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SEMI MEMS & Imaging Sensors Summit 2024 will take place November 14-15 at the International Conference Center Munich (ICM), Messe Münich in Germany.

Thursday, 14^th November 2024 

Session 1: Market Dynamics: Landscape and Growth Strategies

09:00  Welcome Remarks
Laith Altimime, President, SEMI Europe

09:20  Opening Remarks by MEMS and Imaging Committee Chair
Philippe Monnoyer, VTT Technical Research Center of Finland Ltd

09:25  Keynote: Smart Sensors for Smart Life – How Advanced Sensor Technologies Enable Life-Changing Use Cases
Stefan Finkbeiner, General Manager, Bosch Sensortec

09:45  Keynote: Sensing the World: Innovating for a More Sustainable Future
Simone Ferri, APMS Group Vice President, MEMS sub-group General Manager, STMicroelectronics

10:05  Reserved for Yole Development

10:25  Key Takeaways by MEMS and Imaging Committee Chair
Philippe Monnoyer, VTT Technical Research Center of Finland Ltd

10:30  Networking Coffee Break

Session 2: Sustainable Supply Chain Capabilities

11:10  Opening Remarks by Session Chair
Pawel Malinowski, Program Manager and Researcher, imec

11:15  A Paradigm Shift From Imaging to Vision: Oculi Enables 600x Reduction in Latency-Energy Factor for Visual Edge Applications
Charbel Rizk, Founder & CEO, Oculi

11:35  Reserved for Comet Yxlon

11:55  Key Takeaways by Session Chair
Pawel Malinowski, Program Manager and Researcher, imec

12:00  Networking Lunch

Session 3: MEMS - Exploring Future Trends for Technologies and Device Manufacturing

13:20  Opening Remarks by Session Chair
Pierre Damien Berger, MEMS Industrial Partnerships Manager, CEA LETI

13:25  Unlocking Novel Opportunities: How 300mm-capable MEMS Foundries Will Change the Game
Jessica Gomez, CEO, Rogue Valley Microdevices

13:45  Trends in Emerging MEMS
Alissa Fitzgerald, CEO, A.M. Fitzgerald & Associates, LLC

14:05  The Most Common Antistiction Films are PFAS, Now What?
David Springer, Product Manager, MVD and Release Etch Products, KLA Corporation

14:25  Reserved for Infineon

14:45  Latest Innovations in MEMS Wafer Bonding
Thomas Uhrmann, Director of Business Development, EV Group

15:05  Key Takeaways by Session Chair
Pierre Damien Berger, MEMS Industrial Partnerships Manager, CEA LETI

Session 4: Imaging - Exploring Future Trends for Technologies and Device Manufacturing

15:10  Opening Remarks by Session Chair
Stefano Guerrieri, Engineering Fellow and Key Expert Imager & Sensor Components, ams OSRAM

15:15  Topic Coming Soon
Avi Bakal, CEO & Co-founder, TriEye

15:35  Active Hyperspectral Imaging Using Extremely Fast Tunable SWIR Light Source
Jussi Soukkamaki, Lead, Hyperspectral & Imaging Technologies, VTT Technical Research Centre of Finland Ltd

15:55  Networking Coffee Break

16:40  Reserved

17:00  Reserved for CEA-Leti

17:20  Reserved for STMicroelectronics

17:40  Key Takeaways by Session Chair
Stefano Guerrieri, Engineering Fellow and Key Expert Imager & Sensor Components, ams OSRAM

Friday, 15th November 2024 

Session 5: MEMS and Imaging Young Talent

09:00  Opening Remarks by Session Chair
Dimitrios Damianos, Project Manager, Yole Group

09:05  Unlocking Infrared Multispectral Imaging with Pixelated Metasurface Technology
Charles Altuzarra, Chief Executive Officer & Co-founder, Metahelios

09:10  Electrically Tunable Dual-Band VIS/SWIR Imaging and Sensing
Andrea Ballabio, CEO, EYE4NIR

09:15  FMCW Chip-Scale LiDARs Scale Up for Large Volume Markets Thanks to Silicon Photonics Technology
Simoens François, CEO, SteerLight

09:20  ShadowChrome: A Novel Approach to an Old Problem
Geoff Rhoads, Chief Technology Officer, Transformative Optics Corporation

09:25  Feasibility Investigation of Spherically Bent Image Sensors
Amit Pandey, PhD Student, Technische Hochschule Ingolstadt

09:30  Intelligence Through Vision
Stijn Goossens, CTO, Qurv

09:35  Next Generation Quantum Dot SWIR Sensors
Artem Shulga, CEO & Founder, QDI Systems

09:40  Closing Remarks by Session Chair
Dimitrios Damianos, Project Manager, Yole Group

09:45  Networking Coffee Break

Session 6: Innovations for Next-Gen Applications: Smart Mobility

10:35  Opening Remarks by Session Chair
Bernd Dielacher, Business Development Manager MEMS, EVG

10:40  Reserved

11:00  New Topology for MEMS Advances Performance and Speeds Manufacturing
Eric Aguilar, CEO, Omnitron Sensors, Inc.

11:20  Key Takeaways by Session Chair
Bernd Dielacher, Business Development Manager MEMS, EVG

Session 7: Innovations for Next-Gen Applications: Health

11:25  Opening Remarks by Session Chair
Ran Ruby YAN, Director of HMI & HealthTech Business Line, GLOBALFOUNDRIES

11:30  Reserved

11:50  Sensors for Monitoring Vital Signs in Wearable Devices
Markus Arzberger, Senior Director, ams-OSRAM International GmbH

12:10  Pioneering Non-Invasive Wearable MIR Spectrometry for Key Health Biomarkers Analysis
Jan F. Kischkat, CEO, Quantune Technologies GmbH

12:30  Key Takeaways by Session Chair
Ran Ruby YAN, Director of HMI & HealthTech Business Line, GLOBALFOUNDRIES

12:35  End of Conference Reflections by MEMS and Imaging Committee Chair
Philippe Monnoyer, VTT Technical Research Center of Finland Ltd

12:45  Closing Remarks
Laith Altimime, President, SEMI Europe

12:50  Networking Lunch

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The list of topics and the authors for the following two events related to image sensor technology have been finalized for the IEEE SENSORS 2024 Conference. The conference will be held in Kobe, Japan, from 20-23 October 2024. It will provide the opportunity to hear world class speakers in the field of image sensors and to sample the sensor ecosystem that extends beyond to see how imaging fits in.

Workshop: “From Imaging to Sensing: Latest and Future Trends of CMOS Image Sensors” [Sunday, 20 October]

Organizers: Sozo Yokogawa (Sony Semiconductor Solutions corp.) • Erez Tadmor (onsemi)

“Trends and Developments in State-of-the-Art CMOS Image Sensors”, Daniel McGrath, TechInsights
“CMOS Image Sensor Technology: what we have solved, what are to be solved”, Eiichi Funatsu, OMNIVISION
“Automotive Imaging: Beyond human Vision”, Vladi Korobov, onsemi
“Recent Evolution of CMOS Image Sensor Pixel Technology”, Bumsuk Kim et al., Samsung Electronics
“High precision ToF image sensor and system for 3D scanning application”, Keita Yasutomi, Shizuoka University
“High-definition SPAD image sensors for computer vision applications”, Kazuhiro Morimoto, Canon Inc.
“Single Photon Avalanche Diode Sensor Technologies for Pixel Size Shrinkage, Photon Detection Efficiency Enhancement and 3.36-pm-pitch Photon-counting Architecture”, Jun Ogi, Sony Semiconductor Solutions Corp.
“SWIR Single-Photon Detection with Ge-on-Si Technology”, Neil Na, Artilux Inc.
“From SPADs to smart sensors: ToF system innovation and AI enable endless application”, Laurent Plaza & Olivier Lemarchand, STMicroelectronics
“Depth Sensing Technologies, Cameras and Sensors for VR and AR”, Harish Venkataraman, Meta Inc.
 
Focus session: Overview of The Focus Sensor on Stacking in Image Sensor, [Monday, 21 October]

Orgainizer: S-G. Wu, Brillnics

Co-chairs: DN Yaung, TSMC; John McCarten, L3 Harris

Over the past decade, 3-dimensional (3D) wafer level stacked backside Illuminated (BSI) CMOS image sensors (CIS) have achieved the rapid progress in mass production. This focus session on stacking in image sensors will have 4 invited papers to explore the sensor stack technology evolution from process development, circuit architecture to AI/edge computing in system integration.

“The Productization of Stacking in Image Sensors”, Daniel McGrath, TechInsights
“Evolution of Image Sensing and Computing Architectures with Stacking Device Technologies”, BC Hseih, Qualcomm
“Event-based vision sensor”, Christoph Posch, Prophesee
“Evolution of digital pixel sensor (DPS) and advancement by stacking technologies”, Ikeno Rimon, Brillnics

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In this video, we're breaking down Quantum Efficiency (QE) and its crucial role in CIS. QE is a critical measure of how efficiently our sensors convert incoming light into electrical signals, directly affecting image accuracy and quality. This video will guide you through what QE means for CIS, its impact on your images, and how we're improving QE for better, more reliable imaging.

GalaxyCore DAG HDR Technology Film

Exploring GalaxyCore's Sensor-Shift Optical Image Stabilization (OIS) in under Two Minutes

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In a recent paper titled "PCH-EM: A Solution to Information Loss in the Photon Transfer Method" in IEEE Trans. on Electron Devices, Aaron Hendrickson et al. propose a new statistical technique to estimate CIS parameters such as conversion gain and read noise.

Abstract: Working from a Poisson-Gaussian noise model, a multisample extension of the photon counting histogram expectation-maximization (PCH-EM) algorithm is derived as a general-purpose alternative to the photon transfer (PT) method. This algorithm is derived from the same model, requires the same experimental data, and estimates the same sensor performance parameters as the time-tested PT method, all while obtaining lower uncertainty estimates. It is shown that as read noise becomes large, multiple data samples are necessary to capture enough information about the parameters of a device under test, justifying the need for a multisample extension. An estimation procedure is devised consisting of initial PT characterization followed by repeated iteration of PCH-EM to demonstrate the improvement in estimating uncertainty achievable with PCH-EM, particularly in the regime of deep subelectron read noise (DSERN). A statistical argument based on the information theoretic concept of sufficiency is formulated to explain how PT data reduction procedures discard information contained in raw sensor data, thus explaining why the proposed algorithm is able to obtain lower uncertainty estimates of key sensor performance parameters, such as read noise and conversion gain. Experimental data captured from a CMOS quanta image sensor with DSERN are then used to demonstrate the algorithm’s usage and validate the underlying theory and statistical model. In support of the reproducible research effort, the code associated with this work can be obtained on the MathWorks file exchange (FEX) (Hendrickson et al., 2024).

RRMSE versus read noise for parameter estimates computed using constant flux implementation of PT and PCH-EM. RRMSE curves for PT μ~ and σ~ grow large near σread=0 and were clipped from the plot window.

Open access paper link: https://ieeexplore.ieee.org/document/10570238

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The Harvest Imaging forum tradition continues, a next and tenth one will be organized on November 7 & 8, 2024, in Delft, the Netherlands. The basic intention of the Harvest Imaging forum is to have a scientific and technical in-depth discussion on one particular topic that is of great importance and value to digital imaging. The forum 2024 will be an in-person event.

The 2024 Harvest Imaging forum will deal with a single topic from the field of solid-state imaging world and will have only one world-level expert as the speaker:

"AI and VISION : A shallow dive into deep learning"

Prof. dr. Jan van Gemert (Delft Univ. of Technology, Nl)

Abstract: Artificial Intelligence is taking the world by storm! The AI engine is powered by “Deep Learning”. Deep learning differs from normal computer programming in that it allows computers to learn tasks from large, labelled, datasets. In this Harvest Imaging Forum we will go through all fundamentals of Deep Learning: Multi-layer perceptrons, Back-propagation, Optimization, Convolutional neural networks, Recurrent neural networks, un-/self-supervised learning and transformers and self-attention (GPT).

Bio: Jan van Gemert received a PhD degree from the University of Amsterdam in 2010. There he was a post-doctoral fellow as well as at École Normale Supérieure in Paris. Currently he leads the Computer Vision lab at Delft University of Technology. He teaches the Deep learning and Computer Vision MSc courses. His research focuses on visual inductive priors for deep learning for automatic image and video understanding. He has published over 100 peer-reviewed papers with more than 7,500 citations. See his Google scholar profile for his publications: https://scholar.google.com/citations?hl=en&user=JUdMRGcAAAAJ

Registration: The registration fee for this 2-days forum is set to 1295 Euro for an in-person attendance. Next to the cost of attending the forum, this fee for the in-person attendance does include:

•  Coffee breaks in the mornings and afternoons,
•  Lunch on both forum days,
•  Dinner on the first forum day,
•  Soft and hard copy of the presented material.

If you are interested to attend this forum, please fill out the registration form here: https://harvestimaging.com/forum_registration_2024.php

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Title: Event-based Image Sensor for low-power

Author: Mohamed AKRARAI (Universite Grenoble Alpes)

Abstract: In the framework of the OCEAN 12 European project, this PhD achieved the design, the implementation, the testing of an event based image sensor, and the publication of several scientific papers in international conferences, including renowned ones like the International Symposium on Asynchronous Circuits and Systems (ASYNC). The design of event-based image sensors, which are frameless, require a dedicated architecture and an asynchronous logic reacting to events. First, this PhD gives an overview of architectures based on a hybrid pixel matrix including TFS and DVS pixels. Indeed, this two kind of pixels are able to manage the spatial redundancy and the temporal redundancy respectively. One of the main achievement of this work is to take advantage of having both pixels inside an imager in order to reduce its output bitstream and its power consumption. Then, the design of the pixels and readout in FDSOI 28 nm technology from STMicroelectronics is detailed. Finally, two image sensors have been implemented in a testchip and tested.

Link: https://theses.hal.science/tel-04213080v1/file/AKRARAI_2023_archivage.pdf

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Full article: https://www.eetimes.eu/imec-getting-high-precision-sensors-to-market/

Imec: Getting High-Precision Sensors to Market

At the recent ITF World 2024, EE Times Europe talked with imec researchers to catch up on what they’re doing with high-precision sensors—and more importantly, how they make sure their innovations get into the hands of industrial players.

