ISO Speed. Rick Baer. February 10, 2005

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1 Rick Baer

2 Outline Introduction Understanding ISO speed ISO speed characterization ISO speed and image processing Summary 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 2

3 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 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 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 3

4 Understanding ISO speed Exposure controls & metering ISO speed of film ISO speed of a solid-state image sensor 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 4

5 Basic exposure controls Exposure ~ number of incident photons shutter (period) sensor aperture (f#) n.d. filter (density) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 5

6 Why control exposure? Dynamic range Shutter speed control Aperture control depth of field 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 6

7 Underexposure 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 7

8 Correct exposure 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 8

9 Overexposure 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 9

10 Slow shutter 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 10

11 Fast shutter 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 11

12 Wide aperture 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 12

13 Narrow aperture 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 13

14 Exposure index 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 14

15 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 -or- 2. Select a shutter speed and read the aperture aperture value shutter speed ( f 2 #) EI La = t 15.4 average scene luminance sensor/film exposure index 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 15

16 What is the exposure index? 8 10 EI = H g H a Where: <H g > = geometric mean focal plane exposure <H a > = arithmetic mean focal plane exposure used in electronic imaging systems, ISO E f (focal plane illuminance) [lux] <Ha> = <E f > T e lens sensor [lux-seconds] 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 16

17 Relationship between scene illuminance and focal plane illuminance focal plane illuminance (lux) E scene illuminance (lux) f = 4 Typical scene illuminance levels: Direct sunlight 100,000 lux Indirect sunlight 10,000 Overcast 1,000 Office 300 Pub 10 Full moon 0.1 E s R ( ) 2 f # ( 1+ m ) 2 E E f s E s scene reflectivity (lux) image magnification.006 E f 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 Page 17

18 Photopic units y λ photopic units (lux) describe light intensity as perceived by a human observer Φ v = y λ Φ e ( λ) dλ luminous flux (lumens) photopic response function spectral flux (Watts) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 18

19 How many photons are there? 1 lux = 1 lumen / m 2 ~ photons/sec/um 2 (for a spectrally broad illuminant) Example: office lighting, 10 um 2 pixel, 1/120 second exposure 1500 photons/pixel 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 19

20 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 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 20

21 High-key scene 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 21

22 Low-key scene 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 22

23 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 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 23

24 ISO = ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 24

25 ISO = ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 25

26 ISO speed comparisons are meaningless unless image quality is considered! 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 26

27 ISO speed of film Speed range of commercial film Speed versus quality tradeoff ISO measurement procedure 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 27

28 Color negative film ISO 100 ISO 1600 B&W film ISO ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 28

29 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 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 29

30 Scanned film (ISO 100) (ISO 800) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 30

31 Measurement apparatus variable aperture calibrated lux meter shutter speed control camera body (no lens) Calibrated light source IR filter integrating sphere densitometry processing 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 31

32 Measurement procedure 1. Use aperture and shutter to vary focal plane exposure from frame to frame. 2. Process film for gamma = 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 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 32

33 (film density plot) ISO = 0.8/En = 0.8/ = ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 33

34 The ISO characterization methods used for film are not applicable to solid-state image sensors, with linear responses and different noise mechanisms ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 34

35 ISO speed of a solid-state image sensor Comparison of film and solid-state sensors ISO methodology Monochrome image sensor model Color image sensor model 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 35

36 Comparison of film and solid-state image sensors camera film film developer may incorporate camera functions (e.g. metering, shutter) may be integrated! camera image sensor image processor Image sensors and digital processing compare with film and developing 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 36

37 ISO methodology Determine focal plane exposure (H) required to obtain a particular SNR value Specify ISO speed range: S noise10 = SNR = 10 (first acceptable image) S noise40 = SNR = 40 (first excellent image) Specify ISO speed at saturation S sat = 78 / saturation 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 37

38 vary illumination, shutter speed to control focal plane exposure H V measure SNR of output signal sensor test camera 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 38

39 SNR H 10 H 40 H sat H S = 10/H S = 78/H 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 39

40 ISO speed model for monochrome image sensors Determine H required to achieve specified SNR ISO speed = 10/ H photopic response x H x QE noise model signal electrons noise electrons SNR read noise, dark current 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 40

41 Photopic quantum efficiency (photopic electrons per lux) focal plane lux signal electrons photopic response function Planckian radiator IR filter pixel array H = y λ Φ e ( λ) dλ Φ e α λ hc / ktλ ( λ) = ( e ) N e = 0 λ IR( λ) QE( λ) h c Φ e ( λ) d λ η p = N e / H 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 41

42 Typical photopic QE for a monochrome image sensor (Panasonic MN3776; peak QE = 50%) Photopic QE kiloelectrons/(lux-µm 2 ) color temperature [K] 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 42

43 Noise model integration time [sec] dark current [e-/sec] x sum of powers of uncorrelated noise sources X 2 signal electrons [e-] = shot noise power x X 2 Σ X 2 r.m.s. noise electrons [e-] PRNU read noise [e-] 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 43

44 Derivation of ISO speed equation (*** neglecting PRNU ***) Photopic QE S N shot noise η p A H = x η A H + Nr p pixel area 2 focal plane exposure read noise S x = 20 η (S/ p N) A 2 x Nr (S/ 2 N) 2 x 1 ISO noise speed increases linearly with QE and pixel area Acceptable noise speed (SNR=10) depends on electronic noise 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 44

45 SNR curves SNR vs. charge Achievable SNR limited by PRNU log10( SNR ) shot noise only NR = 10, PRNU = 0.01 Nr = 10, PRNU = log10( electrons) Read noise only affects acceptable ISO speed 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 45

46 ISO speed curves for a typical sensor (*** neglecting PRNU ***) η P = 3.7 ke, Nr =10 e, N sat = 20 ke Monochrome ISO speed ISO speed acceptable excellent saturation pixel pitch [um] 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 46

47 Effect of IR and UV (wavelengths outside photopic response range) Black body emission 100% 90% 80% Relative photon flux 70% 60% 50% 40% 30% far IR near IR visible UV 20% 10% 0% Temperature [K] 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 47

48 ISO speed ratio for BB source, w & w/o IR filter Photopic response with IRF / photopic response w/o IRF Ratio Color temperature [K] 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 48

49 Effect of dark current In the low-snr, high noise limit: ISO acceptable speed S a 10 η p dark current [e/sec] Nd A Te exposure period ISO speed varies inversely with exposure period: longer integration times don t help! 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 49

50 The high ISO speeds of solid-state image sensors (compared to film) are a consequence of the higher QE of silicon ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 50

51 ISO speed characterization Camera characterization: ISO Sensor characterization: QE and noise 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 51

52 ISO procedures for determining speed Direct focal plane exposure method Indirect scene luminance method 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 52

53 Measurement apparatus (direct focal plane exposure) variable aperture calibrated lux meter shutter speed control camera body (no lens) Calibrated light source (fixed color temperature) integrating sphere IR (& UV) filter baffle raw digital output Measure SNR versus focal plane exposure 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 53

54 Illumination control f# = d/z z The angular spread of illumination must match the lens f#. d Response [rel.] 120% 100% 80% 60% 40% Sony ICX252 angular response F3.5 f2.8 f2.0 f1.4 f0.6 without baffle horz vert 20% 0% Incidence Angle [deg.] 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 54

55 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 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 55

56 SNR curve (monochrome CCD) SNR vs. focal plane exposure SNR Focal plane exposure (lux-sec) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 56

57 ISO speed from SNR curve SNR vs. focal plane exposure SNR Focal plane exposure (lux-sec) S 10 = 10/ = 2300 S 40 = 10/0.046 = ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 57

58 Measurement apparatus (indirect scene luminance: reflection) color meter light source luminance meter scene luminance lux meter (alternative to luminance meter) lens shutter speed control camera diffuse reflection target baffle (used to adjust luminance) variac (used to adjust source color temperature) Measure SNR versus (scene luminance raw digital output exposure time) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 58

59 variac Measurement apparatus (indirect scene luminance: transmission) color meter luminance meter scene luminance shutter speed control camera light source baffle diffuser transmission target lens raw digital output 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 59

60 Equation relating focal plane exposure to target luminance luminance Integration time H a = 100 ( 65 La t 2 f #) (1 + m ) 2 Calculate speed as SNR = x (as before) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 60

61 Need for OECF characterization: perform analysis on OECF target 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 61

62 SNR curve from OECF target OECF target method SNR patch number 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 62

63 Sensor characterization: QE and noise QE measurement Noise characterization 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 63

