BASLER A631f - CRI JOLANTA · 3.1.1 Illumination Setup Basler-CameraTestTool The illumination...
Transcript of BASLER A631f - CRI JOLANTA · 3.1.1 Illumination Setup Basler-CameraTestTool The illumination...
Camera Specification
BASLER A631fMeasurement protocol using the
EMVA Standard 1288
2nd November 2006
All values are typical and are subject to change without prior notice.
CONTENTS
Contents
1 Overview 1
2 Introduction 2
3 Basic Information 33.1 Illumination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3.1.1 Illumination Setup Basler-CameraTestTool . . . . . . . . . . . . . . 43.1.2 Measurement of the Irradiance . . . . . . . . . . . . . . . . . . . . 4
4 Characterizing Temporal Noise and Sensitivity 54.1 Basic Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
4.1.1 Total quantum efficiency . . . . . . . . . . . . . . . . . . . . . . . . 54.1.2 Temporal dark noise . . . . . . . . . . . . . . . . . . . . . . . . . . 74.1.3 Dark current . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84.1.4 Doubling temperature . . . . . . . . . . . . . . . . . . . . . . . . . 84.1.5 Inverse of overall system gain . . . . . . . . . . . . . . . . . . . . . 94.1.6 Inverse photon transfer . . . . . . . . . . . . . . . . . . . . . . . . 104.1.7 Saturation capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . 114.1.8 Spectrogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124.1.9 Non-Whiteness Coefficient . . . . . . . . . . . . . . . . . . . . . . 15
4.2 Derived Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164.2.1 Absolute sensitivity threshold . . . . . . . . . . . . . . . . . . . . . 164.2.2 Signal to noise ratio . . . . . . . . . . . . . . . . . . . . . . . . . . 174.2.3 Dynamic range . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4.3 Raw Measurement Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204.3.1 Mean gray value . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204.3.2 Variance of temporal distribution of gray values . . . . . . . . . . . 214.3.3 Mean of the gray values dark signal . . . . . . . . . . . . . . . . . 224.3.4 Variance of the gray values temporal distribution in dark . . . . . . 234.3.5 Light induced variance of temporal distribution of gray values . . . 244.3.6 Light induced mean gray value . . . . . . . . . . . . . . . . . . . . 254.3.7 Dark current versus housing temperature . . . . . . . . . . . . . . 26
5 Characterizing Total and Spatial Noise 275.1 Basic Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5.1.1 Spatial offset noise . . . . . . . . . . . . . . . . . . . . . . . . . . . 275.1.2 Spatial gain noise . . . . . . . . . . . . . . . . . . . . . . . . . . . 285.1.3 Spectrogram Spatial Noise . . . . . . . . . . . . . . . . . . . . . . 295.1.4 Spatial Non-Whiteness Coefficient . . . . . . . . . . . . . . . . . . 32
5.2 Raw Measurement Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335.2.1 Standard deviation of the spatial dark noise . . . . . . . . . . . . . 33
BASLER A631f I
CONTENTS
5.2.2 Light induced standard deviation of the spatial noise . . . . . . . . 34
Bibliography 35
II BASLER A631f
1 Overview
1 Overview
Basler A631f
Item Symbol Typ.1 Std. dev.2 Unit Remarks
Temporal Noise Parameters
Total quantum efficiency (QE) η 42 TBD % λ = 545 nm
Inverse of overall system gain 1K
3.3 0.11 e−DN
Temporal dark noise σd0 12 0.8 e−
Saturation capacity µe.sat 13000 600 e−
Spatial Noise Parameters
Spatial offset noise, DSNU1288 σo 2.6 0.3 e−
Spatial gain noise, PRNU1288 Sg 0.9 0.1 %
Derived Parameters
Absolute sensitivity threshold µp.min 28 TBD p∼ λ = 545 nm
Dynamic range DYNout.bit 10.0 0.13 bit
Table 1: Most important specification data
Operating Point
Item Symbol Remarks
Video output format 12 bits/pixel(Mono16)
Gain 350
Offset 11
Exposure time Texp 100.0 µs to 37.7 ms
Table 2: Used camera operating point
1The unit e− is used in this document as statistical measured quantity.2The standard deviation was calculated from a sampling of 19 cameras.
BASLER A631f 1-1
2 Introduction
2 Introduction
This measurement protocol describes the specification of the Basler A631f cameras.The measurement methods are conform to the EMVA Standard 1288, the Standard forCharacterization and Presentation of Specification Data for Image Sensors and Cam-eras (Release A1.03) of the European Machine Vision Association (EMVA) [1].
