Soitec Presents InP Integration onto Si Wafer for SWIR Sensing

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Soitec Capital Market Day presentation shows the company's innovations in wafers for imaging:

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EU Autovision Collaboration Targets Graphene SWIR Sensor for Automotive Applications

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The AUTOVISION Spearhead Project aims to develop a graphene-based SWIR image sensor, and integrate it in a suitable camera system for self-driving cars.

Led by Qurv in Barcelona, AUTOVISION counts on the collaboration of industrial partners such Aixtron in the UK and Veoneer in Sweden, to help make safe deployment of autonomous vehicles possible.

The AUTOVISION project, over the course of three years, will produce CMOS graphene quantum dot image sensors in prototype sensor systems, ready for uptake in the automotive sector. Across the duration of the project, the developing image sensor is set to take huge leaps in sensitivity, operation speed and pixel size.


Once we talk about graphene and its applications, there is Vimeo lecture of Konstandtin Novoselvov, a co-recipient of Nobel Prize for graphene invention:


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Hamamatsu "Lightsheet Readout"

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Hamamatsu presents Lightsheet Readout Mode for microscopes that is said to improve image quality:

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2021 in Review

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Here is my list of the most significant achievements in image sensor industry this year:

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In 2021, Smartsens Released 36 New Sensors to Mass Production, Completed 31 Tapeouts

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Tencent, Sohu: Smartsens reports that in 2021 it has released 36 new products to mass production, and completed 31 tapeouts of future products including 4K and 8K image sensors for security and surveillance applications.

In a separate announcement, Smartsens presents its new automotive sensors: VGA SC031AP and 1MP SC101AP, both integrated with ISP and Tx output port:

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Panasonic Analyses SPAD Quenching

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IEEE TED publishes Panasonic paper "Nonlinear Carrier Dynamics in a Single Photon Avalanche Diode: Stability, Bifurcation, and Quenching Condition" by Akito Inoue and Yutaka Hirose.

"Nonlinear carrier dynamics during quenching of a single photon avalanche diode (SPAD) are investigated. A Lienard type differential equation is derived from carrier continuity equations and it is solved analytically and numerically. Universal characteristics of the quenching carrier dynamics, i.e., stability, bifurcation, and quenching conditions, are analyzed on a trace-determinant plane of the Jacobian matrix and on a phase plane as functions of the quenching resistance (QR). With a finite QR or a resistive quenching (RQ), the breakdown voltage is found to be an attractor leading to a nonquenched final state. In order to produce a successful quenching, i.e., a status identified as an unstable fixed point (FP) with a zero-carrier state, two conditions are found to be necessary: 1) bias voltage dropping below breakdown voltage to ensure carrier decrease and 2) carrier extinction (CE) in this carrier decreasing period. The two conditions together lead to a threshold of QR. On the other hand, a capacitive quenching (CQ) appearing as a special case of RQ with an infinite resistance is found to show a completely different bifurcation character. CQ is derived to be equivalent to a logistic equation giving a transcritical bifurcation at the breakdown voltage and a final state identified as a stable FP with natural CE. Finally, two time constants both governed by an excess voltage are derived. In particular, one of them, a lifetime of impact ionizations, is found to be equivalent to the “avalanche frequency” of an impact ionization avalanche transit-time diode (IMPATT)."

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Stratio Combines its SWIR Sensor with AI Algorithms to Detect Fakes

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BusinessWireStratio will work with South Korea’s National IT Industry Promotion Agency (NIPA) to create a first-of-its kind app that detects design infringements. The app instantly matches photos of suspected items to similar designs from an IP database to obtain a similarity score. This is possible through a backend which utilizes several of Stratio's imaging technologies, including algorithms for object detection, image retrieval, and report generation.

"Using visible imaging technology with the help of AI is an important milestone in our technology roadmap,” explains James Lee, Co-founder and CEO of Stratio, Inc. “In terms of what's next for Stratio, Inc., we plan to merge this AI capability with our upcoming shortwave infrared (SWIR) camera BeyonSense to visualize the invisible, and open up a new world of possibilities using our proprietary SWIR image sensor.

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CIS Companies Among Largest R&D Spenders in China

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JW Insights publishes a list of top R&D spenders among semiconductor companies in China. Image sensor companies Will Semi (Omnivision) and Goodix take 3rd and 5th places respectively:


Goodix also pays one of the highest average salaries in China, according to another JW Insights report. Goodix average half-year salary is $45K in the first half of this year. This means that its average annual salary is $90K:


According to yet another JW Insights report, Will Semi is one of the most valuable companies among the mobile supply chain players in China:


JW Insights also ranks Will Semi the second in size among semiconductor companies in China:

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More About Canon 3.2MP SPAD Sensor

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Canon publishes a press release about its SPAD sensor with 6.39 μm pixels presented at IEDM 2021:

"Canon Inc. announced today that the company, thanks to a proprietary pixel architecture that efficiently captures and greatly multiplies light, has successfully developed an ultra-small 13.2 mm x 9.9 mm SPAD sensor capable of capturing the world's highest1 resolution of 3.2-megapixel images—a higher resolution than Full HD (approximately 2.07 megapixels), even in low-light environments. Manufacture of the new sensor will commence in the second half of 2022.

The newly developed SPAD sensor employs a proprietary pixel architecture that reflects photons inside the pixel in order to effectively detect photons across the entire range of the effective pixels. Under equivalent light, this SPAD sensor can capture the same images as a conventional CMOS sensor while requiring only 1/10 of imaging area. This makes possible an ultra-small design that can be installed even in small devices and greatly increases sensitivity, including for light on the near-infrared spectrum, and realizes video capture with 3.2 megapixels under low-light conditions of 0.002 lux—darker than a starless night sky. By equipping cameras designed for low-light and monitoring applications with this new SPAD sensor, even video footage of low-light environments can be viewed as if it were recorded in bright areas, enabling identification of subject movement as though viewing with the naked eye in well-lit environments

Beginning in the second half of 2022, Canon will commence manufacturing of SPAD sensors for use in the company's security-oriented network camera products. With the inclusion of this innovative sensor, Canon's products will gain a competitive edge and contribute to the realization of a more safe and secure society.

In addition, the SPAD sensor is capable of extremely high information processing speeds on the level of 100 ps (picoseconds, one-trillionth of a second), enabling it to capture objects moving at high speeds including photons. With a resolution that surpasses Full HD and high sensitivity that enables capture of faint light, the sensor's unique rapid response functionality can be utilized in a wide range of applications including self-driving vehicles, medical treatment, diagnostic imaging devices and scientific precision measuring instruments. Canon will proactively expand its sales network in order to encourage further innovation and development of society."

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Huawei Unveils ISP with AI-based Low-Light Imaging Enhancement

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ITHome, GizomoChina, Huaweiupdate: Huawei semiconductor division HiSilicon presents its Yueying ISP at China International Social Public Safety Expo (China Security Expo for short).

"For the first time, the HiSilicon exhibition area fully revealed the five key capabilities of Yueying, breaking through the ceiling of traditional technology, enabling smarter and clearer picture quality in all scenes.

For the first time, HiSilicon moved the Dark Light Image Laboratory into the AMB Pavilion, allowing the public to experience the shocking effects of the latest black technology in an immersive manner. In the darkroom experience zone where “five fingers can't be seen”, one of Yueying’s key capabilities, super-sensitivity noise reduction, uses neural network deep learning to achieve intelligent noise reduction in low-light scenes, leading the industry in image quality and clarity. It also uses multi-spectral fusion technology to effectively fuse the visible light and infrared spectra, so that low-light images achieve a balance of color and detail, and reshape the colorful visual world."

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Huawei Unveils ISP with AI-based Low-Light Imaging Enhancement

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ITHome, GizomoChina, Huaweiupdate: Huawei semiconductor division HiSilicon presents its Yueying ISP at China International Social Public Safety Expo (China Security Expo for short).

"For the first time, the HiSilicon exhibition area fully revealed the five key capabilities of Yueying, breaking through the ceiling of traditional technology, enabling smarter and clearer picture quality in all scenes.

For the first time, HiSilicon moved the Dark Light Image Laboratory into the AMB Pavilion, allowing the public to experience the shocking effects of the latest black technology in an immersive manner. In the darkroom experience zone where “five fingers can't be seen”, one of Yueying’s key capabilities, super-sensitivity noise reduction, uses neural network deep learning to achieve intelligent noise reduction in low-light scenes, leading the industry in image quality and clarity. It also uses multi-spectral fusion technology to effectively fuse the visible light and infrared spectra, so that low-light images achieve a balance of color and detail, and reshape the colorful visual world."

