ISO Speed Rick Baer February 10, 2005
Outline Introduction Understanding ISO speed ISO speed characterization ISO speed and image processing Summary
ISO Speed February 10, 2005
2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
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Introduction •ISO speed is useful in still photography because it determines the nominal exposure conditions. •The ISO (ASA) speed metric was originally developed to describe the sensitivity of silver-halide film. The relationship between speed and image quality is only implicit. •The ISO 12232 standard defines an ISO speed metric for digital cameras (and solid-state image sensors) that is explicitly related to image quality. •ISO speed does not apply to imaging at non-visible wavelengths. ISO Speed February 10, 2005
2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
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Understanding ISO speed Exposure controls & metering ISO speed of film ISO speed of a solid-state image sensor
ISO Speed February 10, 2005
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Basic exposure controls Exposure ~ number of incident photons shutter (period)
sensor
aperture (f#)
ISO Speed February 10, 2005
n.d. filter (density)
2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
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Why control exposure? Dynamic range Shutter speed control Aperture control – depth of field
ISO Speed February 10, 2005
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Underexposure
ISO Speed February 10, 2005
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Correct exposure
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Overexposure
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Slow shutter
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Fast shutter
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Wide aperture
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Narrow aperture
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Exposure index
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How exposure is controlled with a lightmeter:
1. Set the exposure index (nominally equal to ISO speed) 2. Select an aperture (f#) and read the shutter speed -or2. Select a shutter speed and read the aperture sensor/film exposure index
aperture value
( f # ) 2 EI La = t 15.4 shutter speed ISO Speed February 10, 2005
average scene luminance
2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
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What is the exposure index?
8 EI = Hg
≈
10 Ha
Where: = geometric mean focal plane exposure
used in electronic imaging systems, ISO 12232
= arithmetic mean focal plane exposure Ef (focal plane illuminance) [lux] = ⋅ Te lens ISO Speed February 10, 2005
sensor
2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
[lux-seconds] Page 16
Es
Relationship between scene illuminance and focal plane illuminance focal plane illuminance (lux)
scene illuminance (lux)
Ef =
4 ( f # ) (1 + m )
Typical scene illuminance levels: Direct sunlight 100,000 lux Indirect sunlight 10,000 Overcast 1,000 Office 300 Pub 10 Full moon 0.1 ISO Speed February 10, 2005
Es R 2
2
Ef
scene reflectivity (lux) image magnification
Ef ≈ .006 Es For R = 18%, f# = 2.8, m = 0 (1.8 focal-plane lux with office lighting)
2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
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Photopic units
photopic units (lux) describe light intensity as perceived by a human observer
yλ
∞
Φ v = 680 ∫ yλ Φ e (λ )dλ 0
luminous flux (lumens) ISO Speed February 10, 2005
photopic response function
spectral flux (Watts)
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How many photons are there?
1 lux = 1 lumen / m2 ~ 10000 photons/sec/um2 (for a spectrally broad illuminant)
Example: office lighting, 10 um2 pixel, 1/120 second exposure Æ 1500 photons/pixel
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ISO speed and exposure index
•The correct exposure for a particular scene determines the exposure index. exposure compensation
•The ISO speed is equal to the exposure index for a statistically average scene.
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High-key scene
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Low-key scene
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Relationship between ISO speed and (digital) image quality •The gain applied to a solid-state sensor can be adjusted to change the ISO speed •Image quality (SNR) depends on ISO speed
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ISO = 200
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ISO = 3200
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ISO speed comparisons are meaningless unless image quality is considered!
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ISO speed of film Speed range of commercial film Speed versus quality tradeoff ISO measurement procedure
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Color negative film
ISO 100
ISO 1600 B&W film
ISO 400 ISO Speed February 10, 2005
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Speed versus quality
Film response is nonlinear Film is a threshold detector Grain noise is more important than shot noise Grain size increases with film speed
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Scanned film
(ISO 100) ISO Speed February 10, 2005
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(ISO 800) Page 30
Measurement apparatus calibrated lux meter
variable aperture
shutter speed control camera body (no lens)
Calibrated light source
integrating sphere IR filter
densitometry ISO Speed February 10, 2005
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processing Page 31
Measurement procedure 1. Use aperture and shutter to vary focal plane exposure from frame to frame. 2. Process film for gamma = 0.615 3. Measure film density versus focal plane exposure 4. Plot density versus log exposure 5. Determine exposure intercept at (fog + 0.1) density 6. ISO speed = 0.8 / En
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(film density plot)
ISO = 0.8/En = 0.8/10-2.2 = 125 ISO Speed February 10, 2005
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The ISO characterization methods used for film are not applicable to solid-state image sensors, with linear responses and different noise mechanisms.
