How to find mean square error of row mean values?
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close all;
clear all;
clc;
Dir = 'F:\Stuff\Dataset\SignDataset_Sobel\';
count=0;
for i = 1:208
xImgs = imread([Dir,int2str(i),'.jpg']);
[r c pl] = size(xImgs);
xImgs = double(xImgs);
%%---- DCT-----%%
red = dct(xImgs(:,:,1));
green = dct(xImgs(:,:,2));
blue = dct(xImgs(:,:,3));
xr = zeros(1,128);
xg = zeros(1,128);
xb = zeros(1,128);
%%--- Row Mean----%%
for xi=1:128
xr(i,xi) = mean(red(xi,:));
xg(i,xi) = mean(green(xi,:));
xb(i,xi) = mean(blue(xi,:));
end
% xImgs_temp(:,:,1) = xr;
% xImgs_temp(:,:,2) = xg;
% xImgs_temp(:,:,3) = xb;
xImgs_temp = cat(3,xr, xg, xb);
for j=1:208
count=count+1;
xmse_temp(count,1)=0;
xmse_temp(count,2)=i;
xmse_temp(count,3)=j;
totalcat=0;
xmse_temp = double(xmse_temp);
xImg=imread([Dir,int2str(j),'.jpg']);
[r,c,pl] = size(xImg);
xImg = imresize(xImg,[r c]);
xImg = double(xImg);
%--- DCT---%
red1 = dct(xImg(:,:,1));
green1 = dct(xImg(:,:,2));
blue1 = dct(xImg(:,:,3));
xr1 = zeros(1,128);
xg1 = zeros(1,128);
xb1 = zeros(1,128);
%%---- Row Mean---%%
for xj=1:128
xr1(j,xj) = mean2(red1(xj,1:c));
xg1(j,xj) = mean2(green1(xj,1:c));
xb1(j,xj) = mean2(blue1(xj,1:c));
end
% xImg_temp(:,:,1) = xr1;
% xImg_temp(:,:,2) = xg1;
% xImg_temp(:,:,3) = xb1;
xImg_temp = cat(3,xr1,xg1,xb1);
for xi=1:r
for xj=1:c
for xk=1:3
xmse_temp(count,1) = xmse_temp(count,1)+((xImgs_temp(xi,xj,xk)-xImg_temp(xi,xj,xk)) *(xImgs_temp(xi,xj,xk)-xImg_temp(xi,xj,xk)));
end
end
end
xmse_temp(count,1)=xmse_temp(count,1)/(3*r*c);
fprintf('MSE of %f with %f is :%f\n',xmse_temp(count,2),xmse_temp(count,3),xmse_temp(count,1));
end
end
when i applied only DCT it shows the MSE but when on DCT i applied this row mean then i want to find MSE but it shows this, It shows the following error:
Attempted to access xImgs_temp(2,1,1); index out of bounds because size(xImgs_temp)=[1,128,3].
Error in mse_trial (line 72)
xmse_temp(count,1) = xmse_temp(count,1)+( (xImgs_temp(xi,xj,xk)-xImg_temp(xi,xj,xk)) *(xImgs_temp(xi,xj,xk)-xImg_temp(xi,xj,xk)));
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Risposte (1)
Image Analyst
il 25 Ott 2015
In the Image Processing Toolbox, there is an immse() function. Assuming you have a reference, "ground truth" image, use immse().
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