Image Processing Reference
In-Depth Information
done by empirically detected feeble dependence of a difference of the calculated gradient
from colors and considered pixels.
For example, vertical, horizontal and diagonal gradients for the "red" pixel allocated in a
point (3,3) will be equal accordingly:
N g
g
r
r
b
b /2b
b /2g
g /2g
g /2
2,3
4 ,3
1,3
3,3
2,2
4 ,2
2,4
4 ,4
1,2
3,2
1,4
3,4
Eg g
r r
b b/ 2b b/ 2g g/ 2g g/ 2
3,2
3,4
3,3
3,5
2,2
4,2
4,2
3,4
2,3
2,5
4,3
4,5
SW

b
b
r
r
g
g
/2

g
g
/2

g
g
/2
3
g
g
/2.
2,4
4 ,2
5 ,1
3,3
2,3
3,2
3,4
4 ,3
3,2
4 ,1
4 ,
5 ,2
On the basis of a set containing 8 gradients, threshold T is calculated, allowing to define,
what directions were used. T it is defined as
    , where min and max
are the minimum and maximum gradients accordingly, and k1 and k2 constants. Author's
values are k1=1,5 and k2=0,5 . Those directions which gradient is less than a threshold are
selected, and for each selected direction mean values for "blue", "red" and "green" are
calculated. For example, at coordinates (3,3) mean values for directions N, E, SW are the
following:
T
k
min
k
( max
min)
1
2
N
N
N
R( r

r
) / 2
,
Gg
,
B( b b) / 2
,
1,3
3,3
2,3
2,2
2,4
E
E
E
R( r r) / 2

,
Gg
,
B( b b) / 2
,
3,3
3,5
3,4
2,4
4,4
SW
SW
SW
R( r

r
) / 2
,
G( g
g
g
g
) / 4
,
Bb
.
3,3
5,1
3,2
4,1
4,3
5,2
4,2
Let's designate mean values red, blue and green as Ravg , Gavg Bavg accordingly. Then for the
selected pixel mean averaging values for red, dark blue and green in the selected directions
will be: Ravg = (Rs+RE+Rse) /3 , Gavg = (Gs+GE+GSE)/3, Bavg = (BS+BE+BSE) (for pixel pixel (3,3)
and directions S, E, SE ). A final estimation of missing color components levels are: G (3,3)
=r3,3 + (Gavg-Ravg) and B (3,3) =r3,3 + (Bavg+Ravg) [11].
2. Cameras identification techniques
2.1 Camera identification based on artifacts of color interpolation
There are several approaches to the implementation of identification systems for digital
cameras based on the above characteristics.
In [12] cameras identification is done based on color interpolation features. The recognition
process involves the following steps.
Designating I(  as one of R( ) G(  , B( )  channels provided that the pixel in coordinates
(x,y) is correlated linearly with other pixels, it is possible to express value of brightness of a
color component as the weighed total of brightness of components of adjacent pixels:
N
I(x,y )
 
I( x

x ,yy)

,
(1)
i
i
i
i1
Where N is a number of correlated pixels, αi , Δxj , Δyj - weight and offset on an axis x and an
axis y of the pixel correlated from i th pixel accordingly. The set of such coordinates Δхi , Δyi
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