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ISO speed of a solid-state image sensor Comparison of film and solid-state sensors ISO 12232 methodology Monochrome image sensor model Color image sensor model
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Comparison of film and solid-state image sensors
camera
film
film developer
may incorporate camera functions (e.g. metering, shutter)
camera
image sensor
may be integrated!
image processor
Image sensors and digital processing compare with film and developing ISO Speed February 10, 2005
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ISO 12232 methodology
•Determine focal plane exposure (H) required to obtain a particular SNR value •Specify ISO speed range: • Snoise10 = 10/H @ SNR = 10 (first acceptable image) • Snoise40 = 10/H @ SNR = 40 (first excellent image)
•Specify ISO speed at saturation • Ssat = 78 / H @ saturation
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vary illumination, shutter speed to control focal plane exposure H
V measure SNR of output signal
sensor test camera
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SNR 40 30 20 10
H10
H40 Hsat
S = 10/H ISO Speed February 10, 2005
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H S = 78/H Page 39
ISO speed model for monochrome image sensors
•Determine H required to achieve specified SNR •ISO speed = 10/ H
photopic response
x
H signal electrons
x QE
noise model
÷
SNR
noise electrons
read noise, dark current ISO Speed February 10, 2005
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Photopic quantum efficiency (photopic electrons per lux)
focal plane lux
signal electrons photopic response function
Planckian radiator
Φ e (λ ) = ∞
IR filter
pixel array
−1 α hc / kTλ ( ) e − 1 λ5 ∞
H = 680∫ yλ Φ e (λ )dλ
Ne = ∫
0
0
λ IR (λ ) QE(λ ) Φ e (λ ) hc
dλ
ηp = N e / H ISO Speed February 10, 2005
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Typical photopic QE for a monochrome image sensor (Panasonic MN3776; peak QE = 50%) Photopic QE 4.5 4
kiloelectrons/(lux-µ m2)
3.5 3 2.5 2 1.5 1 0.5 0 2500
3000
3500
4000
4500
5000
5500
6000
6500
7000
color temperature [K] ISO Speed February 10, 2005
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Noise model
integration time [sec] dark current [e-/sec]
x
sum of powers of uncorrelated noise sources
X2 signal electrons [e-]
= shot noise power
x PRNU ISO Speed February 10, 2005
X2
Σ X2
r.m.s. noise electrons [e-]
read noise [e-]
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(*** neglecting PRNU ***)
Derivation of ISO speed equation Photopic
QE
pixel area
ηp A H S = N x η p A H + Nr 2
focal plane exposure read noise
shot noise
20 η p A 4 Nr 1+ 1+ Sx = 2 2 (S / N) x (S / N ) x 2
−1
•ISO noise speed increases linearly with QE and pixel area •“Acceptable” noise speed (SNR=10) depends on electronic noise ISO Speed February 10, 2005
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SNR curves SNR vs. charge 3
Achievable SNR limited by PRNU
2.5
log10( SNR )
2
shot noise only 1.5
NR = 10, PRNU = 0.01 Nr = 10, PRNU = 0
1
0.5
0 0
1
2
3
4
5
6
log10( electrons)
Read noise only affects “acceptable” ISO speed ISO Speed February 10, 2005
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ISO speed curves for a typical sensor
(*** neglecting PRNU ***)
ηP = 3.7 ke, Nr =10 e, Nsat = 20 ke Monochrome ISO speed 5000
ISO speed
4000
3000 acceptable excellent saturation 2000
1000
0 2
3
4
5
6
7
8
9
10
pixel pitch [um] ISO Speed February 10, 2005
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Effect of IR and UV (wavelengths outside photopic response range) Black body emission 100% 90%
Relative photon flux
80% 70% 60%
far IR near IR visible UV
50% 40% 30% 20% 10% 0% 2000
3000
4000
5000
6000
7000
8000
9000
10000
Temperature [K]
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ISO speed ratio for BB source, w & w/o IR filter Photopic response with IRF / photopic response w/o IRF 3
2.5
Ratio
2
1.5
1
0.5
0 2500
3000
3500
4000
4500
5000
5500
6000
6500
7000
Color temperature [K]
ISO Speed February 10, 2005
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Effect of dark current In the low-SNR, high noise limit:
Sa ≈ ISO “acceptable” speed
10 η p A Nd Te
dark current [e/sec]
exposure period
ISO speed varies inversely with exposure period: longer integration times don’t help! ISO Speed February 10, 2005
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The high ISO speeds of solid-state image sensors (compared to film) are a consequence of the higher QE of silicon.
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ISO speed characterization Camera characterization: ISO 12232 Sensor characterization: QE and noise
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ISO 12232 procedures for determining speed Direct focal plane exposure method Indirect scene luminance method
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Measurement apparatus (direct focal plane exposure) variable aperture
calibrated lux meter shutter speed control camera body (no lens) baffle
Calibrated light source (fixed color temperature)
integrating sphere IR (& UV) filter
raw digital output
Measure SNR versus focal plane exposure ISO Speed February 10, 2005
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Illumination control
The angular spread of illumination must match the lens f#.
f# = d/z z
without baffle
Sony ICX252 angular response 120%
F3.5
f2.8 f2.0
f1.4
f0.6
100%
80%
Response [rel.]
d
horz vert
60%
40%
20%
0% 0.00
5.00
10.00
15.00
20.00
25.00
30.00
Incidence Angle [deg.]
ISO Speed February 10, 2005
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Other requirements
•Linear data (raw data or linearized) •No lossy compression •Proper white balance •Integration period < 1/30 s (may need aperture control) •Consider only central pixels when sensors include microlenses
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SNR curve (monochrome CCD) SNR vs. focal plane exposure 60
50
SNR
40
30
20
10
0 0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Focal plane exposure (lux-sec)
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ISO speed from SNR curve SNR vs. focal plane exposure 60
50
SNR
40
30
20
10
0 0
0.01
S10 = 10/0.0044 = 2300 ISO Speed February 10, 2005
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Focal plane exposure (lux-sec)
S40 = 10/0.046 = 218
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Measurement apparatus (indirect scene luminance: reflection) light source color meter luminance meter
scene luminance
shutter speed control
lux meter
camera
(alternative to luminance meter)
lens diffuse reflection target
baffle
(used to adjust luminance)
variac
raw digital output
(used to adjust source color temperature)
Measure SNR versus (scene luminance ⋅ ISO Speed February 10, 2005
2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
exposure time) Page 58
Measurement apparatus (indirect scene luminance: transmission) variac
color meter
luminance meter
scene luminance
shutter speed control camera lens
light source baffle
diffuser
transmission target raw digital output
ISO Speed February 10, 2005
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Equation relating focal plane exposure to target luminance luminance
Integration time
65 La t Ha = 100 ( f # ) 2 (1 + m ) 2
Calculate speed as 10/Ha @ SNR = x (as before)
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Need for OECF characterization: perform analysis on OECF target
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SNR curve from OECF target OECF target method 50.0 45.0 40.0 35.0
SNR
30.0 25.0 20.0 15.0 10.0 5.0 0.0 0
2
4
6
8
10
12
patch number
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Sensor characterization: QE and noise QE measurement Noise characterization
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ISO speed calculation from QE and noise (monochrome case) spectral measurements QE(λ) IR(λ) noise parameters noise measurements
ISO Speed February 10, 2005
photopic QE calculation
ηp
noise model
Nr
ISO speed equation
ISO speed range
operating parameters (gain, temp., etc.) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
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ISO speed calculation from QE and noise (color case) color correction matrix calculation
spectral measurements QE(λ) IR(λ) noise parameters noise measurements
ISO Speed February 10, 2005
photopic QE calculation
ηp
noise model
Nr
ISO speed model
ISO speed range
operating parameters (gain, temp., etc.) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
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reference output
QE measurement variable aperture
monochrometer
calibration photodiode
reference photodiode
shutter speed control camera body (no lens) baffle light source low-pass filter
integrating sphere raw digital output Measure QE versus λ
ISO Speed February 10, 2005
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CC matrix determination
From QE curve From Macbeth chart
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Noise measurement
(see ISO 15739 standard) ISO Speed February 10, 2005
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Example: CCD for a typical consumer digital camera Nr = 8 e
50%
40%
Nsat = 10 ke
QE [%]
30%
20%
PRNU = 1%
10%
0% 360
410
460
510
560
610
660
710
760
Wavelength [nm]
Sony ICX202 For 3 um pixel pitch: Acceptable quality speed: SA = 285 Speed range: ~ 50 - 400 ISO Speed February 10, 2005
Excellent quality speed: SE = 23 Saturation speed: Ssat = 72
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Effect of signal processing on ISO speed •Five (coupled) dimensions of image quality •Effects of common image processing functions • Demosaic • Vignetting correction • Sharpening • Tone mapping • Color space conversion • Compression ISO Speed February 10, 2005
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Five (coupled) dimensions of image quality The five “R’s” of image quality Resolution (pixel count, MTF) snR (ISO noise speed) dnR (ISO saturation speed) Reproduction (exposure control, color and tone reproduction) aRtifacts (demosaic and sampling artifacts, flare)
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Coupling between image quality dimensions
(high resolution, high-noise)
ISO Speed February 10, 2005
(low resolution, low-noise)
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Coupling between ISO speed and other IQ dimensions aRtifacts Reproduction
Resolution
DNR SNR (ISO speed)
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Coupling between ISO speed and other IQ dimensions aRtifacts Reproduction
Resolution
DNR SNR (ISO speed)
ISO Speed February 10, 2005
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Demosaic Bayer mosaic pattern
σR
σ’R
bilinear reconstruction
σ G′ = 9 / 16 σ G
σ R′ = 5 / 8 σ R
σ B′ = 5 / 8 σ B
Bilinear reconstruction reduces noise (at the expense of resolution) ISO Speed February 10, 2005
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Vignetting correction
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Sharpening ~ 30% noise increase
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Tone mapping
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Color space conversion RGB 888 Æ YUV 422, YUV 411 …
Chrominance down-sampling reduces color noise
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Compression
original image
ISO Speed February 10, 2005
JPEG compressed
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Summary ISO speed is a valuable quality metric for the solid-state sensors used in (visible) photography. Different combinations of measurement and analysis can be used to obtain the ISO speed. Digital processing can improve one dimension of image quality at the expense of others. All dimensions of IQ must be considered together in sensor comparisons. Total IQ:
ISO Speed February 10, 2005
(ISO speed) × resolution {also true for DNR} ∝ QE × (sensor area) Size matters! 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
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Acknowledgements •Albert Theuwissen and the organizers of this forum •Jack Holm
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References 1.
ISO 12232: Photography – Electronic still-picture cameras – Determination of ISO speed (1998)
2.
M. Kriss, “A model for equivalent ISO CCD camera speeds”, SPIE Vol. 3302, pg. 56-67 (1998)
3.
J. Holm, “The photographic sensitivity of electronic still cameras”, J. Soc. Photogr. Sci. Tech. Japan, Vol. 59, No. 1, pg. 117-131 (1996).
4.
R. Baer & J. Holm, “A model for calculating the potential ISO speeds of digital still cameras based upon CCD characteristics”, IS&T PICS Conference, pg. 35-38 (1999).
5.
R. Palum, “How many photons are there?”, IS&T PICS Conference, pg. 203-206 (2002).
6.
J. Holm, “Challenges and progress in digital photography standards”, SPIE Vol. 5294 (2004).
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Appendices •ISO speed model for color image sensors
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ISO speed model for color image sensors
Assumptions: 1. Independent RGB color samples at every pixel location 2. No image processing other than white balance and color correction (e.g. no tone correction, sharpening, compression)
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Extension of monochrome model to color
photopic response x x
H R,G,B signal electrons
QE vector
white balance
noise model
read noise, dark current
ISO Speed February 10, 2005
color correction
R,G,B noise electrons
white balance
RGB to Y
÷
SNR
color correction RGB to Y-cb-cr
2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors
Y-cb-cr to perceived noise
Page 86
Spectral response => photopic QE vector IR filter
5500K black body
SONY ICX224AQ
1.0
100%
40%
0.8
80%
R elative pow er
T r a n s m is s io n
30%
QE [%]
0.6
0.4
10%
0.2
0.0 360
20%
560
660
760
860
360
460
560
660
760
0% 360
860
∞
Ne = ∫ 0
460
560
660
760
860
Wavelength [nm]
Wavelength [nm]
Wavelength [nm]
λ IR (λ ) QE(λ ) Φ e (λ ) hc
ηp = N e / H ISO Speed February 10, 2005
40%
20%
0%
460
60%
dλ
[electrons/lux-second]
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White balance
Calculate coefficients from photopic QE vector
R G/R 0 0 R G = 0 1 0 ⋅G B 0 0 G/B B Apply to noise vector
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Color correction and spectral response SONY ICX224AQ 40%
QE [%]
30%
20%
10%
0% 360
460
560
660
760
860
Wavelength [nm]
Compute color correction matrix from spectral response, or Macbeth chart image
a12
a13 R
G = a 21 a 22
a 23 ⋅ G
a 31
a 33 B
R B ISO Speed February 10, 2005
a11
a 32
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Color noise
luminance noise
Y = 0.2125 R + 0.7154 G + 0.0721 B
chrominance noise luminance equation
σ (D ) = σ 2 Y + 0.279 σ 2 R − Y + 0.088 σ 2 B− Y ISO Speed February 10, 2005
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total noise Page 90
Color versus monochrome sensitivity
Monochrome compared to color: •Higher peak QE •Broader spectral response Æ ISO speed ~ 10 times greater
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