Image definition Evaluation _ image Clarity

1. Grayscale Difference

function Out_val=difference_absolute (IMG);
I=rgb2gray (IMG);
[M,n]=size (I);
f=0.0;
I=double (I);
for x=1:m-1;
    for y=1:n-1;
        Ix=i (X+1,y)-I (x,y);
        Iy=i (x,y+1)-I (x,y);
        F=f+abs (Ix) +abs (Iy);
    End
end
out_val=f/m/n;

2. Edge Strength

function outval = edge_intensity (img) 
% outval = Edge_intensity (img) 
 
If nargin = 1 
    img=rgb2gray (IMG); c16/>img = Double (img); 
    % Create Horizontal Sobel matrix 
    w = fspecial (' Sobel '); 
     
    % get the size of IMG 
    [R C] = Size (IMG); 
     
    GX = IMFilter (img,w, ' replicate '); 
    GY = IMFilter (img,w ', ' replicate '); 
     
    For m = 1:r for 
        n = 1:c 
            
                g (m,n) = sqrt (GX (m,n) *GX (m,n) + gy (m,n) *gy (m,n)); 
            
        End-end 
    OutVal = mean (mean (g)); 
else 
    error (' Wrong number of input! '); 

3.main

Clear all;
Close all;
CLC;
PathName = '. \2\ ';   
FileName = '. jpg ';  
 
N=20 
tic

for ii=1:n
       Imagename=strcat (PATHNAME,NUM2STR (ii), FileName);
       im = Imread (imagename);              
       A (ii) =difference_absolute (IM);
       B (ii) =edge_intensity (IM);
End
TOC;
A=a/max (a);
B=b/max (b);
Figure (1);p lot (A, '-r+ '); Hold on 
plot (b, '-b* '); Hold on 
xlabel (' len.s position ')
; Ylabel (' value ');
Title (' Definition evaluation function ');

4. Input picture

5. The normalization of the two sets of results is shown below:

The 14th picture is the clearest, consistent with the results of human eye observation.

Test another set of pictures, and the results are as follows:

The upper edge operator of the processing effect is obviously better than the gray difference, but the time consuming is very big.

Edge operator: 96.872847 seconds.
Grayscale difference: 4.645993 seconds.