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Omnivision Milestones

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Omnivision publishes a series of milestone videos summarizing the company's progress over the years:

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Mobile Camera Module Prices in China in December 2021

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SigmaIntell publishes its report on camera module prices in China and its forecast for Q1 2022:


IThome quotes SigmaIntell (Chinese name Qunzhi Consulting):

"According to the latest survey data of Qunzhi Consulting in December, in terms of low-pixel products, 2M pixel products are affected by the strategic reduction in capacity supply. It is expected that prices in the first quarter will show a flat trend. 8M pixel products, affected by the previous price increase factors, the terminal demand will continue to be sluggish in the first quarter. Qunzhi Consulting predicts that the price will show a 3-5% decline in the first quarter .

In terms of high-pixel products, for 64M pixel products, upstream head chip vendors continue to increase their production capacity for high-pixel products, and the industry's high-pixel component inventory continues to increase. Inventory clearing has become a priority strategy for chip vendors in the current period, Qunzhi Consulting predicts , The price will show a decline of about 5% in the first quarter.

The trend of multiple cameras on smart phones will continue in the future. However, due to the diminishing marginal effect of the increase in the number of cameras on the improvement of photo effects, and the increase in the cost of mobile phones brought about by 5G, mobile phone manufacturers have slowed down the upgrade of cameras."

Omdia too publishes its analysis of smartphone cameras number and resolution trends:

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“NIKKOR – The Thousand and One Nights (Tale 80) has been released”

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Howard Rhodes Lifetime Achievement Memorial

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Omnivision opens Howard Rhodes Lifetime Achievement Memorial Wall in its visitor center in Santa Clara, CA:

"As our former CTO & pioneer in CMOS sensor imaging industry, Howard created more than 200 issued US patent families and was one of the founders of OmniVision technology breakthroughs. This achievement wall not only honors Howard's contributions but also inspires #FutureInSight employees to innovate and achieve more accomplishments.

Furthermore, we have created “Howard Rhodes Award“ to honor our most outstanding engineer each year. Congratulations to Keiji Mabuchi who is the winner this year and Special thanks to Rhodes' Family who kindly shared Howard's plaque patents."

Keiji Mabuchi has 123 US issued patent families (274 granted US patents), not to talk about pending applications.

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A3 on Recent Image Sensor Innovations

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Association for Advancing Automation (A3) publishes its list of "Image Sensor Innovations that Push Machine Vision Forward."

  • ToF sensors:
    • Sony DepthSense BSI family
    • Teledyne e2v Hydra3D ToF CMOS
    • Teledyne e2v Flash series of image sensors for 3D laser triangulation
  • Prophesee event-based sensors
  • Sony IMX487 UV CMOS sensor
  • Sony SenSWIR sensors
  • SWIR Vision Systems CQD sensors
  • Emberion graphene SWIR sensor
  • Gpixel GMAX32103 CMOS sensor achieving 103.7MP resolution at 24fps frame rate

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ST Promises SWIR Quantum Dot Pixel Future

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ST publishes an article about its recent IEDM paper "1.62µm Global Shutter Quantum Dot Image Sensor Optimized for Near and Shortwave Infrared" by Johnathan Steckel:

"Quantum dots are tiny (between 2 nm to 20 nm usually) semiconductor crystals. One of their unique properties is that their optical and electrical properties change with their size. In an image sensor, using quantum dots of various sizes makes it possible to capture different wavelengths of light beyond silicon’s absorption limitations. In ST’s IEDM 2021 paper, researchers tuned quantum dots to capture 940 nm and 1400 nm light, the latter rivaling InGaAs sensors. However, InGaAs imaging devices are challenging and costly to make. Using a conventional 300 mm silicon wafer process in existing fabs, ST can produce the quantum dot sensor for shortwave infrared at a fraction of the cost.


Images taken with our 940nm NIR QF sensor (top left) and with our 1400nm SWIR QF sensor (bottom left). Corresponding images taken using a visible smartphone camera (right). QF NIR image shows dramatically better contrast between black electrical wires hidden in the dark green leaves and tree trunks and branches hidden in front of the dark wood fence whereas the SWIR QF image shows how effective it is to use SWIR imaging to see through a Silicon wafer.

Quantum dots are not new, and scientists were already studying their properties in the early 1980s. However, it took years to colloidally synthesize crystals that could absorb infrared light and to create thin-film devices and fabrication processes that would yield the performance and stability necessary for real-world applications. More specifically, ST developed a manufacturing process that would not exceed 150ºC while also creating lithographic methodologies that would preserve the quantum dot’s integrity.


The IEDM 2021 paper explains in detail how ST created this image sensor technology on 300 mm wafers and describes the performance and reliability achieved to date. We plan to provide samples and evaluation kits to potential customers in 2022 and move to mass production in the coming years. Among the potential applications, mobile devices could use the new sensors to improve facial or object detection. Ultimately, a low-cost high-volume SWIR image sensor accessible to all consumers will open the door to new use-cases and applications."

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Metasurface Photodetectors Review

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MDPI publishes a review paper "Metasurface Photodetectors" by Jinzhao Li, Junyu Li, Shudao Zhou, and Fei Yi from Huazhong University of Science and Technology, National University of Defense Technology, and Raytron (China).

"Typical photodetectors only convert the intensity of light electrical output signals, leaving other electromagnetic parameters, such as the frequencies, phases, and polarization states unresolved. Metasurfaces are arrays of subwavelength structures that can manipulate the amplitude, phase, frequency, and polarization state of light. When combined with photodetectors, metasurfaces can enhance the light-matter interaction at the pixel level and also enable the detector pixels to resolve more electromagnetic parameters. In this paper, we review recent research efforts in merging metasurfaces with photodetectors towards improved detection performances and advanced detection schemes. The impacts of merging metasurfaces with photodetectors, on the architecture of optical systems, and potential applications are also discussed."

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Gpixel Announces 9MP 1.1” NIR-enhanced Sensor for Intelligent Traffic Systems

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Gpixel announces GMAX3809 extending the GMAX family into ITS applications next to its traditional industrial inspection segment. Gpixel optimized the GMAX product architecture with dedicated ITS features such as enhanced NIR response, pixel size of 3.8 μm, LED flicker mitigation and multiple region HDR modes. GMAX3809 is first in a series of GMAX products with optimized product features for ITS applications.

GMAX3809 fits 4096(H) x 2160(V) (9 MP) resolution into a 1.1” format with low noise, charge domain Global Shutter pixels running at 65 fps at 12-bit ADC resolution. GMAX3809’s 3.8 μm pixel achieves a FWC of 11.5 Ke- and noise of 3.6 e- which delivers more than 70 dB linear DR. The peak QE is 60%, a Parasitic Light Sensitivity is -92 dB, and angular response at > 15° is 80%.

GMAX3809 comes standard in a NIR-enhanced version using Gpixel’s Red Fox technology, offering the ultimate balance between NIR sensitivity and MTF. GMAX3809 achieves a QE of more than 30% at 850 nm and 14% at 940 nm.

GMAX3809 delivers 65 fps with 8 pairs of sub-LVDS channels each running at 960 Mbps resulting in a maximum data rate of 7.68 Gbps. On-chip functions, such as on-chip color offset calibration, channel multiplexing, multiple region HDR and LED flicker are available and programmable through SPI or I2C interface.

GMAX3809 is housed in a 163-pin ceramic LGA package with outer dimensions of 27.1 mm x 17.9 mm. The sensor assembly includes a double side AR coated cover glass lid.

GMAX3809 engineering samples can be ordered today for delivery in January, 2022.

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BYD QVGA Sensor Won "China Chip" Excellent Market Performance Award

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Sina Technology: BYD Semiconductor's 1/15-inch 80,000-pixel CMOS sensor BF30A2 won the 2021 "China Chip" product award for outstanding market performance in the field of home appliances.

The sensor has 2.5um 4T pixel and a maximum frame rate of 15fps. Its embedded ISP controls WB, AE, black level, filters out noise and false colors, removes dead pixels and dead pixel clusters, and  a skin color detection for more realistic skin color processing.

Since its launch in April 2020, BF30A2 has taken the lead in sales volume and applied for nearly 60 patents. It's said to have a market share of 85% in the wearable market.

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BYD QVGA Sensor Won "China Chip" Excellent Market Performance Award

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Sina Technology: BYD Semiconductor's 1/15-inch 80,000-pixel CMOS sensor BF30A2 won the 2021 "China Chip" product award for outstanding market performance in the field of home appliances.

The sensor has 2.5um 4T pixel and a maximum frame rate of 30fps. Its embedded ISP controls WB, AE, black level, filters out noise and false colors, removes dead pixels and dead pixel clusters, and  a skin color detection for more realistic skin color processing.

Since its launch in April 2020, BF30A2 has taken the lead in sales volume and applied for nearly 60 patents. It's said to have a market share of 85% in the wearable market.

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Image Sensors at 2022 Photonics Spectra Conference

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Photonics Spectra magazine holds is 2022 conference on January 10-13. Registration is free and available here. There are several image sensor presentations at this virtual event:
  • KEYNOTE: Quanta Image Sensors: Every Photon Counts, Even in a Smartphone
    Eric Fossum from Dartmouth College talks about the quantum image sensor concept and how it has been implemented in CMOS image sensors and SPADs and what the major differences are between culminating results.
  • Emerging Short-Wavelength Infrared Sensors
    Matthew Dyson from IDTechEx Ltd. examines the motivation and applications for SWIR image sensing, and assesses the opportunities, challenges, and adoption roadmap for emerging technical approaches.
  • LEDs: Expanding Capabilities for Live Cell Imaging
    Isabel Goodhand from CoolLED explains how innovations such as multi-wavelength switching and TTL triggering enable faster imaging, and how multi-band filters can balance speed and contrast requirements.
  • Advanced Detector Solutions Enabling Quantum Optics Research
    Colin Coates from Andor Technology presents high-performance detector solutions that are central to fundamental research on entangled photon systems and ultracold quantum gases.
  • How Pixel Size and MTF Affect Modern Microscopy and See the Invisible with Microscopes
    Gerhard Holst from Excelitas PCO GmbH discusses the role of camera pixel size and MTF in the design and application of modern microscopes.
  • Enabling Rapid Application Development and Deployment of Hyperspectral Imaging in a Production Environment
    William Rock from Headwall Photonics Inc. presents on the utility of hyperspectral imaging in a production environment using examples in food processing and demonstrates the expedited development cycle using novel hardware and software.
  • High-Throughput Hyperspectral Imaging without Image Degradation
    Rand Swanson from Resonon Inc. examines the problem of image degradation with hyperspectral imagers and explores approaches to enhance the signal.
  • New Photon-Counting Detectors Expand Frontiers in Scientific Imaging
    Jiaju Ma from Gigajot Technology Inc. explains the fundamentals of photon-counting image sensors, or quanta image sensors, beginning with the background knowledge necessary to effectively apply these devices.
  • Dynamic Photodiodes: Unique Light-Sensing Technology with Tunable Sensitivity
    Serguei Okhonin, ActLight SA. Tunable sensitivity sets dynamic photodiode apart from all existing photodiodes, including SPADs. The AI in dynamic photodiode technology is able to dynamically adjust sensitivity at the pixel level to adapt to changing light conditions and keep the high precision of depth measurements. This presentation elaborates on the concept and design of these emerging photodiodes and how they are set to impact today’s sensing applications.
  • Current and Future Detector Designs for Flash Lidar
    Jennifer Ruskowski, Fraunhofer IMS. The roadmap for creating lidar sensors for autonomous cars and robots is moving into a new era. Becoming ever more important are technologies such as sensor fusion and embedded AI, which are poised to enhance the performance, efficiency, and acceptance of lidar sensors. Additionally, on a hardware level, lidar components such as laser sources and detectors are becoming increasingly powerful. Jennifer Ruskowski gives a brief overview of the Fraunhofer IMS’s lidar development activities, from light detector to system design to sensor fusion and embedded AI solutions.
  • FMCW and TOF Flash Automotive Lidar: Challenges and Prospects
    Slawomir Piatek, New Jersey Institute of Technology & Hamamatsu Corp. A vision of self-driving cars propels research and development for automotive lidar, vital hardware providing distance and velocity information about car surroundings. Among several lidar concepts—with some already adopted and heading toward production for automotive advanced driver-assistance systems (ADAS) and industrial markets—two newer designs have emerged with the highest potential in the future: frequency-modulated continuous wave (FMCW) lidar and time-of-flight (ToF) flash lidar. Both concepts, however, face engineering challenges impeding full adaptation. This presentation reviews operation principles of each technique and then discusses in greater detail the unique challenges each one faces. In particular, a light source with a long and stable coherence length is the primary challenge of FMCW lidar, whereas a photodetector with high photosensitivity and low noise is the challenge for ToF-flash lidar. The presentation concludes with a review of possible solutions to the aforementioned obstacles.

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Recent Videos: Light Co., Harvard University, Sony

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Light Co. publishes a video presenting its automotive stereo camera advantages over LiDAR featuring Guidehouse Principal Analyst Sam Abuelsamid, VP at Co-pace Continental AG Anil Rachakonda, Light CEO Dave Grannan, and Light's Chief Product Officer Prashant Velagaleti:

Politecnico di Milano publishes Harvard University's Federico Capasso lecture "Meta Optics: From Flat Lenses to Structured Light and Dark:"

Sony publishes 3 videos on its Pregius S stacked global shutter sensors (1, 2, 3):

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Trieye Unveils VCSEL Powered SWIR Camera

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PRNewswireTriEye announces "the first of its kind VCSEL powered Electro-Optic (EO) SWIR system", integrating TriEye CMOS-based sensor with VCSEL as an illumination source.

TriEye demonstrates an EO system by integrating the TriEye Raven with 1350nm SWIR VCSEL-based illumination, provided by their VCSEL partner, as such they enable the highest power density - which today is over 5 watts per mm2 . This new EO system will provide significant value for short-range applications such as mobile, biometrics, industrial automation, medical and more.

TriEye's solution is said to be the first to provide SWIR based sensing using VCSEL technology. TriEye's SWIR system opens doors to next generation perception capabilities by providing a significant value proposition compared to the NIR spectrum. This includes resilience to sunlight and other sources of ambient noises while providing an eye-safe illumination source. With this combination, the perception system will have longer range and better accuracy than previously achievable with NIR based systems.


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NTT Demos 0.84um Color-Routing Pixel

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NTT Device Technology Lab publishes an OSA Optica paper "Full-color-sorting metalenses for high-sensitivity image sensors" by Masashi Miyata, Naru Nemoto, Kota Shikama, Fumihide Kobayashi, and Toshikazu Hashimoto.

"Image sensors play a critical role in current technologies ranging from smartphones to autonomous vehicles. In these technologies, high-sensitivity image sensors are highly desired because they enable dark-scene/ultra-fast imaging. Unfortunately, a conventional sensor architecture that employs color filters on every pixel fundamentally limits the detected light power per pixel because of the filtering, which has been a long-standing barrier to sensitivity improvement. Here, we demonstrate polarization-insensitive metasurface lenses (metalenses) that sort primary colors on high-density pixels without the use of color filters. The metalenses simultaneously act as pixel-scale color splitters and lenses and are compatible with complementary metal–oxide-semiconductor sensor technology. An image sensor with such metalenses significantly enhances the detected light power, while affording high image quality, incident angle tolerance, and sub-micrometer spatial resolution. The demonstrated architecture opens the way to the development of high-sensitivity color image sensors that exceed current limits while maintaining consistency with state-of-the-art sensor technology."

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Exposure-referred SNR Concept

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 Abhiram Gnanasambandam and Stanley H. Chan from Purdue University publish Arxiv.org paper "Exposure-Referred Signal-to-Noise Ratio for Digital Image Sensors."

"The signal-to-noise ratio (SNR) of a digital image sensor is typically defined as the ratio between the mean over the standard deviation of the sensor's output, thus known as the output-referred SNR. For sensors with a large full-well capacity, the output-referred SNR demonstrates the well-known linear response in the log-log scale. However, as the input exposure approaches the full-well capacity, the vanishing randomness of the saturated pixel will cause this output-referred SNR to artificially go to infinity. Since modern digital image sensors have a small pitch and hence a small full-well capacity, the shortcomings of the output-referred SNR motivated the development of a theoretical concept known as the exposure-referred SNR, first reported in some sensors and computer vision papers in the 1990's and more since 2010. Some intuitions of the exposure-referred SNR have been discussed in the past, but little is known how the exposure-referred SNR can be rigorously derived.

Recognizing the significance of such an analysis to all present and future small pixels, this paper presents a theoretical analysis to justify the definition and answer four questions:

(1) What is the correct definition of SNR?

(2) How is the output-referred SNR related to the exposure-referred SNR?

(3) For simple noise models, the SNRs can be analytically derived, but for complex noise models, how to numerically compute the SNR?

(4) What utilities can the exposure-referred SNR bring to solving imaging tasks?

New theoretical results are shown to confirm the validity of the exposure-referred SNR for image sensors of any bit-depth and full-well capacity."

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Image Sensors at EI 2022

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2022 Electronic Imaging Symposium is to be held on-line starting January 16. There is a number of image sensor presentations:
  1. Plenary Session: Quanta Image Sensors: Counting Photons Is the New Game in Town
    Eric R. Fossum, Professor, Dartmouth Engineering, Dartmouth College
  2. Keynote: Recent developments in GatedVision imaging - Seeing the unseen,
    Ofer David, BrightWay Vision (Israel)
  3. Keynote: Sensing and computing technologies for AR/VR,
    Chiao Liu, Meta Reality Labs Research (United States)
  4. World's first 16:4:1 triple conversion gain sensor with all-pixel AF for 82.4dB single exposure HDR,
    ChangHyun Park, HongSuk Hong, EunSub Shim, JungBin Yun, and KyungHo Lee,
    Samsung Electronics Co., Ltd. (Republic of Korea)
  5. A 40/22nm 200MP stacked CMOS image sensor with 0.61µm pixel,
    Masayuki Uchiyama1, Geunsook Park1, Sangjoo Lee1, Tomoyasu Tate1, Masashi Minagawa2, Shino Shimoyamada2, Zhiqiang Lin1, King Yeung1, Lien Tu1, Wu-Zang Yang3, Alan Hsiung1, Vincent Venezia1, and Lindsay Grant1;
    1OmniVision Technologies, Inc. (United States), 2OmniVision Technologies Japan (Japan), and 3OmniVision Technologies Taiwan (Taiwan)
  6. Perfect RGB color routers for sub-wavelength size CMOS image sensor pixels,
    Peter B. Catrysse, Nathan Zhao, and Shanhui Fan,
    Stanford University (United States)
  7. Time domain noise analysis of oversampled CMOS image sensors,
    Andreas Suess, Mathias Wilhelmsen, Liang Zuo, and Boyd Fowler,
    OmniVision (United States)
  8. An offset calibration technique for CIS column parallel SAR ADC using memory,
    Jaekyum Lee1 and Albert Theuwissen1,2;
    1TU Delft (the Netherlands) and 2Harvest Imaging (Belgium)
  9. Real-time LIDAR imaging by solid-state single chip beam scanner,
    Jisan Lee, Kyunghyun Son, Changbum Lee, Inoh Hwang, Bongyong Jang, Eunkyung Lee, Dongshik Shim, Hyunil Byun, Changgyun Shin, Dongjae Shin, Otsuka Tatsuhiro, Yongchul Cho, Kyoungho Ha, and Hyuck Choo,
    Samsung Electronics Co., Ltd. (Republic of Korea)
  10. A back-illuminated SOI-based 4-tap lock-in pixel with high NIR sensitivity for TOF range image sensors,
    Naoki Takada1, Keita Yasutomi1, Hodaka Kawanishi1, Kazuki Tada1, Tatsuya Kobayashi1, Atsushi Yabata2, Hiroki Kasai2, Noriyuki Miura2, Masao Okihara2, and Shoji Kawahito1;
    1Shizuoka University and 2LAPIS Semiconductor Co., Ltd. (Japan)
  11. An 8-tap image sensor using tapped PN-junction diode demodulation pixels for short-pulse time-of-flight measurements,
    Ryosuke Miyazawa1, Yuya Shirakawa1, Kamel Mars1, Keita Yasutomi1, Keiichiro Kagawa1, Satoshi Aoyama2, and Shoji Kawahito1;
    1Shizuoka University and 2Brookman Technology, Inc. (Japan)
  12. The study and analysis of using CMY color filter arrays for 0.8 mm CMOS image sensors,
    Pohsiang Wang, An-Li Kuo, Ta-Yung Ni, Hao-Wei Liu, Yu C. Chang, Ching-Chiang Wu, and Ken Wu,
    VisEra Technologies (Taiwan)
  13. An anti-UV organic material integrated microlens for automotive CIS,
    William Tsai, VisEra (Taiwan)
  14. Design and analysis on low-power and low-noise single slope ADC for digital pixel sensors,
    Hyun-Yong Jung, Myonglae Chu, Min-Woong Seo, Suksan Kim, Jiyoun Song, Sang-Gwon Lee, Sung-Jae Byun, Minkyung Kim, Daehee Bae, Junan Lee, Sung-Yong Lee, Jongyeon Lee, Jonghyun Go, Jae-kyu Lee, Chang-Rok Moon, and Hyoung-Sub Kim,
    Samsung Electronics Co., Ltd. (Republic of Korea)
  15. 3-Layer stacked pixel-parallel CMOS image sensors using hybrid bonding of SOI wafers,
    Masahide Goto1, Yuki Honda1, Masakazu Nanba1, Yoshinori Iguchi1, Takuya Saraya2, Masaharu Kobayashi2, Eiji Higurashi3, Hiroshi Toshiyoshi2, and Toshiro Hiramoto2;
    1NHK Science & Technology Research Laboratories, 2The University of Tokyo, and 3National Institute of Advanced Industrial Science and Technology (Japan)
  16. Accurate event simulation using high-speed video,
    Xiaozheng Mou, Kaijun Feng, Alex Yi, Steve Wang, Huan Chen, Xiaoqin Hu, Menghan Guo, Shoushun Chen, and Andreas Suess,
    OmniVision (United States)
  17. Photon-starving and high-dynamic-range imaging with photon-counting quanta image sensors (Invited),
    Jiaju Ma, GigaJot Technology (United States)
  18. Photon-limited object detection for CMOS cameras and quanta image sensors (Invited),
    Stanley Chan1, Chengxi Li1, Xiangyu Qu1, Abhiram Gnanasambandam1, Omar Elgendy2, and Jiaju Ma2;
    1Purdue University and 2GigaJot Technology (United States)
  19. High dynamic range single photon LiDAR (Invited),
    Robert K. Henderson, University of Edinburgh (United Kingdom)
  20. Log-simplex denoising for color images (Invited),
    Sarah Miller1, Keigo Hirakawa1, and Chen Zhang2;
    1University of Dayton and 2OmniVision Technologies, Inc. (United States)
  21. Computational imaging, one photon at a time (Invited),
    Mohit Gupta, University of Wisconsin, Madison (United States)
  22. From a handful of photons (Invited),
    Hamid Sheikh, Samsung Research America (United States)
  23. Course SC12: Signal Processing for Photon-Limited Imaging
    Instructor: Stanley Chan, Purdue University 