The most important specification data of the Basler A631f cameras are summarisedin the table 1.
2-2 BASLER A631f
3 Basic Information
3 Basic Information
Basic Information
Vendor Basler
Model A631f
Type of data presented Typical
Number of samples 19
Sensor Sony ICX267AL
Sensor type CCD
Sensor diagonal Diagonal 8 mm (Type 1/2)
Indication of lens category to be used C-Mount
Resolution 1392 x 1040 pixel
Pixel width 4.65 µm
Pixel height 4.65 µm
Readout type Progressive Scan
Transfer type Interline transfer
Shutter type -
Overlap capabilities
Maximum frame rate 18.7 frames/second
General conventions
Interface type Firewire 1394a
Table 3: Basic Information
BASLER A631f 3-3
3.1 Illumination
3.1 Illumination
3.1.1 Illumination Setup Basler-CameraTestTool
The illumination during the test of one camera was fixed. The drift of the illuminationover a long time and after exchange of the lamp is measured by a reference BaslerA602fc camera. The reference camera provides an intensity factor which was used tocalculate the irradiance for each camera measurement.
Light source
Wavelength λ 545 nm
Wavelength variation ∆λ 50 nm
f-number f# 8 = 280 mm/35 mm
Table 4: Light source
3.1.2 Measurement of the Irradiance
The irradiance was measured using a Radiometer IL1700 from International Light Inc.(Detector: SEL033 #6285; Input optic: W #9461; Filter: F #21487; regular calibration).The accuracy of the Radiometer is specified as ±3.5%.
In figure 1 the measured irradiance is plotted.
20.8x10-3
20.6
20.4
20.2
20.0
19.8
Irra
dian
ce [W
/m^2
]
20151050
Measurement
A631f (19 cameras), Irradiance
Figure 1: Irradiance for each camera measurement.
The the error of all calculated values using the amount of light falling on the sensorare dependent of the accuracy of the irradiance measurement.
4-4 BASLER A631f
4 Characterizing Temporal Noise and Sensitivity
4 Characterizing Temporal Noise and Sensitivity
4.1 Basic Parameters
4.1.1 Total quantum efficiency
Total quantum efficiency for one fixed wavelenght Total quantum efficiency η(λ) in[%] for monochrome light at λ = 545 nm. With a wavelength variation of ∆λ = 50 nm.
40
30
20
10
0
Qua
ntum
effi
cien
cy [%
]
151050
Camera
A631f (19 cameras), Quantum efficiency
8
6
4
2
0
Num
ber
43.543.042.542.041.541.0
Quantum efficiency [%]
A631f (19 cameras), Quantum efficiency histogram
Figure 2: Total quantum efficiency (QE)
Item Symbol Typ. Std. dev. Unit Remarks
Total quantum efficiency (QE) η 42 TBD % λ = 545 nm
Table 5: Total quantum efficiency (QE)
The main error of the total quantum efficiency ∆η is related to the error of the mea-surement of the illumination described in section 3.1.
BASLER A631f 4-5
4.1 Basic Parameters
Total quantum efficiency versus wavelength of the light Total quantum efficiencyη(λ) in [%] for monochrome light versus wavelength of the light in [nm] .
40
30
20
10
0
Qua
ntum
effi
cien
cy [%
]
1000900800700600500400
Wavelength [nm]
A631f (19 cameras), Quantum efficiency
Figure 3: Irradiance for each camera measurement.
The curve of the total quantum efficiency versus the wavelength in figure 3 was cal-culated from the one measured total quantum efficiency as presented in section 4.1.1.For the shape of the curve the data from the sensor data sheet was used.
4-6 BASLER A631f
4.1 Basic Parameters
4.1.2 Temporal dark noise
Standard deviation of the temporal dark noise σd0 referenced to electrons for exposuretime zero in [ e−].
14
12
10
8
6
4
2
0
Std
. Tem
pora
l dar
k no
ise
[e-]
151050
Camera
A631f (19 cameras), Std. temporal dark noise
8
6
4
2
0
Num
ber
13.513.012.512.011.5
Std. Temporal dark noise [e-]
A631f (19 cameras), Std. temporal dark noise histogram
Figure 4: Temporal dark noise
Item Symbol Typ. Std. dev. Unit Remarks
Temporal dark noise σd0 12 0.8 e−
Table 6: Temporal dark noise
BASLER A631f 4-7
4.1 Basic Parameters
4.1.3 Dark current
Dark current Nd30 for a housing temperature of 30◦ C in [e−/s] .Not measured!
