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

  1. 1. Infrared Imaging: Seeing the Invisible Part Two: Camera Technology
  2. 2. Structure of an Infrared Camera Optics & Filters Firmware Sensor Sensor Cooling incl. digitization (optional) Background Correction Gain/Offset Correction (NUC) Defect Pixel Correction • Feature Control Interface and • Image Correction I/O Control • Temperature Calibration Temp. Calibration via LUT Drift Compensation
  3. 3. Optics & Filters
  4. 4. Image with / without SWIR Lens SWIR optimized lens Non-optimized lens
  5. 5. 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
  6. 6. Filters for SWIR Wavelengths without filter with filter • Filters are used to increase contrast • They often correspond to the absorption spectra of specific substances. Example: Water filter 1450 nm
  7. 7. How the Water Filter Works Water color black narrow bandpass (1450nm) dark • Filters are used to increase contrast • They often correspond to the absorption spectra of specific substances. clear Visible light IR SWIR (InGaAs)
  8. 8. Sensor Technology
  9. 9. 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
  10. 10. Spectral Sensitivity for Typical IR Detector Types V N I I S R LWIR MWIR SWIR Quantum Detectors MCT QWIP InSb InGaAs Si-based CCD/CMOS Thermal Detectors µ-Bolometer 1 2 3 4 5 6 7 8 9 10 11 12 13 14 [µm]
  11. 11. 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
  12. 12. 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
  13. 13. 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
  14. 14. µBolometer Sensor Technology • 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
  15. 15. 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 Influencing physical variables: thermal time constant f-number temperature NETD
  16. 16. Various Heat Sources Cause Drift • Heat comes from: Scene / object of interest Lens Camera housing – FPA – – – Optical lens Sensor (FPA) Heat can´t be “blocked” like visible light  For temperature measurement, corrections for the undesired heat effects are essential  
  17. 17. Image Processing
  18. 18. Closer Look at SWIR Sensor Image • Nonuniformities • Defect Pixels • Incorrect flipchip bonding
  19. 19. How an Image is Processed 1. Original image of an uncooled SWIR sensor 2. With Gain-Offset Nonuniformity Correction (aka NUC) 3. With Error Pixel Correction
  20. 20. Influence of Exposure Time @20ms Exposure @100ms Exposure after NUC @40ms Exposure @100ms Exposure
  21. 21. Effect of Sensor Temperature 1. Sensor Temp. +40°C @100ms Exposure 2. Sensor Temp. -11°C @100ms Exposure 4. Including NUC 5. Including Defect Pixel Correction 3. @800ms Exposure
  22. 22. Allied Vision Technologies GmbH Taschenweg 2a 07646 Stadtroda, Germany Tel.: +49 36428 / 677-0 Fax: +49 36428 / 677-24 Follow us: