Hi, Suppose you have an 8*8 gray scale image (64 pixels in total). So the x axis varies from 1 to 255 and y axis from 1 to 64, since the maximum number of pixel count corresponding to one gray scale value can be only 64. Make an error matrix of size 64X255. The matrix will be sparse, since most of the values are going to be zero. Make a bar graph as shown in http://www.mathworks.com/help/matlab/ref/bar3.html.
Sample code:
>> clearvars; close all; clc;
%%get an image
>> im = imread('coins.png');
>> im = imresize(im,[8,8]);
>> figure;imshow(im);
%%add noise to image
>> im_noisy = imnoise(im,'gaussian');
>> figure; imshow(im_noisy);
>> x_lim = 255;
>> y_lim = 8*8;
>> err = zeros(y_lim,x_lim);
>> for i = 1:y_lim
>> err(i,im(i)) = abs(double(im(i))-double(im_noisy(i)));
>> end
>> figure; bar3(err);
