CMOS ACTIVE PIXEL SENSOR TECHNOLOGY

Photobit TECHNOLOGY CMOS ACTIVE PIXEL SENSOR TECHNOLOGY - AN INTRODUCTION Dr. Eric R. Fossum © ER FOSSUM Photobit TECHNOLOGY I Imaging i Systems ...
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Photobit TECHNOLOGY

CMOS ACTIVE PIXEL SENSOR TECHNOLOGY - AN INTRODUCTION Dr. Eric R. Fossum

© ER FOSSUM

Photobit TECHNOLOGY

I Imaging i Systems S t Optics

Timing & Driver Circuits Detector Pixel Array

ASP

Analog Signal Processor Analog to Digital Converter Digital Signal Processor

ADC DSP

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Photobit TECHNOLOGY

• •

Ultrai l t violet

Ph t Photons

A photon is a “bullet” “ off light (quantum ( view off light waves)) Energy is related to wavelength: E = hc/λ

High energy Short wavelength

Low energy Long wavelength

Your eye iis sensitive Y i i from f violet i l to dark d k redd 450 nm - 700 nm Silicon is sensitive from violet to the “near” infrared (not thermal) 400 nm - 1050 nm Silicon is also sensitive to higher photon energies (e.g. x-rays)

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Infrared

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Sources of Photons

• Th Three main i sources – Solar – Incandescent lamp – Fluorescent lamp color temperature’ temperature • Typically characterized by ‘color – Temperature of blackbody with roughly same color distribution – Higher temp means more blue, less red -> looks white

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SPECTRAL RESPONSES

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Relative rresponse

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1 0.9 08 0.8 0.7 0.6 05 0.5 0.4 0.3 0.2 0.1 0 400

Human Eye

Silicon

500

600

700

800

900

Wavelength (nm) UV

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NIR

1000

1100

Photobit TECHNOLOGY

• • •



O ti Optics

Optics (lenses (lenses, mirrors) COLLECT and FOCUS light Optics are measured by focal length (zoom-effect) and by “speed” or F-number (ratio of focal length to diameter) – Light Li ht on sensor iis 1/4F2 x light li ht on scene • Higher F-number means less light on image sensor • Lower F-number mean more light – Iris or diaphragm adjusts F-number by changing effective lens diameter – Typical video cameras are F/2 (so ‘faceplate’ illuminance is 1/16 scene) Standard lens sizes are measured in inches (sort of lens diameter) – e.g. 2/3”, 1/2”, 1/3”, 1/4” etc. – Smaller lens sizes weigh less and cost less - important for portables – Smaller S ll sizes i require i smaller ll iimage sensors and d smaller ll pixel i l sizes i (f (for same # of pixels) and are less sensitive to light – Actual image sensor diagonal is much less than lens size – For example, 1/3” format (8.5 mm) needs 6.1 mm diagonal !

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Pixel Sizes

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• • • • • •

A pixel is a “picture picture element” element More pixels means more RESOLUTION More pixels means more DATA (could be a bad thing) Modern pixel sizes are between 4 and 10 microns Pixels are square if designed for a computer display Pixels have a rectangular shape for TV applications

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FORMAT

Columns

Rows

CIF VGA/TV Megapixel HDTV

352 640 1280 1920

288 480 1024 1120

Total # Pixels 100k 300k 1.3M 2 0M 2.0M

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Pi l Pixels

Vpd p

Cpd Ipd voltage

Vss

time © ER FOSSUM

Photobit C l Filter Color Filt Array A (CFA)

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Re elative respons se

• Each pixel gets covered by a colored filter – We use red, green, blue (RGB) CFA - best match for RGB displays p y in “Bayer” y p pattern – Could use complementary colors (cyan, yellow, magenta) 1 0.9 0.8 07 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 400

Human Eye

Silicon

500

600

700

800

Wavelength (nm)

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900

1000

1100

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Fill Factor F t

• A pixel is divided into a sensing portion and a readout portion • Fill factor is the ratio of sensing area to total area and is typically about 20% for CCDs and CMOS APS Total pixel area S Sensitive iti area

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Photobit TECHNOLOGY

Mi Microlenses l

• Microlenses funnel light away from non-sensitive portions of pixel

Microlens layer y Color filter layer Metal opaque layer Photodiode Silicon substrate

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Photons to Electrons

Photon is absorbed by y silicon and converted to an electron-hole p pair. Typically the electrons (e -) are collected and holes discarded. • Quantum efficiency (QE) is ratio of collected electrons to incident photons over whole p p pixel* and is always y less than unity y for visible light, g and is wavelength dependent. • Depends on: – fill factor – microlenses – design – vertical ti l photosensor h t structure t t – fundamental physics of silicon * some people just use the defined sensitive area to get a higher value but we consider this cheating. One always needs to check how it is defined.

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Photobit Q Quantum t Efficiency Effi i

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APS has h quantum t efficiency ffi i comparable bl to t CCDs CCD 0.7 TI Virtual Phase CCD

0.6 CMOS APS Photodiode-Type

QE

0.5 0.4 Philips FT8 FT CCD

0.3

CMOS APS Photogate-Type

0.2 0.1

Kodak KAI 370 ILT CCD KAI-370

0 400

500

600

700

800

Wavelength (nm) © ER FOSSUM

900

1000

1100

Photobit CMOS A Active ti Pi Pixell

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• • • •

Each pixel has its own output amplifier Pi l are X Pixels X-Y Y addressed Key is low noise readout d t circuit i it Best of CCD detection/readout and d CMOS integration

Photodetector

Active amplifier Row Select

Column O t t Output

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Electrons to Volts

• Th The CONVERSION GAIN d determines i the h amount off volts l per electron for the pixels. • Typical value range is 1-10 1 10 μV/e • Higher value is good but limits total signal that can be handled – e.g. g at 10 μ μV/e -,, 1 volt max = 100,000 , electrons max • Pixel amplifier should introduce minimum noise • Noise is measured in equivalent number of electrons – e.g. 200 μV rms @ 10 μV/e - = 20 e - rms noise

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Volts to Bits

• The ANALOG ANALOG-TO-DIGITAL TO DIGITAL CONVERTER (ADC) converts the voltage from the pixels to a digital word. • The Th ADC may h have an ANALOG SIGNAL PROCESSOR (ASP) to reduce noise and provide additional g p gain before conversion. • ADC has a reference voltage, e.g. 1 Volt, so that digital word is scaled against the reference f voltage. lt A lower l reference f voltage is similar to adding gain. • On-chip p ADCs trade p power for resolution (number of bits) • 8 bits is enough for teleconferencing. 1012 bits bit is i desired d i d ffor di digital it l still till cameras. © ER FOSSUM

ADC REF

BITS 255

1V

0.3 V 0V 000

Photobit Ph t Photons tto Bit Bits

TECHNOLOGY

OPTICS

MICROLENS

COLOR FILTER ARRAY (CFA)

QUANTUM EFFICIENCY (QE)

CONVERSION GAIN (uV/e-)

ASP

ADC

1/4F2 Scene S to Sensor

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Funnels F l Light

Selects S l t Color

IIncludes l d El t Electrons Amplification A lifi ti Fill-Factor to and (no cheating) Volts Noise Suppression

Volts V lt to Bits

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P tC t Post-Capture P Processing i

• S Sensor produces d 8b ((or more)) ffor each h pixel i l • System eventually wants 24b (RGB) for each pixel – Color interpolation required – Color balancing (“white balance”) required • Additional processing used for aperture correction, etc. • Communication is usually bandwidth limited – Compression often required • Interfaces need to have data format and output according to interface specification – Interface I t f controller/data t ll /d t formatter f tt required i d e.g., USB, USB NTSC

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Color Interpolation

• Goal is to get best approximation for RGB at each pixel site • Many possible approaches, e.g.: •Have blue, need green & red • G = average of 4 neighboring greens • R = average of 4 neighboring reds •Have green, need blue & red • B = average of 2 neighboring blues • R = average of 2 neighboring reds •Have red, need green & blue • G = average of 4 neighboring greens • B = average of 4 neighboring blues

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Photobit C l Correction Color C ti

TECHNOLOGY

• Need to correct colors – relative intensities (white balance) – remove mixtures (offdiagonal elements)

⎡ R' ⎤ ⎡ rr ⎢G' ⎥ = ⎢ g ⎢ ⎥ ⎢ r ⎢⎣ B B' ⎥⎦ ⎢⎣ br

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rg gg bg

rb ⎤ ⎥ gb ⎥ bb ⎥⎦

⎡R⎤ ⎢G ⎥ ⎢ ⎥ ⎢⎣ B ⎥⎦

No perfect solution due to filter overlaps and eye response Best-fit by weights to standard color chart h

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A Aperture t C Correction ti

• Interpolation and color correction leads to ‘blurring’ blurring of image since averaging over a neighborhood • Want to restore apparent sharpness to image • Apply simple image sharpening algorithm to ‘green’ image • Apply green correction to red and blue

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Photobit TECHNOLOGY

Compression

• C Communications i i typically i ll lilimited i d iin b bandwidth d id h (bi (bits/sec) / ) • USB, Firewire, POTS, Internet…. • Many different compression techniques – JPEG - still pictures – MPEG - moving pictures (e.g. video) – wavelet – fractal – vector quantization • Few lossless approaches - image quality ALWAYS degrades -b t is but i it acceptable? t bl ? • Poor sensor plus poor compression = very poor image

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Photobit TECHNOLOGY

Camera System

• How design and partition system? Many options options. • Jury is out on ASIC vs. PC-based processing.

SENSOR

CMOS APS

SENSOR

SENSOR

COLOR

COMPRESS

COLOR COMPRESS INTERFACE

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INTERFACE

COMPANION CHIP(S) INTERFACE

COLOR

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• • • •

I Imaging i System-on-a-Chip S t Chi

PROS Possibly lower cost – single package – single-pass testing Smaller footprint / form factor Lower total power dissipation Easier system assembly Increased reliability



• •

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CONS Possibly higher cost - Color filters and microlenses deposited on digital logic - Use of larger than optimal design rules - Lower yield due to large die size Noise corruption due to on-chip digital clocking Power dissipation leads to increase in dark current level

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Cameras and the Internet

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• 1 Gb/s ~ 335 TeraBytes/month • Total Worldwide Internet Traffic 2000* – 20,000 TeraBytes/month, or 60 Gb/s average load – increasing 100%/yr, and about 10% total capacity • A single CIF resolution image sensor PC video camera with 3:1 compression i produces d about b t 10 Mb/ Mb/s. – 6,000 households with live cameras are equivalent to the total worldwide internet traffic • A 1.3 Mpixel sensor at 1000 fps with 10b output produces about 13 Gb/s – 5 High speed high resolution cameras are equivalent to total worldwide internet traffic * “The size and growth rate of the internet”, K.G. Coffman and A. Odlyzko, http://www.firstmonday.dk/issues/issue3_10/coffman/ © ER FOSSUM