Analysis and Suppression of Image Sensor Nonuniformities
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- Basil Wilcox
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1 Analysis and Suppression of Image Sensor Nonuniformities Bernd Jähne Chair EMVA 188 Standard Group Heidelberg Collaboratory for Image Processing (HCI) Interdisciplinary Center for Scientific Computing University of Heidelberg Forum Bildverarbeitung, Fraunhofer IOSB, Karlsruhe, Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
2 Outline Outline Classes of image sensors Key parameters for image quality according to the EMVA 188 standard: Signal-to-noise ratio and derivated parameters Nonuniformities DSNU and PRNU To which degree can nonuniformities be corrected? Outlook and further material Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
3 Classes of Image Sensors Classes of Image Sensors Most important and most used classes considered: 1 Interline CCD sensors Sony ICX85, 6,45 µm Pixel and ICX618, 5,6 µm pixel Rolling-shutter CMOS sensors Aptina/On Semiconductor MT9P031, ,, µm pixel 3 Global-shutter CMOS sensors On MT9V03, , 6 µm pixel CMOSIS CMV1000, , 5,5 µm Pixel On Phython NOIP1SN0500A, , 4,8 µm Pixel Sony Pregius IMX174, 5,86 µm Pixel and IMX50, 3,45 µm pixel 4 High-end scientific CMOS sensors (scmos) Fairchild/Andor/PCO CIS51, , 6,5 µm pixel Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
4 Schlüsselparameter nach EMVA 188 Linear Camera Model Physical Model of Imaging... black box camera... photon noise quantum efficiency µ p, σ p µ e, µ e η dark noise µ d, σ d quantization noise system gain K σ q µ y, σ y number of photons input number of electrons black box camera digital grey value output Input: photons, output: digital numbers Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
5 Schlüsselparameter nach EMVA 188 Linear Camera Model Physical Model of Imaging photon noise quantum efficiency µ p, σ p µ e, σ e η dark noise µ d, σ d quantization noise system gain K σ q µ y, σ y number of photons input number of electrons sensor/camera digital grey value output Estimate unknown model parameters quantum efficiency η, camera gain K in DN/e and dark noise σ d in e (µ d not critical, just offset) from measured quantities µ p, µ y and σ y (unknowns red, measured blue) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
6 Schlüsselparameter nach EMVA 188 Signal-to-Noise Ratio SNR Signal-to-Noise Ratio SNR SNR(µ p ) = Signal Rauschen = µ y σ y = ηµ p σd + ηµ p (1) (neglecting quantization noise) Limiting cases: Ideal camera (η = 1, σ d = 0): ηµp SNR(µ p ) ηµ p σ d ηµ p σ d ηµ p σ d () SNR ideal = µ p (3) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
7 Schlüsselparameter nach EMVA 188 Nonuniformities Horizontal and Vertical Profiles New in Release 3.1, versatile to analyse all kinds of nonuniformities using four plots Row/column in the middle: shows typical row Mean: shows mean horizontal and vertical profiles; suppresses spatial variations of indiviudal pixel; column and row variations remain Maximal value: shows positive outliers, pixels or whole rows/columns (e.g. hot pixel ) Minimal value: shows positive outliers, pixels or whole rows/columns (e.g. less sensitive pixel) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
8 Schlüsselparameter nach EMVA 188 Nonuniformities Horizontal DSNU Profile 30 Horizontal lines DSNU m014, 59nm, min mean middle max dark gray value (DN) Pixel position Fast high-end CMOS camera Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
9 Schlüsselparameter nach EMVA 188 Nonuniformities Horizontal PRNU Profile 106 Horizontal lines PRNU m014, 59nm, rel. sensitivity (%) min mean middle max Pixel position Fast high-end CMOS camera Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
10 Schlüsselparameter nach EMVA 188 Nonuniformities DSNU 188 and PRNU 188 DSNU 188 : Spatial standard deviation dark image, y dark (units e ) DSNU 188 = s y.dark /K (4) PRNU 188 : Relative spatial standard deviation sensitivity at 50% saturation, r = y 50 y dark (given in %) PRNU 188 = s r µ r (5) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
11 Schlüsselparameter nach EMVA 188 Nonuniformities Total SNR Addition of variances from temporal noise and spatial inhomogeneities in units e : Variance from DSNU: s y.dark = DSNU 188 Variance from PRNU: PRNU 188 (ηµ p ) total SNR total SNR total (µ p ) = ηµ p σ d + DSNU ηµ p + PRNU 188 (ηµ p ) (6) New branch in SNR curve, limits SNR total (µ p ) to 1/PRNU 188 Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
12 Schlüsselparameter nach EMVA 188 Nonuniformities Total SNR: CCD ICX SNR m053, 53nm, mono data mono fit mono fit total theor. limit 10 threshold SNR = 1 SNR saturation irradiation (photons/pixel) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
13 Schlüsselparameter nach EMVA 188 Nonuniformities Total SNR: Rolling-Shutter CMOS MT9P SNR m0791, 534 nm, mono data mono fit mono fit total theor. limit 10 threshold SNR = 1 SNR saturation irradiation (photons/pixel) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
14 Schlüsselparameter nach EMVA 188 Nonuniformities Total SNR: Global-Shutter CMOS MT9V SNR m094, 534 nm, mono data mono fit mono fit total theor. limit 10 threshold SNR = 1 SNR saturation irradiation (photons/pixel) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
15 Schlüsselparameter nach EMVA 188 Nonuniformities Total SNR: scmos CIS SNR m0774, 534 nm, mono data mono fit mono fit total theor. limit 10 threshold SNR = 1 SNR saturation irradiation (photons/pixel) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
16 Correction of Nonuniformities Why are nonuniformities not corrected better? Deviation from linear camera model: each pixel has slightly different non-linearity Drifts and instabilities PRNU depends on wavelength of irradiation Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
17 Correction of Nonuniformities Linear Model Correction of DSNU and PRNU With linear camera model relative PRNU should be equal for all saturations y y dark = y 50 y dark (7) µ y µ y.dark µ y.50 µ y.dark Correction of PRNU by simple two-point calibration y = y y dark y 50 y dark (µ y.50 µ y.dark ) (8) Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
18 Correction of Nonuniformities Wavelength Dependency of PRNU Wavelength Dependency of PRNU 467 nm, contrast enhanced to ±3 PRNU 188 Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
19 Correction of Nonuniformities Wavelength Dependency of PRNU Wavelength Dependency of PRNU 53 nm, contrast enhanced to ±3 PRNU 188 Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
20 Correction of Nonuniformities Wavelength Dependency of PRNU Wavelength Dependency of PRNU 69 nm, contrast enhanced to ±3 PRNU 188 Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
21 Correction of Nonuniformities Wavelength Dependency of PRNU Wavelength Dependency of PRNU 846 nm, contrast enhanced to ±3 PRNU 188 Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
22 Correction of Nonuniformities Residual PRNU Residual PRNU: CCD ICX 618 rel. sensitivity (%) Measured PRNU 1.01%, residual PRNU 188 < 0.18% Residual PRNU m0567, 53nm, pixel position rel. sensitivity (%) Residual color PRNU m0567, pixel position 10% sat. 100% sat. 467nm 53nm 69nm 846nm Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
23 Correction of Nonuniformities Residual PRNU Residual PRNU: Rolling-Shutter CMOS On MT9P031 rel. sensitivity (%) Measured PRNU 1.78%, residual PRNU 188 < 0.7% Residual PRNU m0791, 534 nm, pixel position rel. sensitivity (%) 5 0 Residual color PRNU m0791, pixel position 10% sat. 100% sat. 466 nm 534 nm 630 nm 848 nm Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
24 Correction of Nonuniformities Residual PRNU Residual PRNU: Global-Shutter CMOS On MT9V03 rel. sensitivity (%) Measured PRNU 1.7%, residual PRNU 188 < 0.7% Residual PRNU m094, 534 nm, pixel position rel. sensitivity (%) Residual color PRNU m094, pixel position 10% sat. 100% sat. 466 nm 534 nm 630 nm 848 nm Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
25 Correction of Nonuniformities Residual PRNU Residual PRNU: scmos CIS51 rel. sensitivity (%) Measured PRNU 0.63%, residual PRNU 188 < 0.8% Residual PRNU m0774, 534 nm, pixel position rel. sensitivity (%) Residual color PRNU m0774, pixel position 10% sat. 100% sat. 466 nm 534 nm 630 nm 848 nm Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
26 Correction of Nonuniformities Residual PRNU Residual PRNU: Global-Shutter CMOS Sony IMX174 rel. sensitivity (%) Measured PRNU 0.40%, residual PRNU 188 < 0.14% Residual PRNU m0951, 534 nm, pixel position rel. sensitivity (%) Residual color PRNU m0951, pixel position 10% sat. 100% sat. 466 nm 534 nm 630 nm 848 nm Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
27 Further Information Further Information Publication in TM of content of this talk with extensions in preparation Please contact me, if interested New release 3.1 of EMVA 188 with standardized summary datasheet Standard documents & data sheets EMVA 188 Seminars: Framos, Munich, December 6/7, AEON, Hanau, February 8 10, Bernd Jähne (HCI, Heidelberg Univ.) Image Sensor Nonuniformities Forum BV / 7
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