PCH-EM Algorithm for DSERN characterization

May 29, 2023 By Leave a Comment

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Hendrickson et al. have posted two new pre-prints on deep sub-electron read noise (DSERN) characterization. This new algorithm called PCH-EM is used to extract key performance parameters of sensors with sub-electron read noise through a custom implementation of the Expectation Maximization (EM) algorithm. It shows a dramatic improvement over the traditional Photon Transfer (PT) method in the sub-electron noise regime. The authors have some extensions and improvements of the method coming soon as well.

The first pre-print titled "Photon Counting Histogram Expectation Maximization Algorithm for Characterization of Deep Sub-Electron Read Noise Sensors" presents the theory behind their approach.

Abstract: We develop a novel algorithm for characterizing Deep Sub-Electron Read Noise (DSERN) image sensors. This algorithm is able to simultaneously compute maximum likelihood estimates of quanta exposure, conversion gain, bias, and read noise of DSERN pixels from a single sample of data with less uncertainty than the traditional photon transfer method. Methods for estimating the starting point of the algorithm are also provided to allow for automated analysis. Demonstration through Monte Carlo numerical experiments are carried out to show the effectiveness of the proposed technique. In support of the reproducible research effort, all of the simulation and analysis tools developed are available on the MathWorks file exchange.

Authors have released their code here: https://www.mathworks.com/matlabcentral/fileexchange/121343-one-sample-pch-em-algorithm


 

 

The second pre-print titled "Experimental Verification of PCH-EM Algorithm for Characterizing DSERN Image Sensors" presents an application of the PCH-EM algorithm to quanta image sensors.

Abstract: The Photon Counting Histogram Expectation Maximization (PCH-EM) algorithm has recently been reported as a candidate method for the characterization of Deep Sub-Electron Read Noise (DSERN) image sensors. This work describes a comprehensive demonstration of the PCH-EM algorithm applied to a DSERN capable quanta image sensor. The results show that PCH-EM is able to characterize DSERN pixels for a large span of quanta exposure and read noise values. The per-pixel characterization results of the sensor are combined with the proposed Photon Counting Distribution (PCD) model to demonstrate the ability of PCH-EM to predict the ensemble distribution of the device. The agreement between experimental observations and model predictions demonstrates both the applicability of the PCD model in the DSERN regime as well as the ability of the PCH-EM algorithm to accurately estimate the underlying model parameters.





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Gigajot article in Nature Scientific Reports

August 19, 2022 By Leave a Comment

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Jiaju Ma et al. of Gigajot Technology, Inc. have published a new article titled "Ultra‑high‑resolution quanta image sensor with reliable photon‑number‑resolving and high dynamic range capabilities" in Nature Scientific Reports.

Abstract:

Superior low‑light and high dynamic range (HDR) imaging performance with ultra‑high pixel resolution are widely sought after in the imaging world. The quanta image sensor (QIS) concept was proposed in 2005 as the next paradigm in solid‑state image sensors after charge coupled devices (CCD)and complementary metal oxide semiconductor (CMOS) active pixel sensors. This next‑generation image sensor would contain hundreds of millions to billions of small pixels with photon‑number‑resolving and HDR capabilities, providing superior imaging performance over CCD and conventional CMOS sensors. In this article, we present a 163 megapixel QIS that enables both reliable photon‑number‑resolving and high dynamic range imaging in a single device. This is the highest pixel resolution ever reported among low‑noise image sensors with photon‑number‑resolving capability. This QIS was fabricated with a standard, state‑of‑the‑art CMOS process with 2‑layer wafer stacking and backside illumination. Reliable photon‑number‑resolving is demonstrated with an average read noise of 0.35 e‑ rms at room temperature operation, enabling industry leading low‑light imaging performance. Additionally, a dynamic range of 95 dB is realized due to the extremely low noise floor and an extended full‑well capacity of 20k e‑. The design, operating principles, experimental results, and imaging performance of this QIS device are discussed.








Ma, J., Zhang, D., Robledo, D. et al. Ultra-high-resolution quanta image sensor with reliable photon-number-resolving and high dynamic range capabilities. Sci Rep 12, 13869 (2022).

This is an open access article: https://www.nature.com/articles/s41598-022-17952-z.epdf

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Review of Quanta Image Sensors for Ultralow-Light Imaging (IEEE TED June 2022)

June 6, 2022 By Leave a Comment

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[As mentioned in some recent comments on this blog, the latest (vol. 69 no. 6, June 2022) issue of IEEE Transactions on Electron Devices has many interesting papers related to image sensors. I will post summaries here in the coming days.]

In an invited paper in the June 2022 issue of IEEE TED, Jiaju Ma et al. write:

The quanta image sensor (QIS) is a photon counting image sensor that has been implemented using different electron devices, including impact ionization gain devices, such as the single-photon avalanche detectors (SPADs), and low-capacitance, high conversion-gain devices, such as modified CMOS image sensors (CIS) with deep sub-electron read noise and/or low noise readout signal chains. This article primarily focuses on CIS QIS, but recent progress of both types is addressed. Signal processing progress, such as denoising, critical to improving apparent signal-to-noise ratio, is also reviewed as an enabling co-innovation.

https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9768129









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Gigajot Announces the World’s Highest Resolution Photon Counting Sensor

April 12, 2022 By Leave a Comment

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PASADENA, Calif., April 4, 2022 /PRNewswire/ -- Gigajot Technology, inventors and developers of Quanta Image Sensors (QIS), today announced the expansion of its groundbreaking QIS product portfolio with the GJ04122 sensor and associated QIS41 camera. With market leading low read noise, the GJ04122 sensor is capable of photon counting and photon number resolving at room temperature. The QIS41 camera, built around the GJ04122 sensor, pairs well with standard 4/3-inch microscopy optics, bringing unparalleled resolution and low light performance to scientific and industrial imaging applications.


Gigajot GJ04122 Sensor


Gigajot QIS41 Camera


"We are excited about the discoveries that our latest QIS will enable in the life sciences community," said Gigajot's CEO, Dr. Saleh Masoodian, "Additionally, this QIS device further validates that Gigajot has the world's leading small pixel performance which will eventually be deployed to high volume consumer products that value high resolution, low light imaging performance and HDR."

The 41 Megapixel GJ04122 sensor, which was funded in part by the National Science Foundation SBIR Program, utilizes a 2.2-micron pixel and has a read noise of only 0.35 electrons, which is significantly lower than state-of-the-art pixels of similar size. The sensor is capable of photon counting and photon number resolving up to its top speed of 30 frames per second at full resolution. The high resolution and the extremely low read noise provide flexibility for binning and additional post-processing, while maintaining a read noise that is still lower than native lower resolution sensors. While pushing the limits of low light imaging, the GJ04122 sensor also offers an impressive single-exposure dynamic range of 95 dB by utilizing Gigajot's patented high dynamic range pixel.

The QIS41 is a fully featured scientific camera based on the GJ04122 sensor. The QIS41 camera has a SuperSpeed USB 3.0 interface and is capable of true photon counting at room temperature. For more information, or to schedule a virtual demonstration contact Gigajot Sales at www.gigajot.tech/order. The QIS41 camera can be pre-ordered now for Q4 2022 deliveries.

About Gigajot Technology, Inc.: Headquartered in Pasadena, CA, Gigajot is developing the next generation of image sensors. Gigajot's mission is to develop innovative Quanta Image Sensor (QIS) devices and advance this technology for the next generation of image sensors, offering high-speed and high-resolution single-photon detection to realize new, unprecedented image capture capabilities for professionals, and consumers. At Gigajot, every photon counts. For more information, visit www.gigajot.tech.

Press release: https://www.prnewswire.com/news-releases/gigajot-announces-the-worlds-highest-resolution-photon-counting-sensor-301516410.html

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Photonics Spectra article about Gigajot’s QIS Tech

March 24, 2022 By Leave a Comment

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The March 2022 edition of Photonics Spectra magazine has an interesting article titled "Photon-Counting CMOS Sensors: Extend Frontiers in Scientific Imaging" by Dakota Robledo, Ph.D., senior image sensor scientist at Gigajot Technology.

While CMOS imagers have evolved significantly since the 1960s, photon-counting sensitivity has still required the use of specialized sensors that often come with detrimental drawbacks. This changed recently with the emergence of new quanta image sensor (QIS) technology, which pushes CMOS imaging capabilities to their fundamental limit while also delivering high-resolution, high-speed, and low-power linear photon counting at room temperature. First proposed in 2005 by Eric Fossum, who pioneered the CMOS imaging sensor, the QIS paradigm envisioned a large array of specialized pixels, called jots, that are able to accurately detect single photons at a very fast frame rate . The technology’s unique combination of high resolution, high sensitivity, and high frame rate enables imaging capabilities that were previously impossible to achieve. The concept was also expanded further to include multibit QIS, wherein the jots can reliably enumerate more than a single photon. As a result, quanta image sensors can be used in higher light scenarios, versus other single-photon detectors, without saturating the pixels. The multibit QIS concept has already resulted in new sensor architectures using photon number resolution, with sufficient photon capacity for high-dynamic-range imaging, and the ability to achieve competitive frame rates.





The article uses "bit-error-rate" metric for assessing image sensor quality.


The photon-counting error rate of a detector is often quantified by the bit error rate. The broadening of signals associated with various photo charge numbers causes the peaks and valleys in the overall distribution to become less distinct, and eventually to be indistinguishable. The bit error rate measures the fraction of false positive and false negative photon counts compared to the total photon count in each signal bin. Figure 4 shows the predicted bit error rate of a detector as a function of the read noise, which demonstrates the rapid rate reduction that occurs for very low-noise sensors. 

 


The article ends with a qualitative comparison between three popular single-photon image sensor technologies.



Interestingly, SPADs are listed as "No Photon Number Resolution" and "Low Manufacturability". It may be worth referring to previous blog posts for different perspectives on this issue. [1] [2] [3]

Full article available here: https://www.photonicsspectra-digital.com/photonicsspectra/march_2022/MobilePagedReplica.action?pm=1&folio=50#pg50



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A Curious Observation about 1-bit Quanta Image Sensors Explained

March 15, 2022 By Leave a Comment

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Dr. Stanley Chan (Purdue University) has a preprint out titled "On the Insensitivity of Bit Density to Read Noise in One-bit Quanta Image Sensors" on arXiv. This paper presents a rigorous theoretical analysis of an intuitive but curious observation that was first made in the paper by E. Fossum titled "Analog read noise and quantizer threshold estimation from Quanta Image Sensor Bit Density."

Why is the quanta image sensor bit density insensitive to read noise at high enough exposure values?

The one-bit quanta image sensor is a photon-counting device that produces binary measurements where each bit represents the presence or absence of a photon. In the presence of read noise, the sensor quantizes the analog voltage into the binary bits using a threshold value q. The average number of ones in the bitstream is known as the bit-density and is often the sufficient statistics for signal estimation. An intriguing phenomenon is observed when the quanta exposure is at unity and the threshold is q=0.5. The bit-density demonstrates a complete insensitivity as long as the read noise level does not exceeds a certain limit. In other words, the bit density stays at a constant independent of the amount of read noise. This paper provides a mathematical explanation of the phenomenon by deriving conditions under which the phenomenon happens. It was found that the insensitivity holds when some forms of the symmetry of the underlying Poisson-Gaussian distribution holds.



The paper concludes:

The insensitivity of the bit density of a 1-bit quanta image sensor is analyzed. It was found that for a quanta exposure θ = 1 and an analog voltage threshold q = 0.5, the bit density D is nearly a constant whenever the read noise satisfies the condition σ ≤ 0.4419. The proof is derived by exploiting the symmetry of the Gaussian cumulative distribution function, and the symmetry of the Poisson probability mass function at the threshold k = 0.5. An approximation scheme is introduced to provide a simplified estimate where σ ≤ 1/√2π = 0.4. In general, the analysis shows that the insensitivity of the bit density is more of a (very) special case of the 1-bit quantized Poisson-Gaussian statistics. Insensitivity can be observed when the quanta exposure θ is an integer and the threshold is q = θ−0.5. As soon as the pair (θ, q) deviates from this configuration, the insensitivity will no longer appear.

Complete article can be downloaded here: https://arxiv.org/pdf/2203.06086

An early-access version of Eric's paper is available here: https://ieeexplore.ieee.org/document/9729893

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