Pixel Differnce Histogram Plotting.

How to plot histogram for (PDH) analysis like in the attached image

Answer 1

[Image Analyst]

You can use histogram or, if you already have the counts (like from histcounts) then use bar.

The title function was also used to put a caption above those plots.

[Mostfa Abd El-Aziz]

Dear Image Analyst,

Can you provide me an example of this sugessted code please??

[Image Analyst]

There are examples in the documentation for the functions. You'll see things like this

yourGrayScaleImage = imread('lena_grayscale.jpg');
% 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(yourGrayScaleImage)

rows = 512

columns = 512

numberOfColorChannels = 1

%--------------------------------------------------------------------------------------------------------
% Convert to grayscale if it's not already
if numberOfColorChannels > 1
	% It's not really gray scale like we expected - it's color.
	fprintf('It is not really gray scale like we expected - it is color\n');
	% Extract the blue channel.
	yourGrayScaleImage = yourGrayScaleImage(:, :, 3);
	% Update 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(yourGrayScaleImage)
end
% Display image.
subplot(2, 1, 1);
imshow(yourGrayScaleImage);
title('Cover')
% Take histogram.
[counts, edges] = histcounts(yourGrayScaleImage, 256);
% Plot Histogram
subplot(2, 1, 2);
bar(edges(1:end-1), counts, 1);
grid on;
title('PDH of Cover')
xlabel('Gray Level')
ylabel('Count')