4.1.4 Doubling temperature
Doubling temperature kd of the dark current in [◦ C].Not measured!
4-8 BASLER A631f
4.1 Basic Parameters
4.1.5 Inverse of overall system gain
Inverse of overall system gain 1K
in [ e−DN
].
3.0
2.5
2.0
1.5
1.0
0.5
0.0Inve
rse
conv
ersi
on g
ain
[e-/
DN
]
151050
Camera
A631f (19 cameras), Inverse conversion gain
6
5
4
3
2
1
0
Num
ber
3.403.353.303.253.203.15
Inverse conversion gain [e-/DN]
A631f (19 cameras), Inverse conversion gain histogram
Figure 5: Inverse of overall system gain
Item Symbol Typ. Std. dev. Unit Remarks
Inverse of overall system gain 1K
3.3 0.11 e−DN
Table 7: Inverse of overall system gain
BASLER A631f 4-9
4.1 Basic Parameters
4.1.6 Inverse photon transfer
Inverse photon transfer 1ηK
in[
p∼DN
].
8
6
4
2
0Inve
rse
phot
on tr
ansf
er [p
~/D
N]
151050
Camera
A631f (19 cameras), Inverse photon transfer
8
6
4
2
0
Num
ber
8.07.87.67.4
Inverse photon transfer [e-/DN]
A631f (19 cameras), Inverse photon transfer histogram
Figure 6: Inverse photon transfer
Item Symbol Typ. Std. dev. Unit Remarks
Inverse photon transfer 1ηK
7.7 TBD p∼DN
λ = 545 nm
Table 8: Inverse photon transfer
The main error of the inverse photon transfer 1ηK
is related to the error of the mea-surement of the illumination described in section 3.1.
4-10 BASLER A631f
4.1 Basic Parameters
4.1.7 Saturation capacity
Saturation capacity µe.sat referenced to electrons in [ e−].
12x103
10
8
6
4
2
0
Sat
urat
ion
capa
city
[e-]
151050
Camera
A631f (19 cameras), Saturation capacity
10
8
6
4
2
0
Num
ber
13.0x103
12.512.011.511.010.5
Saturation apacity [e-]
A631f (19 cameras), Saturation capacity histogram
Figure 7: Saturation capacity
Item Symbol Typ. Std. dev. Unit Remarks
Saturation capacity µe.sat 13000 600 e−
Table 9: Saturation capacity
BASLER A631f 4-11
4.1 Basic Parameters
4.1.8 Spectrogram
Spectrogram referenced to photons in [p∼] is plotted versus spatial frequency in [1/pixel]for no light, 50% saturation and 90% saturation.
120
100
80
60
40
20
0
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), FFT dark
All Mean
3
4
5
6
7
89
100
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), FFT dark
All Mean
Figure 8: Spectrogram referenced to photons for no light
4-12 BASLER A631f
4.1 Basic Parameters
2500
2000
1500
1000
500
0
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), FFT saturation 0.5
All Mean
2
3
4
567
1000
2
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), FFT saturation 0.5
All Mean
Figure 9: Spectrogram referenced to photons for 50% saturation
BASLER A631f 4-13
4.1 Basic Parameters
4000
3000
2000
1000
0
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), FFT saturation 0.9
All Mean
3
4
56
1000
2
3
4
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), FFT saturation 0.9
All Mean
Figure 10: Spectrogram referenced to photons for 90% saturation
4-14 BASLER A631f
4.1 Basic Parameters
4.1.9 Non-Whiteness Coefficient
The non-whiteness coefficient is plotted versus the number of photons µp in [p∼] col-lected in a pixel during exposure time.
2.0
1.5
1.0
0.5
0.0
Non
whi
tene
ss
40x103
3020100
Mean photon [Photons/pixel]
A631f (19 cameras), Non whiteness
Figure 11: Non-whiteness coefficient
BASLER A631f 4-15
4.2 Derived Data
4.2 Derived Data
4.2.1 Absolute sensitivity threshold
Absolute sensitivity threshold µp.min(λ) in [ p∼] for monochrome light versus wavelengthof the light in [nm] .
µp.min =σd0
η(1)
30
25
20
15
10
5
0Abs
olut
e se
nsiti
vity
thre
shol
d [p
~]
151050
Camera
A631f (19 cameras), Absolute sensitivity threshold
7
6
5
4
3
2
1
0
Num
ber
32313029282726
Absolute sensitivity threshold [p~]
A631f (19 cameras), Absolute sensitivity threshold histogram
Figure 12: Absolute sensitivity threshold
Item Symbol Typ. Std. dev. Unit Remarks
Absolute sensitivity threshold µp.min 28 TBD p∼ λ = 545 nm
Table 10: Absolute sensitivity threshold
4-16 BASLER A631f
4.2 Derived Data
4.2.2 Signal to noise ratio
Signal to noise ratio SNRy(µp) is plotted versus number of photons µp collected in a pixelduring exposure time in [p∼] for monochrome light with the wavelength λ given in [ nm].The wavelength should be near the maximum of the quantum efficiency.
A : SNRy =µy − µy.dark
σy
(2)
B : SNRy =ηµp√
(ηµp + σ2d0
)(3)
Figure 13 shows the signal to noise ratio SNRy for monochrome light with the wave-length λ = 545 nm.
8
6
4
2
0
SN
R [b
it]
1614121086420
Mean photon [bit]
A631f (19 cameras), SNR
A B
Figure 13: Signal to noise ratio
BASLER A631f 4-17
4.2 Derived Data
1
2
4
10
2
4
100
2
4
SN
R
100
101
102
103
104
105
Mean photon [Photons/pixel]
A631f (19 cameras), SNR
A B
Figure 14: Signal to noise ratio
4-18 BASLER A631f
4.2 Derived Data
4.2.3 Dynamic range
Dynamic range DYNout.bit in [ bit].
DYNout =µe.sat
σd0
(4)
DYNout.bit = log2 (DYNout) (5)
10
8
6
4
2
0
Dyn
amic
ran
ge o
utpu
t [bi
t]
151050
Camera
A631f (19 cameras), Dynamic range output
7
6
5
4
3
2
1
0
Num
ber
10.210.110.09.99.8
Dynamic range output [bit]
A631f (19 cameras), Dynamic range output histogram
Figure 15: Output dynamic range
Item Symbol Typ. Std. dev. Unit Remarks
Output dynamic range DYNout.bit 10.0 0.13 bit
Table 11: Output dynamic range
BASLER A631f 4-19
4.3 Raw Measurement Data
4.3 Raw Measurement Data
4.3.1 Mean gray value
Mean gray value µy(µp) in [DN] is plotted versus number of photons µp in [p∼] collectedin a pixel during exposure time.
4000
3000
2000
1000
0
Mea
n gr
ay v
alue
brig
ht [D
N]
40x103
3020100
Mean photon [Photons/pixel]
A631f (19 cameras), Mean gray value bright
Figure 16: Mean gray values of the cameras with illuminated pixels
4-20 BASLER A631f
4.3 Raw Measurement Data
4.3.2 Variance of temporal distribution of gray values
Variance of temporal distribution of gray values σ2y.temp(µp) in [DN2] is plotted versus
number of photons µp in [p∼] collected in a pixel during exposure time.
1200
1000
800
600
400
200
0Var
ianc
e gr
ay v
alue
brig
ht [D
N^2
]
40x103
3020100
Mean photon [Photons/pixel]
A631f (19 cameras), Variance gray value bright
Figure 17: Variance values of temporal distribution of gray values with illuminated pixels
Saturation Capacity The saturation point is defined as the maximum of the curve inthe diagram 17. The abscissa of the maximum point is the number of photons µp.sat
where the camera saturates. The saturation capacity µe.sat in electrons is computedaccording to the mathematical model as:
µe.sat = ηµp.sat (6)
BASLER A631f 4-21
4.3 Raw Measurement Data
4.3.3 Mean of the gray values dark signal
Mean of the gray values dark signal µy.dark(Texp) in [DN] is plotted versus exposure timein [s] .
12
10
8
6
4
2
0
Mea
n gr
ay v
alue
dar
k [D
N]
30x103
20100
Exposure time [us]
A631f (19 cameras), Mean gray value dark
Figure 18: Mean gray values of the cameras in darkness
4-22 BASLER A631f
4.3 Raw Measurement Data
4.3.4 Variance of the gray values temporal distribution in dark
Variance of the gray values temporal distribution in dark σ2y.temp.dark(Texp) in [DN2] is
plotted versus exposure time Texp in [s] .
16
14
12
10
8
6
4
2
0Var
ianc
e gr
ay v
alue
dar
k [D
N^2
]
30x103
20100
Exposure time [us]
A631f (19 cameras), Variance gray value dark
Figure 19: Variance values of temporal distribution of gray values in darkness
Temporal Dark Noise The dark noise for exposure time zero is found as the offset ofthe linear correspondence in figure 19. Match a line (with offset) to the linear part of thedata in the diagram. The dark noise for exposure time zero σ2
d0is found as the offset of
the line divided by the square of the overall system gain K.
σd0 =
√σ2
y.temp.dark(Texp = 0)
K2(7)
BASLER A631f 4-23
4.3 Raw Measurement Data
4.3.5 Light induced variance of temporal distribution of gray values
The light induced variance of temporal distribution of gray values in [DN2] is plottedversus light induced mean gray value in [DN] .
1000
800
600
400
200
0
Var
ianc
e gr
ay v
alue
(br
ight
- d
ark)
[DN
^2]
3500300025002000150010005000
Mean gray value (bright - dark) [DN]
A631f (19 cameras), Diff variance vs diff mean gray value
Figure 20: Light induced variance of temporal distribution of gray values versus lightinduced mean gray value
Overall System Gain The overall system gain K is computed according to the math-ematical model as:
K =σ2
y.temp − σ2y.temp.dark
µy − µy.dark
(8)
which describes the linear correspondence in the diagram 20. Match a line starting atthe origin to the linear part of the data in this diagram. The slope of this line is the overallsystem gain K.
4-24 BASLER A631f
4.3 Raw Measurement Data
4.3.6 Light induced mean gray value
The light induced mean gray value µy − µy.dark in [ DN] is plotted versus the number ofphotons collected in a pixel during exposure time Kµp in [ p ∼].
3500
3000
2500
2000
1500
1000
500
0
Mea
n gr
ay v
alue
(br
ight
- d
ark)
[DN
]
25x103
20151050
Mean photon [Photons/pixel]
A631f (19 cameras), Difference mean gray value
Figure 21: Light induced mean gray value versus the number of photons
Total Quantum Efficiency The total quantum efficiency η is computed according tothe mathematical model as:
η =µy − µy.dark
Kµp
(9)
which describes the linear correspondence in the diagram 21. Match a line starting atthe origin to the linear part of the data in this diagram. The slope of this line divided bythe overall system gain K yields the total quantum efficiency η.
The number of photons µp are calculated using the model for monochrome light. Thenumber of photons Φp collected in the geometric pixel per unit exposure time [p∼/s] isgiven by
Φp =EAλ
hc(10)
with the irradiance E on the sensor surface [W/m2] , the area A of the (geometrical)pixel [m2] , the wavelength λ of light [m] , the Planck’s constant h ≈ 6.63 · 10−34 Js andthe speed of light c ≈ 3 · 108 m/s. The number of photons can be calculated by
µp = ΦpTexp (11)
BASLER A631f 4-25
4.3 Raw Measurement Data
during the exposure time Texp. Using equation 9 and the number of photons µp, the totalquantum efficiency η can be calculated as
η =hc
ATexp
1
E
1
λ
µp − µy.dark
K. (12)
4.3.7 Dark current versus housing temperature
Logarithm to the base 2 of the dark current in [e−/s] versus deviation of the housingtemperature from 30◦C in [ ◦ C]
Not measured!
4-26 BASLER A631f
5 Characterizing Total and Spatial Noise
5 Characterizing Total and Spatial Noise
5.1 Basic Parameters
5.1.1 Spatial offset noise
Standard deviation of the spatial offset noise σo referenced to electrons in [ e−].
3.0
2.5
2.0
1.5
1.0
0.5
0.0
DS
NU
1288
[e-]
151050
Camera
A631f (19 cameras), DSNU1288
8
6
4
2
0
Num
ber
3.23.02.82.62.4
DSNU1288 [e-]
A631f (19 cameras), DSNU1288 histogram
Figure 22: Spatial offset noise ( DSNU1288 )
Item Symbol Typ. Std. dev. Unit Remarks
Spatial offset noise ( DSNU1288 ) σo 2.6 0.3 e−
Table 12: Spatial offset noise ( DSNU1288 )
BASLER A631f 5-27
5.1 Basic Parameters
5.1.2 Spatial gain noise
Standard deviation of the spatial gain noise Sg in [ %].
