% The calculating program developed by Fluid and Flow Group of HIT.
% If you want to run this program please change the file suffix type
% to '.m' and save. Then run it using MATLAB.

close all;       %close all the images
clear all;       %clear all variables
clc;             %clear screen

% Import an image into MATLAB from your storage path
string=strcat('D:\experimental images\1.jpg');
RGB=imread(string);

% Colour space conversion(from RGB to HSI)
hsi=rgb2hsi(RGB);

% Extact intensity image
ii=hsi(:,:,3);
figure
imshow(ii)  

% Extract valid regions by function [x,y]=ginput(2)
% obtain two points'(upper left corner and lower right corner) coordinates of rectangular region
% Pay attention to the definition of coordinate in matlab
[x,y]=ginput(2)
xn1=x(1,1);%Upper left corner
yn1=y(1,1);
xn2=x(2,1);%Lower right corner
yn2=y(2,1);
c=round(xn1)
r=round(yn1)
% Calculate the upper left corner coordinates of small rectangles
N=8;    % The number of small rectangles
n=round((xn2-xn1)/(N))
m=round(yn2-yn1)
cy(1)=c
rx(1)=r
for k=2:N
   cy(k)=m+cy(k-1)
   rx(k)=rx(1)
end

% Extract images and compute mixing indexes
for k=1:N
z=subim(ii,m,n,rx(k),cy(k));
figure;
imshow(z)

% Compute maximum intensity value of an image
max=z(1,1);
for i=1:m
    for j=1:n
        if max<=z(i,j)
            max=z(i,j);
        end
    end
end


% Compute mean intensity value of an image
num=n*m;
total=0;
for i=1:m
    for j=1:n
        total=total+z(i,j);
    end
end
ave=total/num;

% For computing standard variance value of an image
sum=0;
for i=1:m
    for j=1:n
    sum=sum+(z(i,j)-ave)^2;
    end
end

% The sum for computing mixing index based on formula (1)
sum1=0;
for i=1:m
    for j=1:n
    sum1=sum1+(z(i,j)-max)^2;
    end
end

% Compute mixing indexes
% (The first kind)Both the mean and standard variance 
% decreasing with the enhancement of mixing 
sigma=sqrt(sum/num);
I1=sqrt(sum1/num)
I2=1-sigma/ave
I4=sigma*sigma/(1-ave)/ave
I5=sqrt(sum/(num-1))/ave
I6=sigma
I20=1/(ave*sigma)
I21=-ave*sigma

% % (The second kind)The mean increasing and standard variance % % decreasing with the enhancement of mixing
% sigma=sqrt(sum/num);
% I1=sqrt(sum1/num)
% I2=1-sigma/ave
% I4=sigma*sigma/(1-ave)/ave
% I5=sqrt(sum/(num-1))/ave
% I6=sigma
% I20=ave/sigma
% I21=-sigma/ave

% Construct data variable to export into an excel sheet
excel_data(k,1)=k;
excel_data(k,2)=I1;
excel_data(k,3)=I2;
excel_data(k,4)=I4;
excel_data(k,5)=I5;
excel_data(k,6)=I6;
excel_data(k,7)=I20;
excel_data(k,8)=I21;
end
disp('Mixing indexes are computed completely!');


% Export the computing results into an excel sheet
excel_outpath='D:\experimental images\experimental results 1.xls';
% Construct the head of excel sheet 
excel_head={'Serial number','I1','I2','I4','I5','I6','I20','I21'};
rtn=xlswrite(excel_outpath,excel_head,'A1:H1');
disp('Excel head is complished!');
%export data into an excel sheet
xlswrite(excel_outpath,excel_data,'A2:H9')
disp('Excel data output completely!');