Bjorn F. Andresen

Time-encoded multiplexed imaging (Conference Presentation)

We describe a technique for multiplexed imaging that is based on the concept of mapping scene features to unique temporal codes, and using smart digital pixels to efficiently decode at the focal-plane. We use this technique to demonstrate multiplexed multispectral imaging using actively encoded LEDs, and multiplexed hyperspectral imaging using a digital micromiror spatial light modulator. Both experiments utilize a computational imaging array comprised of a 32x32 array of digital pixels with the capability of acquiring eight concurrent measurements that can be modulated with a time-varying duo-binary signal (+1,-1,0) at MHz rates. This results in eight decoded images per frame at a maximum frame rate of 1600 frames per second. The total frame rate of the imaging system depends on the number of encoded features and the number of decoding channels within the digital pixel. We explore these trades as well as discuss limitations and areas for future improvement.

Visible response of λ c =2.5´m HgCdTe HDVIP detectors

Cu-doped HDVIP detectors with different cut-off wavelengths are routinely manufactured. The DRS HDVIP detector technology is a front-side-illuminated detector technology. There is no substrate to absorb the visible photons as in backside-illuminated detectors and these detectors should be well suited to respond to visible light. However, HDVIP detectors are passivated using CdTe that absorbs the visible light photons. CdTe strongly absorbs photons of wavelength shorter than about 800 nm. Detectors with varying thickness of CdTe passivation layers were fabricated to investigate the visible response of the 2.5-μm-cutoff detectors. A model was developed to predict the quantum efficiency of the detectors in the near infrared and visible wavelength regions as a function of CdTe thickness. Individual photodiodes (λc = 2.5 μm) in test bars were examined. Measurements of the quantum efficiency as a function of wavelength region will be presented and compared to the model predictions.