Infrared Technology - Seeing the Invisible (Part Two: Camera Technology)

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Through specific applications examples with sample images, this presentation introduces you to the basics of infrared (IR) imaging technology. You will learn that in the IR-world things look different and that you can visualize with an IR camera things which you cannot see with your own eyes. To understand “the why”, we touch on some basics about IR radiation and corresponding imaging sensor technologies.

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Infrared Imaging: Seeing the Invisible

Part Two:

Camera Technology

Sensor incl. digitization

Optics &

Filters

Sensor Cooling (optional)

Gain/Offset

Correction

(NUC)

Defect

Pixel

Correction

Background

Correction

Temp.

Calibration

via

LUT

Drift

Compen-

sation

Firmware • Feature Control • Image Correction • Temperature

Calibration

Interface and I/O Control

Structure of an Infrared Camera

Optics & Filters

SWIR optimized lens Non-optimized lens

Image with / without SWIR Lens

MWIR and LWIR Optics

• For wavelengths > 2.5 µm that glass would block

• Special & costly optics: germanium and silicon

• Further materials available for high transmittance

• No standard mounts

Filters for SWIR Wavelengths

• Filters are used to increase contrast

• They often correspond to the absorption spectra of specific substances.

Example: Water filter 1450 nm

without filter with filter

IR SWIR (InGaAs)

narrow bandpass (1450nm)

Visible light

• Filters are used to increase contrast

• They often correspond to the absorption spectra of specific substances.

black

dark

clear

Water color

How the Water Filter Works

Sensor Technology

Quantum vs. Thermal Detectors

• Quantum Detectors

• Sensitivity dependent on wavelength

• Require cooling to improve S/N ratio especially for wavelengths beyond 1µm

• High detection performance and fast response

• Thermal Detectors

• Detect IR energy as heat

• In general do not require cooling

• Have a slow response time and detection capability

1 2 3 4 5 6 7 8 9 10 11 12 13 14 [µm]

InGaAs

InSb

µ-Bolometer

QWIP

MCT

Si-based

CCD/CMOS

Quantum

Detectors

Thermal

Detectors

LWIR N I R

SWIR MWIR V I S

Spectral Sensitivity

for Typical IR Detector Types

Infrared Detector Selection

Min. Object Temperature (self-emissive)

Sensor Type Sensor wavelength [µm]

Operating Temperature

800 °C CCD/CMOS [Si] < 1 300 K (27 °C)

250 °C SWIR [InGaAs] < 1.7 300 K (27 °C)

0 °C MWIR [InSb] < 6 77 K (-196 °C)

-70 °C LWIR [µBolometer]

< 14 300 K (27 °C)

-150 °C LWIR [MCT] < 20 77 K (-196 °C)

Reference temps: White hot steel ~1200 °C Melting point of aluminum 660 °C Water boils at 100 °C Uncooled camera at 38 °C Human body at 37 °C, radiates at ~ 10 μm Water freezes at 0 °C

Cooling Methods

• Cryogenic Cooling

– dry ice or liquid nitrogen

– mechanical cooling using Stirling elements

• Thermoelectric Cooling (TEC) using Peltier elements

– Lower cost

– Solid state – no vibration

SWIR Sensor Technology

• Quantum detector

Working principle: Absorption of photons that elevate the material’s electrons to a higher energy level, so that they can be counted

• Hybrid array: IR detector, Si readout

Indium bumps on each pixel of array and readout IC

• Thermal detector

Working principle: Detection of electrical resistance changes in a thermally insulated absorber material (VOx, a-Si)

• Hybrid array: IR detector, Si readout

Spectral range: 8 ..14 µm i.e. for LWIR

µBolometer Sensor Technology

Comparing Camera Performance

• Noise Equivalent Temperature Difference [NETD]: A measure of detector sensitivity; influences precision of temperature measurement – Measured in °C or K

– 10 mK – 200 mK typical

• Is equal to temperature difference which would produce given noise

NETD

f-number

thermal time constant

temperature

Influencing physical variables:

Various Heat Sources Cause Drift

• Heat comes from: – Scene / object of interest

– Lens

– Camera housing

– Sensor (FPA)

For temperature measurement, corrections for the undesired heat effects are essential

Heat can´t be “blocked” like visible light

Optical lens

FPA

Image Processing

Closer Look at SWIR Sensor Image

• Non-uniformities

• Defect Pixels

• Incorrect flip-chip bonding

1. Original image of an uncooled SWIR sensor

2. With Gain-Offset Nonuniformity Correction (aka NUC)

3. With Error Pixel Correction

How an Image is Processed

@20ms Exposure

@100ms Exposure after NUC

@40ms Exposure @100ms Exposure

Influence of Exposure Time

1. Sensor Temp. +40°C

@100ms Exposure

2. Sensor Temp. -11°C

@100ms Exposure

3. @800ms Exposure

4. Including NUC 5. Including Defect

Pixel Correction

Effect of Sensor Temperature

Allied Vision Technologies GmbH Taschenweg 2a 07646 Stadtroda, Germany Tel.: +49 36428 / 677-0 Fax: +49 36428 / 677-24

info@alliedvisiontec.com www.alliedvisiontec.com

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