How an EMCCD works
An EMCCD (electron-multiplying CCD) camera works by first transforming incident photons into electrons via the photoelectric effect that takes place in the EMCCD’s silicon body within the camera cryostat. This semiconducting surface is meticulously organized in an array of pixels, a matrix of potential wells in which electrons can accumulate during exposure. Following the collection of these negative charges during exposure time, the application of electrical signals from the CCCP to the potential wells forces the electrons to quickly travel row by row from the imaging region to the storage region so that the acquired image can be processed while a new image is formed during the subsequent exposure time. Once masked from light in the storage region, the electrons in the bottommost row of the detector travel pixel by pixel into the electron multiplication register. At this stage, the accumulated photoelectrons are amplified via impact ionization, a type of avalanche effect that allows the generation of several thousands of electrons per photoelectron. Finally, the charges reach an amplifier where they are converted into an electric potential that is subsequently digitized to form a high quality digital image.
What parameters influence EMCCD sensitivity
Compared to other low flux imaging technologies, EMCCDs have the benefits of high quantum efficiency (QE) and low dark current in the same manner as traditional CCDs, as well as negligible readout noise similar to ICCDs to provide the best sensitivity. However, the EMCCD is subject to a different source of noise commonly referred to as clock-induced charge (CIC), which can contaminate generated images up to 200 times more than dark current in photon counting applications.
Listed below are the primary parameters that influence the sensitivity of low light imaging systems as well as the means by which Nüvü Camēras technology is capable of efficiently and elegantly overcoming such obstacles.
A first type of noise that will interfere with proper signal acquisition is Thermal Noise (also referred to as dark current). Ideally, the only electrons generated and detected by the system are those produced by the photoelectric effect. However, the mere thermal agitation of the silicon semiconductor is sufficient to occasionally eject an electron, thereby allowing it to accumulate in a potential well. In this manner, even if the camera shutter is closed, the wells may slowly gather charges, thus giving the false impression that the CCD is being exposed to a faint light source. To counter Thermal Noise, a widespread technique for scientific CCDs is to cool it down to temperatures well below freezing in the vicinity of -85°C. In doing so, high quality images can be obtained for applications where light is readily available. However, this is rarely the case in a variety of fields including astronomy and biomedical research, where light sources are extremely dim. Consequently, other noise sources must be taken into consideration and be eliminated.
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Neglecting the effects of Thermal Noise, the amount of accumulated electrons is proportional to the quantity of received light. Consequently, in low lighting conditions, the CCD must be exposed for longer periods of time such that an appreciable quantity of electrons can be captured and detected. In certain cases, the observed phenomenon may occur over a timescale shorter than the necessary exposure time to obtain a good quality image. In addition, another noise source –- the readout noise -– is introduced during the conversion process from charge to electric potential, but is typically insignificant, as it is in the order of 2 to 10 electrons. Nevertheless, when there are very few electrons in the potential wells throughout the entire acquisition period, the readout noise becomes a highly limiting factor in obtaining a high quality image. To increase CCD sensitivity, EMCCDs offer a charge amplification stage induced by a high voltage electrical signal prior to the charge-potential conversion. This amplification can generate a gain in the order of 1000 to 2000 electrons per photoelectron which renders the readout noise negligible in contrast. Thus, an EMCCD can be used to observe scenes under ultra low lighting, since the impact of every incident photon is increased over a thousandfold. However, the stochastic nature of electron multiplication adds another form of noise to the system: the excess noise factor.
Excess Noise Factor
The electron multiplication process employed to amplify photoelectrons is a stochastic process. In other words, this implies that only the mean value of the multiplicative gain can be determined, whereas the gain applied to a specific pixel for a particular incident photon cannot be known due to the statistical nature of the physical processes involved. The graphs below demonstrate this uncertainty. In theory, the mean value represented by the full line can be predicted with good accuracy but individual values are in fact spawned across a range of values varying according to the time and the place of the specific pixel measured. In turn, this uncertainty induces an excess noise factor (ENF) of √2 which has the same effect on the SNR as halving the system’s quantum efficiency. To counter this, the photon counting mode imposes the application of a threshold to the pixels’ values. In this manner, the individual pixel gains are not necessary to determine the number of incident photons; rather, the output is rendered binary. If the number of photoelectrons accumulated within a given potential well is greater than the specified threshold, the system will consider that one photon has been detected on that pixel. Thus, the use of the photon counting mode eliminates the ENF and allows high sensitivity acquisition without losing image quality. Nevertheless, another noise source now appears in low lighting conditions during high speed acquisition that greatly limits EMCCD performance –- and it is precisely this noise source that Nüvü Camēras’ products are able to efficiently overcome.
Horizontal dashed lines represent ±1% of mean value.
The high voltages and high frequencies implied in acquisitions using an EMCCD are the sources of clock-induced charges (CIC). These electrons are generated during the transition of the electrical signals from one well to another used to read the EMCCD. Fortunately, Nüvü Camēras’ innovative patented CCCP technology generates signals that are more precise and more versatile than those produced by other controllers, allowing it to drastically decrease CIC.
Charge Transfer Efficiency
Finally, a last source of noise can be observed during high speed charge transfer. In fact, at high readout speeds, the transfer of electrons from one potential well to the next may be incomplete, leaving certain charges behind during this process. Consequently, the leftover electrons artificially increase the brightness of certain pixels, thereby diminishing the overall quality of the image with the addition of correlated bright spots. Nonetheless, on top of decreasing CICs, the CCCP considerably increases the charge transfer efficiency (CTE) of the system in order to obtain images of highly superior quality.
The inverted mode of operation (IMO) of a CCD consists in applying a voltage across the CCD detector in order to generate a population of “holes” within the silicon substrate, allowing them to recombine with the electrons resulting from dark current prior to readout. As a result, IMO significantly contributes to decreasing the dark current. However, the trade-off is that the moving holes generate more CIC during the vertical transfer of the electrons towards the readout register. That’s why on one hand, the IMO appears appropriate for long exposure times while on the other, NIMO is ideal for short periods of acquisition when the dark current has little time to accumulate. Of course, this is all true except in the case where the high voltage signals delivered by your EMCCD controller are sufficiently fine-tuneable to limit the excess CIC resulting from IMO. In fact, Nüvü Camēras’ patented CCCP — operating exclusively in IMO — is a state of the art EMCCD camera controller capable of generating such precise signals. The CCCP therefore allows a much greater SNR than any other controller, whether operated in IMO or NIMO, no matter the integration time.
In addition, it is essential to note that IMO and NIMO are mutually exclusive modes of operation and it is thus impossible to obtain the best of both worlds! As such, it is essential to know the modes of operation used in the characterization of EMCCD cameras in data sheets. In the case of Nüvü Camēras products, all data are obtained in IMO. Certain other EMCCD manufacturers may provide CIC data in NIMO, while dark current data is obtained in IMO, thus giving the false impression of low total background noise. However, given that both modes are mutually exclusive, the resulting background signal will inevitably be greater than expected when such manufacturer’s cameras are put to use.
photon counting Mode
When expecting an average of 1 photon per pixel per exposure or less, the key is to implement of a binary mode of acquisition including an algorithm that analyzes the image on a pixel-by-pixel basis. A mathematically relevant threshold allows to statistically determine whether a given pixel did in fact originally contain a genuine photoelectron or not. The generated images are binary due to the thresholding involved. The stochastic nature of the EM process is no longer relevant to the SNR calculations and the ENF is thus completely suppressed. By summing several frames together, it is possible to recover the dynamic range which is decreased by the nature of this mode of acquisition.
photon counting Performance
In extremely low light applications, image acquisition using photon counting (PC) processing has a significant advantage over traditional Linear processing: the elimination of the excess noise factor (ENF). However, in order to provide its theoretical plus-value, an EMCCD camera using PC must also be capable of high frame rates, produce minimal clock-induced charges (CIC) and use an extremely high EM gain for optimal thresholding – all in order to detect the highest proportion of incoming photons with the least noise. When properly combined, these elements yield the highest SNR in extreme low light imaging as demonstrated in the comparison below.
Using a standard USAF 1951 target, a PC image is compared to an image acquired in Linear mode, also sometimes referred to as Analog Mode (AM). The first two images were acquired using Nüvü Camēras’ EM N2 512, while the third image was a simulation generated based on the best available specifications of other EMCCD cameras (without specifications as to IMO or NIMO operation). The PC image was produced by accumulating and superposing 10 binary frames, each with an exposure time of 50 ms at a 10 MHz pixel rate and EM gain of 5000. The Linear (AM) image was a single acquisition with 500 ms of exposure, again with a 10 MHz pixel rate and EM gain of 5000.
Low noise performance
Nüvü Camēras’ cutting edge imaging sensitivity is based on its CCD controller for counting photons (CCCP) that renders EMCCD devices faster and more precise for low lighting applications such as astronomy and biomedical research. The great degree of precision of the electrical signals generated by the CCCP significantly decreases clock-induced charge (CIC) levels (the main source of noise in EMCCD cameras) while maintaining a rapid readout rate.
The obstacles in acquiring high quality images in low light conditions reside principally in sources of noise that are not apparent in standard operating conditions, but rather that become predominant in the nearly total absence of light. Furthermore, in conditions of such low lighting that the counting of individual photons is required, high frame rates are primordial in order to obtain accurate and representative images of observed phenomena. These two major obstacles are precisely those that Nüvü Camēras inventively overcame with the design of the innovative CCCP camera controller. As such, Nüvü Camēras’ imaging devices modernize the fields of astronomy and biomedical research by not only providing a better understanding of the physical principles governing the behavior of stars and galaxies, but also by being able to detect even the faintest luminous signals emitted by medical diagnostic tools such as fluorescent markers or laser light scattered by in vivo tissues. In turn, these signals may be able to indicate early signs of diseases such as macular degeneration or early stage cancer.