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In an ArXiV preprint titled "Multi-Length-Scale Dopants Analysis of an Image Sensor via Focused Ion Beam-Secondary Ion Mass Spectrometry and Atom Probe Tomography", Guerguis et al write:

The following article presents a multi-length-scale characterization approach for investigating doping chemistry and spatial distributions within semiconductors, as demonstrated using a state-of-the-art CMOS image sensor. With an intricate structural layout and varying doping types/concentration levels, this device is representative of the current challenges faced in measuring dopants within confined volumes using conventional techniques. Focused ion beam-secondary ion mass spectrometry is applied to produce large-
area compositional maps with a sub-20 nm resolution, while atom probe tomography is used to extract atomic-scale quantitative dopant profiles. Leveraging the complementary capabilities of the two methods, this workflow is shown to be an effective approach for resolving nano- and micro- scale dopant information, crucial for optimizing the performance and reliability of advanced semiconductor devices.

Preprint: https://arxiv.org/pdf/2501.08980 

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In an ArXiV preprint titled "Multi-Length-Scale Dopants Analysis of an Image Sensor via Focused Ion Beam-Secondary Ion Mass Spectrometry and Atom Probe Tomography", Guerguis et al write:

The following article presents a multi-length-scale characterization approach for investigating doping chemistry and spatial distributions within semiconductors, as demonstrated using a state-of-the-art CMOS image sensor. With an intricate structural layout and varying doping types/concentration levels, this device is representative of the current challenges faced in measuring dopants within confined volumes using conventional techniques. Focused ion beam-secondary ion mass spectrometry is applied to produce large-
area compositional maps with a sub-20 nm resolution, while atom probe tomography is used to extract atomic-scale quantitative dopant profiles. Leveraging the complementary capabilities of the two methods, this workflow is shown to be an effective approach for resolving nano- and micro- scale dopant information, crucial for optimizing the performance and reliability of advanced semiconductor devices.

Preprint: https://arxiv.org/pdf/2501.08980 

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 The Fundamentals of CMOS Image Sensors with Richard Crisp 

This video provides a sneak peek of "CMOS Image Sensors: Technology, Applications, and Camera Design Methodology," an SPIE course taught by imaging systems expert Richard Crisp. The course covers everything from the basics of photon capture to sensor architecture and real-world system implementation.
The preview highlights key differences between CCD and CMOS image sensors, delves into common sensor architectures such as rolling shutter and global shutter, and explains the distinction between frontside and backside illumination.
It also introduces the primary noise sources in image sensors and how they can be managed through design and optimization techniques such as photon transfer analysis and MTF assessment.
You'll also see how the course approaches imaging system design using a top-down methodology. This includes considerations regarding pixel architecture, optics, frame rate, and data bandwidth, all demonstrated through practical examples, such as a networked video camera design.
Whether you're an engineer, scientist, or technical manager working with imaging systems, this course is designed to help you better understand the technology behind modern CMOS image sensors and how to make informed design choices. Enjoy!

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Guo et al. from Changchun Institute of Optics, University of Chinese Academy of Sciences, and Gpixel Inc. published a paper titled "Study on 3D Effects on Small Time Delay Integration Image Sensor Pixels" in Sensors.

Abstract: This paper demonstrates the impact of 3D effects on performance parameters in small-sized Time Delay Integration (TDI) image sensor pixels. In this paper, 2D and 3D simulation models of 3.5 μm × 3.5 μm small-sized TDI pixels were constructed, utilizing a three-phase pixel structure integrated with a lateral anti-blooming structure. The simulation experiments reveal the limitations of traditional 2D pixel simulation models by comparing the 2D and 3D structure simulation results. This research validates the influence of the 3D effects on the barrier height of the anti-blooming structure and the full well potential and proposes methods to optimize the full well potential and the operating voltage of the anti-blooming structure. To verify the simulation results, test chips with pixel sizes of 3.5 μm × 3.5 μm and 7.0 μm × 7.0 μm were designed and manufactured based on a 90 nm CCD-in-CMOS process. The measurement results of the test chips matched the simulation data closely and demonstrated excellent performance: the 3.5 μm × 3.5 μm pixel achieved a full well capacity of 9 ke- while maintaining a charge transfer efficiency of over 0.99998.

Paper link [open access]: https://www.mdpi.com/1424-8220/25/7/1953

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 SPAD and SPAD Arrays: Theory, Practice, and Applications

 

The video is a comprehensive webinar on Single Photon Avalanche Diodes (SPADs) and SPAD arrays, addressing their theory, applications, and recent advancements. It is led by experts from the New Jersey Institute of Technology and Hamamatsu, discussing technical fundamentals, challenges, and innovative solutions to improve the performance of SPAD devices. Key applications highlighted include fluorescence lifetime imaging, remote gas sensing, quantum key distribution, and 3D radiation detection, showcasing SPAD's unique ability to timestamp events and enhance photon detection efficiency.

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Recent speculative news article suggest that Samsung is weighing exiting CIS business after recent exit by SK Hynix.

News source: https://www.digitimes.com/news/a20250312PD213/cis-samsung-sk-hynix-business-lsi.html

SK Hynix is shutting down its CMOS image sensor (CIS) business, fueling industry speculation over whether Samsung Electronics will follow suit. Samsung's system LSI division, which oversees its CIS operations, is undergoing an operational diagnosis...

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In this keynote held at the 2024 International Conference on Computational Photography, Prof. Davide Scaramuzza from the University of Zurich presents a visionary keynote on event cameras, which are bio-inspired vision sensors that outperform conventional cameras with ultra-low latency, high dynamic range, and minimal power consumption. He dives into the motivation behind event-based cameras, explains how these sensors work, and explores their mathematical modeling and processing frameworks. He highlights cutting-edge applications across computer vision, robotics, autonomous vehicles, virtual reality, and mobile devices while also addressing the open challenges and future directions shaping this exciting field.
00:00 - Why event cameras matter to robotics and computer vision

07:24 - Bandwidth-latency tradeoff
08:24 - Working principle of the event camera
10:50 - Who sells event cameras
12:27 - Relation between event cameras and the biological eye
13:19 - Mathematical model of the event camera
15:35 - Image reconstruction from events
18:32 - A simple optical-flow algorithm
20:20 - How to process events in general
21:28 - 1st order approximation of the event generation model
23:56 - Application 1: Event-based feature tracking
25:03 - Application 2: Ultimate SLAM
26:30 - Application 3: Autonomous navigation in low light
27:38 - Application 4: Keeping drones fly when a rotor fails
31:06 - Contrast maximization for event cameras
34:14 - Application 1: Video stabilization
35:16 - Application 2: Motion segmentation
36:32 - Application 3: Dodging dynamic objects
38:57 - Application 4: Catching dynamic objects
39:41 - Application 5: High-speed inspection at Boeing and Strata
41:33 - Combining events and RGB cameras and how to apply deep learning
45:18 - Application 1: Slow-motion video
48:34 - Application 2: Video deblurring
49:45 - Application 3: Advanced Driving Assistant Systems
56:34 - History and future of event cameras
58:42 - Reading material and Q&A

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From PetaPixel: https://petapixel.com/2025/04/15/sony-unveils-the-worlds-smallest-and-lightest-lidar-depth-sensor/

Sony announced the AS-DT1, the world’s smallest and lightest miniature precision LiDAR depth sensor.

Measuring a mere 29 by 29 by 31 millimeters (1.14 by 1.14 by 1.22 inches) excluding protrusions, the Sony AS-DT1 LiDAR Depth Sensor relies upon sophisticated miniaturization and optical lens technologies from Sony’s machine vision industrial cameras to accurately measure distance and range. The device utilizes “Direct Time of Flight” (dToF) LiDAR technology and features a Sony Single Photon Avalanche Diode (SPAD) image sensor. 

From the official Sony webpage: https://pro.sony/ue_US/products/lidar/as-dt1

• 1.14 (W) x 1.14 (H) x 1.22 in (D)
• 50 g (1.1 oz)
• Utilizes dToF LiDAR technology
• Single Photon Avalanche Diode (SPAD) sensor
• Range distance of 40 m (131 ft) indoor, 20 m (65.6 ft) outdoor
• Lightweight aluminum alloy housing structure
• 2 USB-C ports
• Connector for external power, UART interface and trigger

• HFoV 30° or more
• Maximum measurement range at 15 fps, 50 percent reflectivity, center: Indoor: 131.23 ft and Outdoor: 65.62 ft
• Measurement accuracy at 10 m: Indoor/Outdoor: ±0.2 in
• Distance resolution: 0.98 in
• Frame rate: 30 fps
• 15 fps @ Maximum ranging distance mode
• Number of ranging points 576（24 x 24）
• Laser wavelength 940 nm
• Dimensions 1.14 (W) x 1.14 (H) x 1.22 in (D) (excluding protrusions)
• Weight 1.1 oz or less

 

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Tripurari Singh, Image Algorithmics (US); Mritunjay Singh, Image Algorithmics presented a paper titled "RGBC-IR: A CFA for single exposure dark flash" at Electronic Imaging 2025.

Abstract: Modern RGB-IR cameras have evolved to capture accurate colors and NIR from a single sensor. While these cameras can employ their RGB images to effectively denoise IR, they contain too few IR pixels to do the reverse: denoise RGB with IR.Improving low light RGB with an IR illuminator is an important feature for upcoming automotive applications where cabins have to be kept dark at night so as not to distract the driver. Current solutions to this problem either discard the IR cut filter and take separate RGB and IR exposures and suffer from poor colors. Or employ a bulky beam splitter architecture with separate RGB and IR sensors.We propose a camera with a novel RGBC-IR color filter array containing clear pixels that are sensitive to both visible light and IR. Its RGB pixels feature an IR attenuating coating while its IR pixels contain a black filter that blocks visible light.Mulitspectral demosaicking techniques are used to reconstruct RGB and IR images, as well as a high SNR luminance image containing the Clear, RGB and IR signals. Fusion techniques developed for beam splitter RGB-IR cameras are used to denoise RGB and IR using the luminance.

 

 

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PARIS, France and OBERSULM, Germany – March 5, 2025 - IDS Imaging Development Systems GmbH,  market leader in industrial machine vision, and Prophesee SA, inventor of the most advanced neuromorphic vision systems, today announced that IDS’ new uEye EVS camera line incorporates the high-speed, dynamic range and data efficiency of the Prophesee-Sony IMX636HD event-based vision sensor to offer new capabilities for industrial machine vision applications.

The result of extensive collaboration between the two companies, the solution features Prophesee’s proven neuromorphic approach to capturing fast-moving objects with significantly less data processing, power and blur than traditional frame-based methods. With these capabilities, the uEye EVS camera is the ideal solution for applications that require real-time machine vision processing at very high speed, such as optical monitoring of vibrations or high-speed motion analysis.

The camera benefits from Prophesee’s event-based vision’s ability to capture only relevant events in a scene. In contrast to conventional image sensors, it does not capture every image completely at regular intervals (frames) but only reacts to changes within a scene. It transmits events depending on when and where the brightness in its field of view changes - for each individual sensor pixel. The temporal resolution, i.e. the minimum measurable time difference between two successive changes in brightness, can be less than 100 microseconds.

The sensor is supported by Metavision SDK, a seamlessly integrated suite of software tools and models, APIs, and other training and development resources from Prophesee for efficient evaluation, visualization, and customization.

"This partnership combines our mutual areas of expertise to realize the benefits of event-based vision, including remarkable temporal resolution which make the cameras optimised for analysing highly dynamic scenes. It enables best conditions for capturing fast object movements without loss of information, comparable to an image-based frame rate of more than 10,000 images per second," explains Patrick Schick, Product Owner 3D & Vision Software. “At the same time, the sensor ignores all motionless areas of its field of view and thus generates 10 to 1000 times less data than image-based variants. This saves memory and computing time.”

“IDS cameras are well known to address the toughest machine vision use cases and with the incorporation of Prophesee event-based vision technologies, it strengthens its offering to provide far more performance, power efficiency and accuracy, even in the most challenging conditions,” says Luca Verre, CEO and co-founder of Prophesee. “We are excited to see how the efforts of this tight collaboration have resulted in the new uEye EVS camera which leverages the potential of our sensors and development environment to deliver new value to its customers.”

About IDS Imaging Development Systems GmbH:
IDS Imaging Development Systems GmbH is a leading manufacturer of industrial cameras and pioneer in industrial image processing. The owner-managed, environmentally certified company develops high-performance and versatile 2D and 3D cameras as well as models with artificial intelligence (AI) or with streaming/event recording feature. The almost unlimited range of applications covers multiple non-industrial and industrial sectors of equipment, plant and mechanical engineering.
Since its foundation in 1997 as a two-man company, IDS has developed into an independent, ISO and environmental-friendly certified family business with around 320 employees. The headquarters in Obersulm, Germany, is both a development and production site. With subsidiaries in the USA, Japan, South Korea and the UK, as well as further representative offices in France, Benelux and India, the technology company has a global presence.

About Prophesee
Prophesee is the inventor of the world’s most advanced neuromorphic vision systems. Prophesee’s patented sensors and AI algorithms, introduce a new computer vision paradigm based on how the human eye and brain work. Like the human vision, it sees events: essential, motion information in the scene, not a succession of conventional images. This breakthrough method allows for unprecedented speed (>10 000fps time resolution equivalent), dynamic range (>120dB), data volume (10x to 1000x less) and power efficiency (<10 mW). Prophesee bio-inspired revolution opens a new path to absolute efficiency and safety in autonomous driving, IoT and Industry 4.0. Prophesee reveals the invisible.   For more information, please visit www.prophesee.ai.

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Various news agencies reporting that SK hynix is exiting the CIS business to focus on AI.

https://www.trendforce.com/news/2025/03/06/news-sk-hynix-reportedly-exits-cis-to-focus-on-ai-memory-amid-weak-demand-and-fierce-china-competition/

Amid the AI-driven HBM boom, SK hynix is exiting its non-core CMOS image sensor (CIS) business, according to ZDNet and Edaily.

The ZDNet report suggests that SK hynix used to supply CMOS sensors for Samsung’s Galaxy Z3 and Chinese smartphones, but struggled to expand due to weak market demand and rising competition from Chinese newcomers.

According to SK hynix, its CIS division, launched in 2007, gained expertise in logic semiconductors beyond memory. However, the company decided to shift resources from CIS to AI memory to strengthen its AI-focused strategy, as per ZDNet.

Another report from fnews notes that SK hynix entered the image sensor market in 2008 by acquiring Silicon File. In 2019, it established a CIS R&D center in Japan and launched the “Black Pearl” sensor brand.

However, while trailing behind Sony and Samsung on the CIS business, SK hynix has been gradually downsizing the division, according to Edaily.

In late 2024, the company placed its CIS development team under the Future Technology Research Institute amid ongoing discussions about the business’s declining profitability, the Edaily report indicates.

https://www.thelec.net/news/articleView.html?idxno=5177 

SK Hynix is existing the CMOS image sensor (CIS) business, TheElec has learned.

The company will instead focus fully on AI memory products. Those working at its CIS business unit will be transferred to teams working on high-bandwidth memory (HBM).

In a recent internal communication event with employees, SK Hynix said the AI era has come and that the company has achieved “great results” in the AI memory sector.

The company was in the middle of a “great transition” to become a core AI company, SK Hynix told employees.

Technology and expertise that its CIS business unit will be crucial in solidifying its position as a global AI company, SK Hynix added.

SK Hynix started its CIS business in 2007 and since then attempted to expand its market share in the mobile market. But the unit continued to mark low profitability and its existence was always questioned.

In its year’s end reshuffle lats year, the business unit was moved to be under the supervision of the Future Technology Lab. These teams are more research oriented than teams under the supervision of the CEO.
SK Hynix CEO Kwak Noh-jung was also known to be strongly in favor of continuing the CIS business unit prior to the exit.

The company, during the vent, also said it plans to become a full stack AI memory provider.

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ICCP is the premier annual conference on computational imaging. The conference brings together researchers with interests broadly related to advancing computational imaging, from theory to systems to applications, including sensors, optics, algorithms, machine intelligence, vision science and perception.
ICCP 2025 will be an in-person event at the University of Toronto in Toronto, Canada, from July 21 – 23, 2025.

ICCP 2025 seeks novel and high-quality submissions in all areas of computational imaging—from theory to systems to applications, including sensors, optics, algorithms, machine intelligence, vision science, and perception—as well as the following topics of interest.

•  High-performance imaging
•  Computational cameras, illumination, and displays
•  Advanced image and video processing
•  Integration of imaging, physics, and machine learning
•  Organizing and exploiting photo/video collections
•  Structured light and time-of-flight imaging
•  Appearance, shape, and illumination capture
•  Computational optics (wavefront coding, digital holography, compressive sensing, etc.)
•  Sensor and illumination hardware
•  Imaging models and limits
•  Physics-based rendering, neural rendering, and differentiable rendering
•  Applications: imaging on mobile platforms, scientific imaging, medicine and biology, user interfaces, AR/VR systems

Two Integrated Paper Tracks
As in previous years, ICCP is coordinating with the IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) for a special issue on Computational Photography to be published after the conference. All submissions to ICCP will undergo a common review process and be judged for acceptance to either:

1.  The PAMI special issue: for papers that describe entirely novel work (i.e., not extensions of published conference papers) and are also of archival quality with comprehensive evaluation and analysis.
2.  The ICCP Proceedings: for papers that meet traditional conference criteria for quality and novelty but do not meet the criteria for (1) above.

Reviewing will be double-blind, and authors will be allowed a rebuttal after initial reviews. After review, the program chairs will inform the authors of accepted papers whether their paper has been selected for the special issue or the conference proceedings (see the Review and Decision Process section below for further details). Both sets of accepted papers will be presented as talks at the conference.

Please visit this page for more details and submission link: https://iccp2025.iccp-conference.org/#callforpapers

Paper submission deadline (firm, no extensions)     April 9, 2025 at 2359h Pacific Time.

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The Future of Image Sensors, John McCarten

John McCarten presented a talk as part of the Society for Imaging Science and Technology (IS&T) Rochester NY chapter seminar series on 22 Jan. 2025.

John McCarten studied Physics at Cornell University and currently works for L3Harris. Since 2001, John’s focus has been on image sensors and cameras. He has worked with semiconductor foundries on four continents. He has over 30 patents and has been the technical lead on development projects that have brought in over a billion dollars in sales.

00:00 - Introduction
00:45 - