How to find out the different intensity values that are used in the image and make out a list of them. Then find the freq. of occurrence (probability) of each of intensity values in the image?
MATLAB: How to find out the different intensity values that are used in the image and make out a list of them.Then find the freq. of occurence (probability) of each of intensity values in the image
histogramImage Processing Toolboxintensitypdf
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Here's the full demo for you:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format short g;format compact;fontSize = 25;%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'o4s1_11.bmp';% Get the full filename, with path prepended.
folder = pwdfullFileName = fullfile(folder, baseFileName);%===============================================================================% Read in a first image.
grayImage1 = imread(fullFileName);% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage1)if numberOfColorChannels > 1 % It's not really gray scale like we expected - it's color.
% Use weighted sum of ALL channels to create a gray scale image.
% grayImage = rgb2gray(grayImage);
% ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
% which in a typical snapshot will be the least noisy channel.
grayImage1 = grayImage1(:, :, 2); % Take green channel.
end% Display the image.
subplot(2, 2, 1);imshow(grayImage1, []);axis on;axis image;caption = sprintf('Image1');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0.04, 1, .96]);% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;%===============================================================================% Read in a second image.
fullFileName = fullfile(pwd, 'blankv5.bmp');grayImage2 = imread(fullFileName);% Get the dimensions of the image.% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.[rows, columns, numberOfColorChannels] = size(grayImage2)if numberOfColorChannels > 1 % It's not really gray scale like we expected - it's color. % Use weighted sum of ALL channels to create a gray scale image.% grayImage = rgb2gray(grayImage); % ALTERNATE METHOD: Convert it to gray scale by taking only the green channel, % which in a typical snapshot will be the least noisy channel. grayImage2 = grayImage2(:, :, 2); % Take green channel.end% Display the image.subplot(2, 2, 2);imshow(grayImage2, []);axis on;axis image;caption = sprintf('Image2');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Display the histogram of the image so we can see what threshold to use.
subplot(2, 2, 3);histogram(grayImage2);grid on;% Binarize the image.
threshold = 128;binaryImage = grayImage1 < threshold; % Determine number from histogram.
% Get rid of surround that is touching the border.
binaryImage = imclearborder(binaryImage);% Display the image.subplot(2, 2, 3);imshow(binaryImage, []);axis on;axis image;caption = sprintf('Binary Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;hp = impixelinfo();% Use this binary image to transfer the stuff in the second image.
grayImage2(binaryImage) = grayImage1(binaryImage);% Display the image.subplot(2, 2, 4);imshow(grayImage2, []);axis on;axis image;caption = sprintf('Final Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;
The mean of a particular pixel is just simply the pixel value, since there is only one sample - nothing really to take the mean of:
intensityValue = grayImage(100, 230); meanIntensityValue = mean(grayImage(100, 230));Here, of course meanIntensityValue will equal intensityValue.
To get the mean of all the pixel values in the entire image, you can do any of these:
meanIntensityValue = mean2(grayImage);meanIntensityValue = mean(grayImage(:));meanIntensityValue = mean(mean(grayImage));
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