1.0
0.8
0.6
0.4
0.2
0.0
PR
NU
1288
[%]
151050
Camera
A631f (19 cameras), PRNU1288
7
6
5
4
3
2
1
0
Num
ber
1.11.00.90.80.70.6
PRNU1288 [%]
A631f (19 cameras), PRNU1288 histogram
Figure 23: Spatial gain noise ( PRNU1288 )
Item Symbol Typ. Std. dev. Unit Remarks
Spatial gain noise ( PRNU1288 ) Sg 0.9 0.1 %
Table 13: Spatial gain noise ( PRNU1288 )
5-28 BASLER A631f
5.1 Basic Parameters
5.1.3 Spectrogram Spatial Noise
Spectrogram referenced to photons in [p∼] is plotted versus spatial frequency in [1/pixel]for no light, 50% saturation and 90% saturation.
100
80
60
40
20
0
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), Spatial FFT dark
All Mean
456
10
2
3
456
100
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), Spatial FFT dark
All Mean
Figure 24: Spectrogram referenced to photons for no light
BASLER A631f 5-29
5.1 Basic Parameters
2500
2000
1500
1000
500
0
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), Spatial FFT saturation 0.5
All Mean
68
100
2
4
6
81000
2
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), Spatial FFT saturation 0.5
All Mean
Figure 25: Spectrogram referenced to photons for 50% saturation
5-30 BASLER A631f
5.1 Basic Parameters
4000
3000
2000
1000
0
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), Spatial FFT saturation 0.9
All Mean
100
2
4
68
1000
2
4
FF
T a
mpl
itude
[p~
]
10008006004002000
A631f (19 cameras), Spatial FFT saturation 0.9
All Mean
Figure 26: Spectrogram referenced to photons for 90% saturation
BASLER A631f 5-31
5.1 Basic Parameters
5.1.4 Spatial Non-Whiteness Coefficient
The non-whiteness coefficient is plotted versus the number of photons µp in [p∼] col-lected in a pixel during exposure time.
4
3
2
1
0
Spa
tial n
on w
hite
ness
25x103
2015105
Mean photon [Photons/pixel]
A631f (19 cameras), Spatial non whiteness
Figure 27: Spatial Non-whiteness coefficient
5-32 BASLER A631f
5.2 Raw Measurement Data
5.2 Raw Measurement Data
5.2.1 Standard deviation of the spatial dark noise
Standard deviation of the spatial dark noise in [DN] versus exposure time in [s] .
1.0
0.8
0.6
0.4
0.2
0.0Spa
tial s
td g
ray
valu
e da
rk [e
-]
20x103
15105
Exposure time [us]
A631f (19 cameras), Spatial std gray value dark
Figure 28: Standard deviation of the spatial dark noise
From the mathematical model, it follows that the variance of the spatial offsetnoise σ2
o should be constant and not dependent on the exosure time. Check that thedata in the figure 28 forms a flat line. Compute the mean of the values in the diagram.The mean divided by the conversion gain K gives the standard deviation of the spatialoffset noise σo .
DSNU1288 = σo =σy.spat.dark
K(13)
The square of the result equals the variance of the spatial offset noise σ2o .
BASLER A631f 5-33
5.2 Raw Measurement Data
5.2.2 Light induced standard deviation of the spatial noise
Light induced standard deviation of the spatial noise in [DN] versus light induced meanof gray values [DN] .
40
30
20
10
0
Std
. dev
. gra
y va
lue
(brig
ht -
dar
k) [D
N]
350030002500200015001000500
Mean gray value (bright - dark) [DN]
A631f (19 cameras), Spatial gain noise
Figure 29: Light induced standard deviation of the spatial noise
The variance coefficient of the spatial gain noise S2g or its standard deviation
value Sg respective, is computed according to the mathematical model as
PRNU1288 = Sg =
√σ2
y.spat − σ2y.spat.dark
µy − µy.dark
, (14)
which describes the linear correspondence in the figure 29. Match a line through theorigin to the linear part of the data. The line’s slope equals the standard deviation valueof the spatial gain noise Sg .
5-34 BASLER A631f
REFERENCES
References
[1] EUROPEAN MACHINE VISION ASSOCIATION (EMVA): EMVA Standard 1288 - Stan-dard for Characterization and Presentation of Specification Data for Image Sensorsand Cameras (Release A1.03). 2006
BASLER A631f 5-35