Imec develops sensors for cameras and displays, and it works with both light and ultrasound—for medical applications, for example. But the Leuven, Belgium–based research institute never takes technology to market itself. It either finds industrial partners—or when conditions are right, imec creates a spinoff. One way to understand how imec takes an idea from lab to fab and finds a way to get it to market is to zoom in on its approach with image sensors for cameras.

“We make image sensors that are at the beating heart of incredible cameras around the world,” said Paul Heremans, vice president of future CMOS devices and senior fellow at imec. “Our research starts with material selection and an overall new concept for sensors and goes all the way to development, engineering and low-volume manufacturing within imec’s pilot line.”

A good example is the Pharsighted E9-100S ultra-high-speed video camera, developed by Pharsighted LLC and marketed by Photron. The camera reaches 326,000 frames per second (full frame: 640 × 480 pixels) and up to 2,720,000 frames per second at a lower frame size (640 × 32 pixels), thanks to a high-speed image sensor developed and manufactured by imec.

Another example is an electron imager used in a cryo-transmission electron microscope (cryo-TEM) marketed by a U.S. company called Thermo Fisher. The instrument produces atomic resolution pictures of DNA strands and other complex molecules. These images help in the drug-discovery process by allowing researchers to understand the structure of the molecules they need to target.
Thermo Fisher uses direct electron detection imagers, developed by imec and built into the company’s Falcon direct electron detection imagers, each composed of 4K × 4K pixels. The pixels are very large to get to the ultimate sensitivity. Consequently, the chip is so large (5.7 × 5.7 cm) that only four fit on a 200-mm wafer.

A third example is hyperspectral imagers, with very special filters that detect many more colors than just red, green and blue (RGB). Hyperspectral imagers pick up tens or hundreds of spectral bands. They can achieve this level of performance because imec implements processing filters on each pixel.

“We can do that on almost any commercial imager and turn it into a hyperspectral camera,” Heremans said. “Our technology is used by plenty of customers with a range of applications—from surveillance to satellite-based Earth observation, from medical to agriculture and more.”

Spectricity

To bring some of its work on hyperspectral imagers to market, imec created a startup called Spectricity. “The whole idea is to bring this field of multispectral imaging or spectroscopy into cellphones or other high-volume products,” said Glenn Vandevoorde, CEO of Spectricity. “Our imagers can see things that are not visible to the human eye. Instead of just processing RGB data, which a traditional camera does, we take a complete spectral image, where each pixel contains 16 different color points—including near-infrared. And with that, you can detect different materials that look alike but are actually very different. Or you can do color correction on smartphones. Sometimes people look very different, depending on the ambient light. We can detect what kind of light is shining—and based on that, adjust the color.”
The first use case for cellphones is auto white balancing. When a picture is taken with a cellphone, sometimes the colors show up very differently from reality, because the camera doesn’t have an accurate white point, which is the set of values that make up the color white in an image. These values change under different conditions, which means they need to be calibrated often. All other colors are then adjusted based on the white point reference.

Traditional smartphone cameras cannot determine the ambient light accurately, so they cannot find the white point to serve as a viable reference. But the multispectral imager obtains the full spectral information of the ambient light and applies advanced AI algorithms to detect the white point, which leads to accurate auto white balancing and true color correction.

Spectricity said its sensor is being evaluated by seven out of the top eight smartphone manufacturers in the world for integration into phones. “By the end of this year, you will see several smartphone vendors launching the first phones with multispectral imagers inside,” Vandevoorde said.

While smartphones are the ultimate target for high volume, they are also very cost-competitive—and it takes a long time to introduce a new feature in a smartphone. Spectricity is targeting other smartphone applications but also applications for webcams, security cameras and in-cabin video cameras for cars. One category of use cases takes advantage of the ability of multispectral images to detect health conditions.

 

 

“For example, you can accurately monitor how a person’s skin tone develops every day,” Vandevoorde said. “We can monitor blood flow in the skin, we can monitor moisture in the skin, we can detect melanoma and so on. These and many other things can be detected with these multispectral imagers.”
Spectricity has raised €28 million in funding since it was founded in 2018—and the startup has its own mass-production line at X-Fab, one of the company’s investors. “We have our machinery and our process installed there,” Vandevoorde said. “It’s now going through qualification—and by the end of the year, we’ll be ready for mass production to start shipping large volume to customers.” 

How imec finds the right trends to target
Spectricity is a good example of how imec spots a need and develops technology to meet that need. Spectroscopy, of course, is not new. It’s been around for decades, and researchers use it in labs to detect different materials and different gases. What’s new is that imec integrated spectroscopy onto CMOS technology and developed processes to produce it in high volumes for just a couple of dollars. Researchers worked on the idea for about 10 years—and once it was running on imec’s pilot line, the institute set up Spectricity to take it into mass production and develop applications around it. 

“We sniff around different trends,” said Xavier Rottenberg, scientific director and group leader of wave-based sensors and actuators at imec. “We’re in contact with a lot of players in the industry to get exposed to plenty of problems. Based on that, we develop a gut feeling. But gut feelings are dangerous, because it might be that you’re just hungry. However, with an educated gut feeling, sometimes your intuition is right.”

Once imec develops an idea in the lab, it takes the technology to its pilot line to develop a demonstrator. “We do proofs of concept to see how a device performs,” Rottenberg said. “Then we set up contacts in the ecosystem to form partnerships to bring the platform to a level where it can be mass-produced in an industrial fab.”

In some cases, an idea is too far out for partners to pick up for near-term profit. That’s when imec ventures out with a spinoff company, as it did with Spectricity.

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Link to full article: https://www.phonearena.com/news/sonys-image-sensor-makeover-imx-to-lytia-by-2026_id160402

Sony's image sensor makeover: IMX to LYTIA by 2026

... there's a buzz about Sony making a branding shift for its smartphone image sensors. According to a recent report, Sony is considering moving all its mobile image sensors, including the current IMX lineup, under the newer LYTIA brand. The company is gradually phasing out the IMX brand, and some IMX sensors have already been rebranded to LYTIA. Reportedly, the company plans to fully transition to the LYT lineup by 2026.

The report states that the 50MP IMX890 and IMX882 sensors have already been rebranded as LYT-701 and LYT-600. For instance, the LYT-600 is already used in the vivo X100 Ultra, launched in May this year.

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Marras et al. presented a paper titled "Development of the Continuous Readout Digitising Imager Array Detector" at the Topical Workshop on Electronics for Particle Physics 2023.

Abstract: Abstract: The CoRDIA project aims to develop an X-ray imager capable of continuous operation in excess of 100 kframe/s. The goal is to provide a suitable instrument for Photon Science experiments at diffraction-limited Synchrotron Rings and Free Electron Lasers considering Continuous Wave operation. Several chip prototypes were designed in a 65 nm process: in this paper we will present an overview of the challenges and solutions adopted in the ASIC design.

 

 

 

  

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Zhang et al. from MIT recently published a paper titled "Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy" in Nature Communications.