64 ISO speed calculation from QE and noise (monochrome case) spectral measurements QE(λ) IR(λ) noise parameters photopic QE calculation noise model η p Nr ISO speed equation ISO speed range noise measurements operating parameters (gain, temp., etc.) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 64

65 ISO speed calculation from QE and noise (color case) spectral measurements noise measurements QE(λ) IR(λ) noise parameters photopic QE calculation noise model operating parameters (gain, temp., etc.) color correction matrix calculation η p Nr ISO speed model ISO speed range 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 65

66 QE measurement variable aperture monochrometer reference photodiode calibration photodiode camera body (no lens) reference output shutter speed control baffle light source low-pass filter integrating sphere raw digital output Measure QE versus λ 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 66

67 CC matrix determination From QE curve From Macbeth chart 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 67

68 Noise measurement (see ISO standard) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 68

69 Example: CCD for a typical consumer digital camera 50% 40% Nr = 8 e QE [%] 30% 20% Nsat = 10 ke 10% 0% Wavelength [nm] Sony ICX202 PRNU = 1% For 3 um pixel pitch: Acceptable quality speed: S A = 285 Speed range: ~ Excellent quality speed: S E = 23 Saturation speed: S sat = ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 69

70 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 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 70

71 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) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 71

72 Coupling between image quality dimensions (high resolution, high-noise) (low resolution, low-noise) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 72

73 Coupling between ISO speed and other IQ dimensions artifacts Reproduction Resolution DNR SNR (ISO speed) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 73

74 Coupling between ISO speed and other IQ dimensions artifacts Reproduction Resolution DNR SNR (ISO speed) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 74

75 Demosaic Bayer mosaic pattern σ R σ R bilinear reconstruction σ G = 9 / 16 σ G R 5/ 8 σ R σ B = 5/ 8 σ B σ = Bilinear reconstruction reduces noise (at the expense of resolution) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 75

76 Vignetting correction 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 76

77 Sharpening ~ 30% noise increase 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 77

78 Tone mapping 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 78

79 Color space conversion RGB 888 YUV 422, YUV 411 Chrominance down-sampling reduces color noise 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 79

80 Compression original image JPEG compressed 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 80

81 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) resolution {also true for DNR} QE (sensor area) Size matters! 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 81

82 Acknowledgements Albert Theuwissen and the organizers of this forum Jack Holm 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 82

83 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 (1998) 3. J. Holm, The photographic sensitivity of electronic still cameras, J. Soc. Photogr. Sci. Tech. Japan, Vol. 59, No. 1, pg (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 (1999). 5. R. Palum, How many photons are there?, IS&T PICS Conference, pg (2002). 6. J. Holm, Challenges and progress in digital photography standards, SPIE Vol (2004) ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 83

84 Appendices ISO speed model for color image sensors 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 84

85 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) 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 85

86 Extension of monochrome model to color photopic response x x QE vector R,G,B signal electrons white balance noise model R,G,B noise electrons color correction white balance RGB to Y color correction H SNR read noise, dark current RGB to Y-cb-cr Y-cb-cr to perceived noise 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 86

87 Spectral response => photopic QE vector IR filter SONY ICX224AQ 5500K black body % 100% % 30% Transm ission QE [%] 20% Relative power 60% 40% % 20% Wavelength [nm] 0% Wavelength [nm] 0% Wavelength [nm] N e = 0 λ IR( λ) QE( λ) h c Φ e ( λ) d λ η p = N e / H [electrons/lux-second] 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 87

88 White balance Calculate coefficients from photopic QE vector R G/R 0 0 R G = G B 0 0 G/B B Apply to noise vector 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 88

89 Color correction and spectral response SONY ICX224AQ 40% 30% QE [%] 20% 10% 0% Wavelength [nm] Compute color correction matrix from spectral response, or Macbeth chart image R a 11 a 12 a 13 R G = a 21 a 22 a 23 G B a 31 a 32 a 33 B 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 89

90 Color noise luminance noise chrominance noise Y R G B = luminance equation σ ( D) = σ 2 Y σ 2 R Y σ 2 B Y total noise 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 90

91 Color versus monochrome sensitivity Monochrome compared to color: Higher peak QE Broader spectral response ISO speed ~ 10 times greater 2005 ISSCC Circuit Design Forum: Characterization of Solid-State Image Sensors Page 91

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