Accurately estimating the spectral reflectance of art paintings
from low-dimensional multichannel images requires that both
image-acquisition hardware with appropriate spectral characteristics
and appropriate estimation software be applied to the captured
multichannel image. In this study, a system that incorporates both
factors is designed and developed on the basis of the
minimum-mean-square error criterion. The accuracy of spectral
estimation by use of this system is evaluated, and the system’s high
performance is demonstrated.
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Case 1, noise free. Case 2, assume
that the recorded data have only positive bias caused by dark current
with a small fluctuation as noise; check the effectiveness of bias
subtraction. Case 3, assume that the recorded data have only
signal-dependent, zero-mean noise according to the properties shown in
Fig. 4; check the effectiveness of the Wiener estimation matrix,
considering the noise properties. Case 4, assume that the recorded
data have both of the noise properties mentioned for the other cases;
check the effectiveness of the proposed estimation method.
Table 4
Robustness Evaluation of the Wiener Estimation
CCD camera
Patch Set
〈ΔEspec〉 (×10-2)
〈ΔEuv*〉
CV-04
A
0.143
2.18
B
0.105
1.70
C
0.140
2.16
DCS420
A
0.171
1.95
B
0.155
1.71
C
0.193
1.92
Table 5
Estimation Accuracy
Number of Filters
ΔEspec
ΔEuv*
Mean (×10-2)
Min (×10-4)
Max (×10-2)
Mean
Min
Max
With best combination of commercially available filters
Case 1, noise free. Case 2, assume
that the recorded data have only positive bias caused by dark current
with a small fluctuation as noise; check the effectiveness of bias
subtraction. Case 3, assume that the recorded data have only
signal-dependent, zero-mean noise according to the properties shown in
Fig. 4; check the effectiveness of the Wiener estimation matrix,
considering the noise properties. Case 4, assume that the recorded
data have both of the noise properties mentioned for the other cases;
check the effectiveness of the proposed estimation method.
Table 4
Robustness Evaluation of the Wiener Estimation
CCD camera
Patch Set
〈ΔEspec〉 (×10-2)
〈ΔEuv*〉
CV-04
A
0.143
2.18
B
0.105
1.70
C
0.140
2.16
DCS420
A
0.171
1.95
B
0.155
1.71
C
0.193
1.92
Table 5
Estimation Accuracy
Number of Filters
ΔEspec
ΔEuv*
Mean (×10-2)
Min (×10-4)
Max (×10-2)
Mean
Min
Max
With best combination of commercially available filters