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Ams Unveils SPAD ToF Sensors

Image Sensors World        Go to the original article...

ams OSRAM is expanding its portfolio of dToF modules with three new devices for multi-zone and multi-object detection with a wider FoV and extended range. The multi-zone dToF modules TMF8820, TMF8821, and TMF8828 allow for a precise distance measurement.

The TMF8820 divides the FoV into 3x3 or 9 individual detection zones, the TMF8821 into 4x4 or 16 individual detection zones and the TMF8828 into 8x8 or 64 individual detection zones. With multi-zone detection, it is possible to identify where an object is located within the sensors FoV. These new devices feature a dynamically adjustable FoV up to 63°, enabling customers to select either a narrow or wide FoV to meet their application needs. All th
ree dToF modules have a detection range from one centimeter up to five meters.

The modules combine a 940 nm VCSEL, a SPAD array with matching multi-lens optics, and an on-chip microcontroller for histogram processing in one device. Thanks to the compact dimensions of 2.0 mm x 4.6 mm x 1.4 mm, the modules are said to be the smallest multi-zone dToF modules available on the market.


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NTT Metalens Turns Any Sensor into Hyperspectral One

Image Sensors World        Go to the original article...

NTT R&D Forum presents a new approach to hyperspectral imaging:

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Sony Splits 4T Pixel Transistors Between 2 Layers of Stacked Sensor

Image Sensors World        Go to the original article...

Sony presents IEDM paper on pixel level stacked sensor with 2-Layer Transistor Pixel. Whereas conventional CMOS image sensors’ photodiodes and pixel transistors occupy the same substrate, Sony’s new technology separates photodiodes and pixel transistors on different substrate layers. This is said to double saturation signal level relative to conventional image sensors, widen DR and reduce noise. The new technology’s pixel structure will enable pixels to maintain or improve their existing properties at not only current but also smaller pixel sizes.

Since pixel transistors other than transfer gates (TRG), including reset transistors (RST), select transistors (SEL) and amp transistors (AMP), occupy a photodiode-free layer, the amp transistors can be increased in size. By increasing amp transistor size, Sony says it was able to substantially reduce the noise.

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