = imhist(oneColorChannel, 256);

    subplot(3, 3, subplotNumber);
    bar(grayLevels, pixelCount, 'FaceColor', color); 
    title(caption, 'FontSize', 16);
    grid on;
    % Set the x axis range manually to be 0-255.
    xlim([0 255]); 
  catch ME
    errorMessage = sprintf('Error in function PlotHistogramOfOneColorChannel.\n.\n\nError Message:\n%s', ME.message);
    uiwait(warndlg(errorMessage));
  end
  return;

[achuth]

please guide me to apply histeq(image)