![]() ![]() But the real cost of dark current is not the counts but in dark current noise. Why can’t this increased background count simply be subtracted from the image post-acquisition? In reality, performing this subtraction is essential in imaging with InGaAs due to the high dark current of this technology. The dark counts (in units of electrons) in a pixel is given by :ĭark Signal (e-) = Dark Current (e- /pixel/second) X Exposure Time (seconds) ![]() The net effect is a gradual increase in the ‘dark counts’, the measured signal with no incident photons, for increasing exposure time. This thermal release of electrons occurs randomly, though typically with a well-defined average rate that can differ across the sensor. There is no way within the pixel to differentiate between photoelectrons, and these ‘noise’ electrons. Some electrons within the sensor substrate and the components of the pixel can free themselves through thermal motion and enter the pixel well. However, incident photons are not the only source of electrons within the pixel. The number of detected photoelectrons in each pixel at the end of the exposure makes up our image. Camera sensors detect light through capturing incident photons and releasing photoelectrons, through the photoelectric effect. ![]() Often the primary noise source for low light imaging in InGaAs is dark current noise. The ultimate determining factor of sensitivity is the signal to noise ratio that the camera achieves, and as is shown in this document, the NIRvana range of cameras provide superior signal-to-noise ratio at practically every imaging condition in scientific imaging. To read more about scene noise and how minimizing this enables better scientific imaging, see our technical note on Cold Shielding. Through low dark current noise, high signal collection efficiency, low read noise and reduction in the unwanted background ‘scene noise’ captured by the camera, high-quality scientific InGaAs SWIR cameras can deliver better images with shorter exposure times. But despite large dark current noise contributions, long exposure times of seconds to multiple minutes are frequently required in SWIR imaging to achieve an adequate signal-to-noise ratio. ![]() Dark current values can range from 10e-/p/s for the world-leading NIRvana LN, up to tens of thousands of e-/p/s for uncooled cameras, both orders of magnitude higher than those expected for silicon cameras. Often, the biggest barrier to achieving sufficiently high signal-to-noise-ratio in scientific imaging is the exposure-time-dependent dark current noise, which is dependent on the temperature of the sensor. For all InGaAs sensors, achieving the high image quality and quantifiability required for scientific applications requires far more engineering time and investment. If only silicon sensors existed, SWIR imaging would not be possible – but compared to silicon-based sensors, the uniformity, read noise and dark current values inherent to InGaAs technology are considerably higher. Instead of the 85% QE from 900 nm to 1500 nm. This is made possible by InGaAs sensors – sensors where the imaging substrate is composed of a mix of indium, gallium and arsenide instead of silicon. Infrared imaging in the Short-Wave InfraRed (SWIR) region from 1000-1700 nm wavelength, also known as NIR-II, opens doors to powerful and versatile imaging techniques and applications. ![]()
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