Graphics Reference
In-Depth Information
Subjective tests for each 3D video system parameter (e.g. camera angle, coding) change is
not an efficient method to evaluate the quality due to several reasons. The most promin-
ent reasons are the time consumption, enormous effort necessary, and the requirements for
special test environments (e.g. standard test laboratories). Therefore, candidate objective
quality measures of 3D video have become a compromise way of measuring the quality.
Therefore, candidate objective quality measures (i.e. PSNR) of colour image sequence and
depth image sequence are utilized to represent the effectiveness of proposed algorithms in
this topic. PSNR is derived by setting the Mean Squared Error (MSE) in relation to the
maximum possible value of the luminance (see Equations 6.1 and 6.2).
For n-bit value this is as follows,
M N
2
g
(
i
,
j
)
G
(
i
,
j
)
MSE
i
1
j
1
Equation 6.1
M
N
PSNR
20log
? 2
n
1
?
Equation 6.2
10
? ?
?
MSE
?
Where g (i,j) is the original signal at pixel (i,j), G (i,j) is the processed signal and M × N is
the picture size. The resultant is a single number in decibels (dB).
