function blur = blurMetric(original)
% original : entry image
% The idea is from "The Blur Effect: Perception and Estimation with a New No-Reference Perceptual Blur Metric"
% Cr�t�-Roffet F., Dolmiere T., Ladret P., Nicolas M. - GRENOBLE - 2007
% In SPIE proceedings - SPIE Electronic Imaging Symposium Conf Human Vision and Electronic Imaging, �tats-Unis d'Am�rique (2007)
% Written by DO Quoc Bao, PhD Student in L2TI Laboratory, Paris 13 University, France
% Email: [email protected], [email protected]
% Last changed: 21-09-2008
%%%%%%%%%%%%%%%%%%Note: the output (blur) is in [0,1]; 0 means sharp, 1 means blur%%%%%%%%%%%%%%%%%%
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% Please cite the author when you use this code. All remarks are welcome. %
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I = double(original);
[y x] = size(I);
Hv = [1 1 1 1 1 1 1 1 1]/9;
Hh = Hv';
B_Ver = imfilter(I,Hv);%blur the input image in vertical direction
B_Hor = imfilter(I,Hh);%blur the input image in horizontal direction
D_F_Ver = abs(I(:,1:x-1) - I(:,2:x));%variation of the input image (vertical direction)
D_F_Hor = abs(I(1:y-1,:) - I(2:y,:));%variation of the input image (horizontal direction)
D_B_Ver = abs(B_Ver(:,1:x-1)-B_Ver(:,2:x));%variation of the blured image (vertical direction)
D_B_Hor = abs(B_Hor(1:y-1,:)-B_Hor(2:y,:));%variation of the blured image (horizontal direction)
T_Ver = D_F_Ver - D_B_Ver;%difference between two vertical variations of 2 image (input and blured)
T_Hor = D_F_Hor - D_B_Hor;%difference between two horizontal variations of 2 image (input and blured)
V_Ver = max(0,T_Ver);
V_Hor = max(0,T_Hor);
S_D_Ver = sum(sum(D_F_Ver(2:y-1,2:x-1)));
S_D_Hor = sum(sum(D_F_Hor(2:y-1,2:x-1)));
S_V_Ver = sum(sum(V_Ver(2:y-1,2:x-1)));
S_V_Hor = sum(sum(V_Hor(2:y-1,2:x-1)));
blur_F_Ver = (S_D_Ver-S_V_Ver)/S_D_Ver;
blur_F_Hor = (S_D_Hor-S_V_Hor)/S_D_Hor;
blur = max(blur_F_Ver,blur_F_Hor);