Abstract: High-speed wide-field fluorescence microscopy has the potential to capture biological processes with exceptional spatiotemporal resolution. However, conventional cameras suffer from low signal-to-noise ratio at high frame rates, limiting their ability to detect faint fluorescent events. Here, we introduce an image sensor where each pixel has individually programmable sampling speed and phase, so that pixels can be arranged to simultaneously sample at high speed with a high signal-to-noise ratio. In high-speed voltage imaging experiments, our image sensor significantly increases the output signal-to-noise ratio compared to a low-noise scientific CMOS camera (~2–3 folds). This signal-to-noise ratio gain enables the detection of weak neuronal action potentials and subthreshold activities missed by the standard scientific CMOS cameras. Our camera with flexible pixel exposure configurations offers versatile sampling strategies to improve signal quality in various experimental conditions.

a Pixels within an ROI capture spatiotemporally-correlated physiological activity, such as signals from somatic genetically encoded voltage indicators (GEVI). b Simulated CMOS pixel outputs with uniform exposure (TE) face the trade between SNR and temporal resolution. Short TE (1.25 ms) provides high temporal resolution but low SNR. Long TE (5 ms) enhances SNR but suffers from aliasing due to low sample rate, causing spikes (10 ms interspike interval) to be indiscernible. Pixel outputs are normalized row-wise. Gray brackets: the zoomed-in view of the pixel outputs. c Simulated pixel outputs of the PE-CMOS. Pixel-wise exposure allows pixels to sample at different speeds and phases. Two examples: in the staggered configuration, the pixels sample the spiking activity with prolonged TE (5 ms) at multiple phases with offsets of (Δ = 0, 1,25, 2.5, 3.75 ms). This configuration maintains SNR and prevents aliasing, as the interspike interval exceeding the temporal resolution of a single phase is captured by phase-shifted pixels. In the multiple exposure configuration, the ROI is sampled with pixels at different speeds, resolving high-frequency spiking activity and slow varying subthreshold potentials that are challenging to acquire simultaneously at a fixed sampling rate. d The PE-CMOS pixel schematic with 6 transistors (T1-T6), a photodiode (PD), and an output (OUT). RST, TX, and SEL are row control signals. EX is a column signal that controls pixel exposure. e The pixel layout. The design achieves programmable pixel-wise exposure while maximizing the PD fill factor for high optical sensitivity.

 

 

 

Open access article link: https://www.nature.com/articles/s41467-024-48765-5

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Link: https://www.research-collection.ethz.ch/handle/20.500.11850/683623

Thesis title: A Scientific Event Camera: Theory, Design, and Measurements
Author: Rui Garcia
Advisor: Tobi Delbrück

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Article by Axel Clouet, Ph.D. (Yole Group)

Link: https://www.yolegroup.com/strategy-insights/onsemi-enters-the-realm-of-ir-by-acquiring-swir-vision-systems/

Onsemi, a leading CMOS image sensor supplier, has acquired SWIR Vision Systems, a pioneer in quantum-dots-based short-wave infrared (SWIR) imaging technology. Yole Group tracks and reports on these technologies through reports like Status of the CMOS Image Sensor 2024 and SWIR Imaging 2023. Yole Group’s Imaging Team discusses how this acquisition mirrors current industry trends.

SWIR Vision Systems pioneered the quantum dots platform

SWIR imaging modality has long been used in defense and industrial applications, generating $97 million in revenue for SWIR imager suppliers in 2022. However, its adoption has been limited by the high cost of InGaAs technology, the historical platform necessary to capture these wavelengths, compared to standard CMOS technology. In recent years, SWIR has attracted interest with the emergence of lower-cost technologies like quantum dots and germanium-on-silicon, both compatible with CMOS fabs and anticipated to serve the mass markets in the long term.

SWIR Vision Systems, a U.S.-based start-up, pioneered the quantum dots platform, introducing the first-ever commercial product in 2018. This company is fully vertically integrated, making its own image sensors for integration into its own cameras. 

An acquisition aligned with Onsemi’s positioning

The CMOS image sensor industry was worth $21.8 billion in 2023 and is expected to reach $28.6 billion by 2029. With a market share of 6%, onsemi is the fourth largest CMOS image sensor supplier globally. The company is the leader in the fast-growing $2.3 billion automotive segment and has a significant presence in the industrial, defense and aerospace, and medical segments.

In the short term, SWIR products will help onsemi catch up with Sony’s InGaAs products in the industrial segment by leveraging the cost advantage of quantum dots. Its existing sales channels will facilitate the adoption of quantum dots technology by camera manufacturers.

Additionally, onsemi is set to establish long-term relationships with defense customers, a segment poised for growth due to global geopolitical instability. By acquiring SWIR Vision Systems and the East Fishkill CMOS fab completed in 2022, onsemi secured its supply chain, owns the SWIR strategic technology, and has a large-volume U.S.-based factory. It is, therefore, aligned with the dual-use approach promoted by the U.S. government for its local industry.

This acquisition will contribute to faster development and adoption of the quantum dots platform without disrupting the SWIR landscape. For onsemi, it is an attractive feature to quickly attract new customers in the industrial and defense sectors and a differentiating technology for the automotive segment in the long term.

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Link: https://www.prnewswire.com/news-releases/tof-sensor-for-enhanced-object-detection-and-safety-application-nuvoton-launches-new-3d-tof-sensor-with-integrated-distance-calculation-circuit-302197512.html

TOF Sensor for Enhanced Object Detection and Safety Application: Nuvoton Launches New 3D TOF Sensor with Integrated Distance Calculation Circuit

KYOTO, Japan, July 16, 2024 /PRNewswire/ -- Nuvoton Technology Corporation Japan is set to begin mass production of a 1/4-inch VGA (640x480 pixel) resolution 3D Time-of-Flight (TOF) sensor in July 2024. This sensor is poised to revolutionize the recognition of people and objects in various indoor and outdoor environments. This capability has been achieved through Nuvoton's unique pixel design technology and distance calculation/Image Signal Processor (ISP) technology.
 

1. High Accuracy in Bright Ambient Lighting Conditions
Leveraging Nuvoton's proprietary CMOS image sensor pixel technology and CCD memory technology, the new TOF sensor has four memories in the 5.6-square-micrometer pixel compared to the three memories of its conventional TOF sensor and achieves accurate distance sensing by simultaneously controlling pulse light sources and acquiring background light signals. It can provide the precise recognition of the position and shape of people and objects under various ambient lighting conditions.

2. Accurate Distance Measurement for Moving Objects
With four embedded memories within each pixel, Nuvoton's new TOF sensor outputs distance images in a single frame. This innovative design significantly reduces motion blur and measurement errors in moving objects by capturing and calculating distance from four types of imaging signals within one frame. This feature is particularly suited for applications requiring dynamic object detection and recognition, such as obstacle detection for autonomous mobile robots (AMRs) and airbag intensity control in vehicles.

3. Integrated Distance Calculation Circuit for Fast and Accurate Sensing
Nuvoton's new TOF sensor is equipped with an integrated distance calculation circuit and a signal correction ISP, enabling it to output high-speed, high-precision distance (3D) images at up to 120 fps (QVGA) without delay. This eliminates the need for distance calculation by the system processor, reducing the processing overhead and enabling faster sensing systems. Additionally, the sensor can simultaneously output distance (3D) and IR (2D) images, useful for applications requiring both high precision and recognition/authentication functions.
 

For more information, please visit: https://www.nuvoton.com/products/image-sensors/3d-tof-sensors/kw330-series/
 

About Nuvoton Technology Corporation Japan: https://www.nuvoton.co.jp/en/

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 Owl Autonomous Imaging

Website Careers Page Link

Digital Design Engineer - Link to job description

Senior Analog Design Engineer - Link to job description

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The International Image Sensor Society (IISS) calls for nominations for IISS Exceptional Lifetime Achievement Award, IISS Pioneering Achievement Award, and IISS Exceptional Service Award. The Awards are to be presented at the 2025 International Image Sensor Workshop (IISW) (to be held in Japan).
 
Description of Awards:

• IISS Exceptional Lifetime Achievement Award. This Award is made to a member of the image sensor community who has made substantial sustained and exceptional contributions to the field of solid-state image sensors over the course of their career. (Established 2013)
• IISS Pioneering Achievement Award. This award is to recognize a person who made a pioneering achievement in image sensor technology as judged by at least 10 years of hindsight as a foundational contribution. (Established 2015)
• IISS Exceptional Service Award. This award is presented for exceptional service to the image sensor specialist community. This category recognizes activities in editorial roles, conference leadership roles, and so on, outside of their service related to the IISS. (Established 2011)

 
Submission deadline: all nominations must be received by October 1st, 2024 using the specified entry format.

Email for submissions: 2025nominations@imagesensors.org

Note: Self-nomination is discouraged.

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Link: https://www.sae.org/news/2024/07/adas-sensor-update

Are today’s sensors ready for next-level automated driving?

SAE Level 3 automated driving marks a clear break from the lower levels of driving assistance since that is the dividing line where the driver can be freed to focus on things other than driving. While the driver may sometimes be required to take control again, responsibility in an accident can be shifted from the driver to the automaker and suppliers. Only a few cars have met regulatory approval for Level 3 operation. Thus far, only Honda (in Japan), the Mercedes-Benz S-Class and EQS sedans with Drive Pilot and BMW’s recently introduced 7 Series offer Level 3 autonomy.

With more vehicles getting L3 technology and further automated driving skills being developed, we wanted to check in with some of the key players in this tech space and hear the latest industry thinking about best practices for ADAS and AV Sensors.

Towards More Accurate 3D Object Detection

Researchers from Japan's Ritsumeikan University have developed DPPFA-Net, an innovative network that combines 3D LiDAR and 2D image data to improve 3D object detection for robots and self-driving cars. Led by Professor Hiroyuki Tomiyama, the team addressed challenges in accurately detecting small objects and aligning 2D and 3D data, especially in adverse weather conditions.

DPPFA-Net incorporates three key modules:

•  Memory-based Point-Pixel Fusion (MPPF): Enhances robustness against 3D point cloud noise by using 2D images as a memory bank.
•  Deformable Point-Pixel Fusion (DPPF): Focuses on key pixel positions for efficient high resolution feature fusion.
•  Semantic Alignment Evaluator (SAE): Ensures semantic alignment between data representations during fusion.

The network outperformed existing models in the KITTI Vision Benchmark, achieving up to 7.18% improvement in average precision under various noise conditions. It also performed well in a new dataset with simulated rainfall.

Ritsumeikan University researchers said this advancement has significant implications for self driving cars and robotics. It could lead to reduced accidents, improved traffic flow and safety, and enhanced robot capabilities in various applications. The improvements in 3D object detection are expected to contribute to safer transportation, enhanced robot capabilities, and accelerated development of autonomous systems.

AEVA

Aeva has introduced Atlas, the first 4D lidar sensor designed for mass-production automotive applications. Atlas aims to enhance advanced driver assistance systems (ADAS) and autonomous driving, meeting automotive-grade requirements.

•  The company’s sensor is powered by two key innovations: the fourth-generation lidar-on-chip module called Aeva CoreVision that incorporate all key lidar elements in a smaller package, using silicon photonics technology.
•  Aeva X1 new system-on-chip (SoC) lidar processor that integrate data acquisition, point cloud processing, scanning system, and application software.

These innovations make Atlas 70% smaller and four times more power-efficient than Aeva's previous generation, enabling various integration options without active cooling. Atlas uses Frequency Modulated Continuous Wave (FMCW) 4D lidar technology, which offers improved object detection range and immunity to interference. It also provides a 25% greater detection range for low-reflectivity targets and a maximum range of 500 meters.

Atlas is accompanied by Aeva’s perception software, which harnesses advanced machine learning-based classification, detection and tracking algorithms. Incorporating the additional dimension of velocity data, Aeva’s perception software provides unique advantages over conventional time-of-flight 3D lidar sensors.

Atlas is expected to be available for production vehicles starting in 2025, with earlier sample availability for select customers. Aeva's co-founder and CTO Mina Rezk said that Atlas will enable OEMs to equip vehicles with advanced safety and automated driving features at highway speeds, addressing previously unsolvable challenges. Rezk believes Atlas will accelerate the industry's transition to Frequency-Modulated Continuous-Wave 4D lidar technology, which is increasingly considered the end state for lidar due to its enhanced perception capabilities and unique instant velocity data.

Luminar

Following several rocky financial months and five years of development, global automotive technology company Luminar is launching Sentinel, its full-stack software suite. Sentinel enables automakers to accelerate advanced safety and autonomous functionality, including 3D mapping, simulation, and dynamic lidar features. A study by the Swiss Re Institute showed cars equipped with Luminar lidar and Sentinel software demonstrated up to 40% reduction in accident severity.

Developed primarily in-house with support from partners, including Scale AI, Applied Intuition, and Civil Maps (which Luminar acquired in 2022), Sentinel leverages Luminar's lidar hardware and AI-based software technologies.

CEO and founder Austin Russell said Luminar has been building next-generation AI-based safety and autonomy software since 2017. “The majority of major automakers don't currently have a software solution for next-generation assisted and autonomous driving systems,” he said. “Our launch couldn't be more timely with the new NHTSA mandate for next-generation safety in all U.S.-production vehicles by 2029, and as of today, we're the only solution we know of that meets all of these requirements.”

Mobileye

Mobileye has secured design wins with a major Western automaker for 17 vehicle models launching in 2026 and beyond. The deal covers Mobileye's SuperVision, Chauffeur, and Drive platforms, offering varying levels of autonomous capabilities from hands-off, eyes-on driving to fully autonomous robotaxis.

All systems will use Mobileye's EyeQ 6H chip, integrating sensing, mapping, and driving policy. The agreement includes customizable software to maintain brand-specific experiences.
CEO Amnon Shashua called this an "historic milestone" in automated driving, emphasizing the scalability of Mobileye's technology. He highlighted SuperVision's role as a bridge to eyes-off systems for both consumer vehicles and mobility services.

Initial driverless deployments are targeted for 2026.

BMW 

BMW new 7 Series received the world’s first approval for a combination Level 2/Level 3 driving assistance systems in the same vehicle. This milestone offers drivers unique benefits from both systems.
The Level 2 BMW Highway Assistant enhances comfort on long journeys, operating at speeds up to 81 mph (130 km/h) on motorways with separated carriageways. It allows drivers to take their hands off the steering wheel for extended periods while remaining attentive. The system can also perform lane changes autonomously or at the driver's confirmation.

The Level 3 BMW Personal Pilot L3 enables highly automated driving at speeds up to 37 mph (60 km/h) in specific conditions, such as motorway traffic jams. Drivers can temporarily divert their attention from the road, but they have to retake control when prompted.

This combination of systems offers a comprehensive set of functionalities for a more comfortable and relaxing driving experience on both long and short journeys. The BMW Personal Pilot L3, which includes both systems, is available exclusively in Germany for €6,000 (around $6,500). Current BMW owners can add the L2 Highway Assistant to their vehicle, if applicable, free of charge starting August 24.

Mercedes-Benz 

Mercedes-Benz’s groundbreaking Drive Pilot Level 3 autonomous driving system is available for the S-Class and EQS Sedan. It allows drivers to disengage from driving in specific conditions, such as heavy traffic under 40 mph (64 km/h) on approved freeways under certain circumstances. The system uses advanced sensors – including radar, lidar, ultrasound, and cameras – to navigate and make decisions.
While active, Drive Pilot enables drivers to use in-car entertainment features on the central display. However, drivers must remain alert and take control when requested. Drive Pilot functions under the following conditions:

•  Clear lane markings on approved freeways
•  Moderate to heavy traffic with speeds under 40 mph
•  Daytime lighting and clear weather
•  Driver visible by camera located above driver's display
•  The car is not in a construction zone.

Drive Pilot relies on a high-definition 3D map of the road and surroundings. It's currently certified for use on major freeways in California and parts of Nevada.

NPS

At CES 2024, Neural Propulsion Systems (NPS) demonstrated its ultra-resolution imaging radar software for automotive vision sensing. The technology significantly improves radar precision without expensive lidar sensors or weather-related limitations.

NPS CEO Behrooz Rezvani likens the improvement to enhancing automotive imaging from 20/20 to better than 20/10 vision. The software enables existing sensors to resolve to one-third of the radar beam-width, creating a 10 times denser point cloud and reducing false positives by over ten times, the company said.

The demonstration compared performance using Texas Instruments 77 GHz chipsets with and without NPS technology. Former GM R&D vice president and Waymo advisor Lawrence Burns noted that automakers can use NPS to enhance safety, performance, and cost-effectiveness of driver-assistance features using existing hardware.

NPS' algorithms are based on the Atomic Norm framework, rooted in magnetic resonance imaging technology. The software can be deployed on various sensing platforms and implemented on processors with neural network capability. Advanced applications of NPS software with wide aperture multi-band radar enable seeing through physical barriers like shrubs, trees, and buildings — and even around corners. The technology is poised to help automakers meet NHTSA's proposed stricter standards for automatic emergency braking, aiming to reduce pedestrian and bicycle fatalities on U.S. roads.

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Link: https://www.admin.ch/gov/en/start/documentation/media-releases.msg-id-101189.html

Dübendorf, St. Gallen und Thun, 28.05.2024 - Capturing three times more light: Empa and ETH researchers are developing an image sensor made of perovskite that could deliver true-color photos even in poor lighting conditions. Unlike conventional image sensors, where the pixels for red, green and blue lie next to each other in a grid, perovskite pixels can be stacked thus greatly increasing the amount of light each individual pixel can capture.

Family, friends, vacations, pets: Today, we take photos of everything that comes in front of our lens. Digital photography, whether with a cell phone or camera, is simple and hence widespread. Every year, the latest devices promise an even better image sensor with even more megapixels. The most common type of sensor is based on silicon, which is divided into individual pixels for red, green and blue (RGB) light using special filters. However, this is not the only way to make a digital image sensor – and possibly not even the best.

A consortium comprising Maksym Kovalenko from Empa's Thin Films and Photovoltaics laboratory, Ivan Shorubalko from Empa's Transport at Nanoscale Interfaces laboratory, as well as ETH Zurich researchers Taekwang Jang and Sergii Yakunin, is working on an image sensor made of perovskite capable of capturing considerably more light than its silicon counterpart. In a silicon image sensor, the RGB pixels are arranged next to each other in a grid. Each pixel only captures around one-third of the light that reaches it. The remaining two-thirds are blocked by the color filter.
Pixels made of lead halide perovskites do not need an additional filter: it is already "built into" the material, so to speak. Empa and ETH researchers have succeeded in producing lead halide perovskites in such a way that they only absorb the light of a certain wavelength – and therefore color – but are transparent to the other wavelengths. This means that the pixels for red, green and blue can be stacked on top of each other instead of being arranged next to each other. The resulting pixel can absorb the entire wavelength spectrum of visible light. "A perovskite sensor could therefore capture three times as much light per area as a conventional silicon sensor," explains Empa researcher Shorubalko. Moreover, perovskite converts a larger proportion of the absorbed light into an electrical signal, which makes the image sensor even more efficient.

Kovalenko's team was first able to fabricate individual functioning stacked perovskite pixels in 2017. To make the next step towards real image sensors, the ETH-Empa consortium led by Kovalenko had partnered with the electronics industry. "The challenges to address include finding new materials fabrication and patterning processes, as well as design and implementation of the perovskite-compatible read-out electronic architectures", emphasizes Kovalenko. The researchers are now working on miniaturizing the pixels, which were originally up to five millimeters in size, and assembling them into a functioning image sensor. "In the laboratory, we don't produce the large sensors with several megapixels that are used in cameras," explains Shorubalko, "but with a sensor size of around 100'000 pixels, we can already show that the technology works."

Good performance with less energy
Another advantage of perovskite-based image sensors is their manufacture. Unlike other semiconductors, perovskites are less sensitive to material defects and can therefore be fabricated relatively easily, for example by depositing them from a solution onto the carrier material. Conventional image sensors, on the other hand, require high-purity monocrystalline silicon, which is produced in a slow process at almost 1500 degrees Celsius.

The advantages of perovskite-based image sensors are apparent. It is therefore not surprising that the research project also includes a partnership with industry. The challenge lies in the stability of perovskite, which is more sensitive to environmental influences than silicon. "Standard processes would destroy the material," says Shorubalko. "So we are developing new processes in which the perovskite remains stable. And our partner groups at ETH Zurich are working on ensuring the stability of the image sensor during operation."

If the project, which will run until the end of 2025, is successful, the technology will be ready for transfer to industry. Shorubalko is confident that the promise of a better image sensor will attract cell phone manufacturers. "Many people today choose their smartphone based on the camera quality because they no longer have a stand-alone camera," says the researcher. A sensor delivering excellent images in much poorer lighting conditions could be a major advantage.

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Sony held a strategy meeting recently. Slides from the Imaging and Sensing business are available here: https://www.sony.com/en/SonyInfo/IR/library/presen/business_segment_meeting/pdf/2024/ISS_E.pdf

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Sony UV and SWIR sensors demo:

Webinar by ON Semi on image sensor selection:

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The 10 µm, 1280 x 1024 Neon® RD0131 DROIC is available now for commercial use.

• 10 μm , P-on-N polarity, CTIA input
• Global snapshot, Integrate-while-read (IWR) operation
• Three selectable gains with well capacity of 22 ke- (high-
• gain), 160 ke- (medium-gain) and 1.1 Me- (low-gain)
• Correlated Doubling Sampling (CDS) on and off chip
• Advanced zero-signal noise floors of 15 e– rms (high-gain
• using CDS, room temperature)
• Synchronous or asynchronous integration control
• High-speed windowing with multiple windows
• Serialized to 16 bits per pixel (15 data, 1 valid flag bit)
• SPI control interface (SenSPI®) and optional frame clock

 

 

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Slides available here: https://www.project-mantis.eu/presentations_2023/ePicture_2023_AMSOSRAM_20230608121413.pdf

A subset of slides below:

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FIRST CALL FOR PAPERS
ABSTRACTS DUE DEC 19, 2024
2025 International Image Sensor Workshop Awaji Yumebutai Int. Conf. Center, Hyōgo, Japan
(June 2 - 5, 2025)

The 2025 International Image Sensor Workshop (IISW) provides a biennial opportunity to present innovative work in the area of solid-state image sensors and share new results with the image sensor community. The event is intended for image sensor technologists; in order to encourage attendee interaction and a shared experience, attendance is limited, with strong acceptance preference given to workshop presenters. As is the tradition, the 2025 workshop will emphasize an open exchange of information among participants in an informal, secluded setting beside the Awaji Island in Hyōgo, Japan.

The scope of the workshop includes all aspects of electronic image sensor design and development. In addition to regular oral and poster papers, the workshop will include invited talks and announcement of International Image Sensors Society (IISS) Award winners.

Papers on the following topics are solicited:

Image Sensor Design and Performance
CMOS imagers, CCD imagers, SPAD sensors
New and disruptive architectures
Global shutter image sensors
Low noise readout circuitry, ADC designs
Single photon sensitivity sensors
High frame rate image sensors
High dynamic range sensors
Low voltage and low power imagers
High image quality; Low noise; High sensitivity
Improved color reproduction
Non-standard color patterns with special digital processing
Imaging system-on-a-chip, on-chip image processing
Event-based image sensors

Pixels and Image Sensor Device Physics
New devices and pixel structures
Advanced materials
Ultra miniaturized pixels development, testing, and characterization
New device physics and phenomena
Electron multiplication pixels and imagers
Techniques for increasing QE, well capacity, reducing crosstalk, and improving angular response
Frontside illuminated, backside illuminated, and stacked pixels and pixel arrays
Pixel simulation: optical and electrical simulation, 2D and 3D, CAD for design and simulation, improved models

Application Specific Imagers
Image sensors and pixels for range sensing: LIDAR, TOF, RGBZ, structured light, stereo imaging, etc.
Image sensors with enhanced spectral sensitivity (NIR, UV, IR)
Sensors for DSC, DSLR, mobile, digital video cameras and mirror-less cameras
Array imagers and sensors for multi-aperture imaging, computational imaging, and machine learning
Sensors for medical applications, microbiology, genome sequencing
High energy photon and particle sensors (X-ray, radiation)
Line arrays, TDI, very large format imagers
Multi and hyperspectral imagers
Polarization sensitive imagers

Image Sensor Manufacturing and Testing
New manufacturing techniques
Wafer-on-wafer and chip-on-wafer stacking technologies
Backside thinning
New characterization methods
Packaging and testing: reliability, yield, cost
Defects, noises, and leakage currents
Radiation damage and radiation hard imagers

On-chip Optics and Color Filters
Advanced optical path, color filters, microlens, light guides
Nanotechnologies for Imaging
Wafer level cameras

Submission of abstracts:

An abstract should consist of a single page of maximum 500-words text with up to two pages of illustrations (3 pages maximum), and include authors’ name(s), affiliation, mailing address, telephone number, and e-mail address.

The deadline for abstract submission is 11:59pm, Thursday Dec 19, 2024 (GMT).
To submit an abstract, please go to: https://cmt3.research.microsoft.com/IISW2025
Above website should be open by Aug 1, 2024.

The first time you visit the paper submission site, you'll need to click on "Create Account". Once you create and verify your account with your email address, you will be able to submit abstracts by logging in and clicking “Create New Submission”.

Please visit https://imagesensors.org/CFP2025 for complete instructions and any updates to the abstract and paper submission procedures.

Abstracts will be considered on the basis of originality and quality. High quality papers on work in progress are also welcome. Abstracts will be reviewed confidentially by the Technical Program Committee.

Key Dates:
Authors will be notified of the acceptance of their abstract latest by Feb 10, 2025.
Final-form 4-page paper submission date is Mar 22, 2025.
Presentation material submission date is May 1, 2025.

Location:
The IISW 2025 will be held at the International Conference Center on Awaji Island in Hyōgo Prefecture, Japan. This beautiful hotel is about 1 hour from Kansai International Airport. Limousine Buses chartered by IISW will pick up attendees at JR Shin-Kobe Station and JR Sannomiya Station.

Registration, Workshop fee, and Hotel Reservation:
Registration details and hotel reservation information will be provided in the Final Announcement of the Workshop.

Forthcoming announcements and additional information will be posted on the 2025 Workshop page of the International Image Sensor Society website at: https://www.imagesensors.org/

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We shared back in 2015 news of Sony discontinuing their CCD sensors.

The "last time buy" period for these sensors is nearing the end.

Framos: https://www.framos.com/en/news/framos-announces-last-time-buy-deadline-for-sony-ccd-sensors

Taking into consideration current market demand and customer feedback, Sony has decided to revise the “Last Time Buy PO submission” deadline to the End of September 2024. Final shipments to FRAMOS remain unchanged at the end of March 2026. With these changes, FRAMOS invites all customers to submit their final Last Time Buy Purchase Orders to them no later than September 24th, 2024, to ensure timely processing and submission to Sony by the new Last Time Buy deadline date.
Important dates:
 Deadline for Last Time Buy Purchase Orders received by FRAMOS: September 24th, 2024
 Final delivery of accepted Last Time Buy Purchase Orders from FRAMOS: March 31st, 2026 

SVS-Vistek: https://www.svs-vistek.com/en/news/svs-news-article.php?p=svs-vistek-offers-last-time-buy-options-or-replacement-products-for-ccd-cameras

For customers who wish to continue using CCD-based designs, SVS-Vistek has initiated a Last-Time-Buy (LTB) period, effective immediately, followed by a subsequent Last-Time-Delivery (LTD) period. This allows our customers to continue to produce and sell their CCD-based products, ensuring reliable delivery. Orders can be placed until August 31, 2024 (Last-Time-Buy). SVS-Vistek will then offer delivery of LTB cameras until August 31, 2026 (Last-Time-Delivery). We advise our customers individually and try to find the best solution together. 

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Link: https://www.forbes.com/sites/davidhambling/2024/05/22/new-us-technology-makes-more--powerful-thermal-imagers-at-lower-cost/

[some excerpts below]

New U.S. Technology Makes More Powerful Thermal Imagers At Lower Cost 

Thermal imaging has been a critical technology in the war in Ukraine, spotting warm targets like vehicles and soldiers in the darkest nights. Military-grade thermal imagers used on big Baba Yaga night bombers are far too expensive for drone makers assembling $400 FPV kamikaze drones who have to rely on lower-cost devices. But a new technology developed by U.S company Obsidian Sensors Inc could transform the thermal imaging market with affordable high-resolution sensors.

...

Older digital cameras were based on CCDs (charge coupled devices), the current generation use more affordable CMOS imaging sensors which produce an electrical charge in response to light. The vast majority of thermal imagers use a different technology: an array of microbolometers, miniature devices whose pixels absorb infrared energy and measure the resulting change in resistance. The conventional design neatly integrates the microbolometers and the circuits which read them on the same silicon chip.

...

John Hong, CEO of Obsidian Sensors based in San Diego believes he has a better approach, which can scale up to high resolution at low cost and, crucially, high volume, at established foundries. The new design does not integrate everything in one unit but separates the bolometer array from the readout circuits. This is more complex but allows a different manufacturing technique to be used.

The readout circuits are still on silicon, but the sensor array is produced on a sheet of glass, leveraging technology perfected for flat-screen TVs and mobile phone displays. Large sheets of glass are far cheaper to process than small wafers of silicon and bolometers made on glass cost about a hundred times less than on silicon.

Hong says the process can easily produce multi-megapixel arrays. Obsidian are already producing test batches of VGA sensors, and plan to move to 1280x1024 this year and 1920x1080 in 2025.
Obsidian has been quietly developing their technology for six years and are now able to produce units for evaluation at a price three to four times lower than comparable models. Further evolution of the manufacturing process will bring prices even lower.

That could bring a 640x480 VGA sensor imager down to well below $200.

...

Hong says they plan to sell a thousand VGA cameras this year on a pilot production run, and are currently raising a series B to hit much larger volumes in 2025 and beyond. That should be just about right to surf the wave of demand in the next few years.

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Diffractive blur and low light levels are two fundamental challenges in producing high-quality photographs in under-display cameras (UDCs). In this paper, we incorporate phase masks on display panels to tackle both challenges. Our design inserts two phase masks, specifically two microlens arrays, in front of and behind a display panel. The first phase mask concentrates light on the locations where the display is transparent so that more light passes through the display, and the second phase mask reverts the effect of the first phase mask. We further optimize the folding height of each microlens to improve the quality of PSFs and suppress chromatic aberration. We evaluate our design using a physically-accurate simulator based on Fourier optics. The proposed design is able to double the light throughput while improving the invertibility of the PSFs. Lastly, we discuss the effect of our design on the display quality and show that implementation with polarization-dependent phase masks can leave the display quality uncompromised.

We consider the problem of imaging a dynamic scene over an extreme range of timescales simultaneously—seconds to picoseconds—and doing so passively, without much light, and without any timing signals from the light source(s) emitting it. Because existing flux estimation techniques for single-photon cameras break down in this regime, we develop a flux probing theory that draws insights from stochastic calculus to enable reconstruction of a pixel’s time-varying flux from a stream of monotonically-increasing photon detection timestamps. We use this theory to (1) show that passive free-running SPAD cameras have an attainable frequency bandwidth that spans the entire DC-to-31 GHz range in low-flux conditions, (2) derive a novel Fourier-domain flux reconstruction algorithm that scans this range for frequencies with statistically-significant support in the timestamp data, and (3) ensure the algorithm’s noise model remains valid even for very low photon counts or non-negligible dead times. We show the potential of this asynchronous imaging regime by experimentally demonstrating several never-seen-before abilities: (1) imaging a scene illuminated simultaneously by sources operating at vastly different speeds without synchronization (bulbs, projectors, multiple pulsed lasers), (2) passive non-line-of-sight video acquisition, and (3) recording ultra-wideband video, which can be played back later at 30 Hz to show everyday motions—but can also be played a billion times slower to show the propagation of light itself.

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon-cubes represent the spatio-temporal detections of photons as a sequence of binary frames, at frame-rates as high as 100 kHz. We show that simple transformations of the photon-cube, or photon-cube projections, provide the functionality of numerous imaging systems including: exposure bracketing, flutter shutter cameras, video compressive systems, event cameras, and even cameras that move during exposure. Our photon-cube projections offer the flexibility of being software-defined constructs that are only limited by what is computable, and shot-noise. We exploit this flexibility to provide new capabilities for the emulated cameras. As an added benefit, our projections provide camera-dependent compression of photon-cubes, which we demonstrate using an implementation of our projections on a novel compute architecture that is designed for single-photon imaging.

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Full article here: https://petapixel.com/2024/06/27/samsung-announces-worlds-first-200mp-sensor-for-telephoto-cameras/

Samsung Unveils World’s First 200MP Sensor for Smartphone Telephoto Cameras

The ISOCELL HP9, the industry’s first 200MP telephoto sensor for smartphones, features a Type 1/1.4 format and 0.56μm pixel size. Samsung explains that the sensor has a proprietary high-refractive microlens that uses a novel material and significantly improves the sensor’s light-gathering capabilities. This works by more precisely directing light to the corresponding RGB color filter. Samsung claims this results in 12% better light sensitivity (based on signal-to-noise ratio 10) and 10% improved autofocus contrast performance compared to Samsung’s prior telephoto sensor. 

“Notably, the HP9 excels in low-light conditions, addressing a common challenge for traditional telephoto cameras. Its Tetra²pixel technology merges 16 pixels (4×4) into a large, 12MP 2.24μm-sized sensor, enabling sharper portrait shots — even in dark settings — and creating dramatic out-of-focus bokeh effects,” the Korean tech giant explains.

When used alongside a new remosaic algorithm, Samsung says its new HP9 sensor offers 2x or 4x in-sensor zoom modes, achieving up to 12x total zoom when paired with a 3x optical zoom telephoto module, “all while maintaining crisp image quality.”

Next is the ISOCELL GNJ, a dual-pixel 50-megapixel image sensor in Type 1/1.57 format. This sensor sports 1.0μm pixels, and each pixel includes a pair of photodiodes, enabling “fast and accurate autofocus, similar to the way human eyes focus.” The sensor also captures complete color information, which Samsung says helps with focusing and image quality.

The sensor utilizes an in-sensor zoom function, which promises good video quality. It also offers benefits for still photography, as Samsung says the in-sensor zoom function can reduce artifacts and moiré.

Thanks to an improved high-transmittance anti-reflective layer (ARL), plus Samsung’s high-refractive microlenses, the GNJ boasts better light transmission and promises consistent image quality. It also has an upgraded pixel isolation material to minimize the crosstalk between adjacent pixels, resulting in more detailed, accurate photos.

As Samsung notes, these improvements also result in a more power-efficient design. The sensor offers a 29% improvement in live view power efficiency and a 34% reduction in power use when shooting 4K/60p video.

Rounding out the three new sensors is the ISOCELL JN5, a 50-megapixel Type 1/2.76 sensor with 0.64μm pixels. Because of its slim optical format, the new JN5 sensor can be used across primary and sub-cameras, including ultra-wide, wide, telephoto, and front-facing camera units.

The sensor includes dual vertical transfer gate (Dual VTG) technology to increase charge transfer within pixels, which reduces noise in extremely low-light conditions. It also leverages Super Quad Phase Detection (Super QPD) to rapidly adjust focus when capturing moving subjects.

Yet another fancifully named feature is dual slope gain (DSG), which Samsung says enhances the JN5’s high-dynamic range (HDR) performance. This works by amplifying analog signals (photons) into two signals, converting them into digital data, and combining them. This sounds similar to dual ISO technology, which expands dynamic range by combining low-gain and high-gain data into a single file.

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