BASLER A631f - CRI JOLANTA · 3.1.1 Illumination Setup Basler-CameraTestTool The illumination during the test of one camera was ﬁxed. The drift of the illumination over a long time

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


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


4.1.2 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


Temporal dark noise σd0 12 0.8 e−

Table 6: Temporal dark noise

BASLER A631f 4-7


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


4.1.5 Inverse of overall system gain


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



3.3 0.11 e−DN

Table 7: Inverse of overall system gain

BASLER A631f 4-9


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


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


4.1.7 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


Saturation capacity µe.sat 13000 600 e−

Table 9: Saturation capacity

BASLER A631f 4-11


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


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


All Mean

Figure 9: Spectrogram referenced to photons for 50% saturation

BASLER A631f 4-13


4000

3000

2000

1000

0

FF

T a

mpl

itude

[p~

]

10008006004002000


All Mean

3

4

56

1000

2

3

4

FF

T a

mpl

itude

[p~

]

10008006004002000


All Mean


4-14 BASLER A631f


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


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


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


Output dynamic range DYNout.bit 10.0 0.13 bit

Table 11: Output dynamic range

BASLER A631f 4-19

4.3 Raw Measurement Data


4.3.1 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


A631f (19 cameras), Mean gray value bright

Figure 16: Mean gray values of the cameras with illuminated pixels

4-20 BASLER A631f


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


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


4.3.3 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


4.3.4 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


4.3.5 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


4.3.6 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


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


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


5.1.1 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 )


Spatial offset noise ( DSNU1288 ) σo 2.6 0.3 e−

Table 12: Spatial offset noise ( DSNU1288 )

BASLER A631f 5-27


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 )


Spatial gain noise ( PRNU1288 ) Sg 0.9 0.1 %

Table 13: Spatial gain noise ( PRNU1288 )

5-28 BASLER A631f


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


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


All Mean


5-30 BASLER A631f


4000

3000

2000

1000

0

FF

T a

mpl

itude

[p~

]

10008006004002000


All Mean

100

2

4

68

1000

2

4

FF

T a

mpl

itude

[p~

]

10008006004002000


All Mean


BASLER A631f 5-31


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


A631f (19 cameras), Spatial non whiteness

Figure 27: Spatial Non-whiteness coefficient

5-32 BASLER A631f



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


5.2.2 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

Documents

BASLER A631f - CRI JOLANTA · 3.1.1 Illumination Setup Basler-CameraTestTool The illumination during the test of one camera was ﬁxed. The drift of the illumination over a long time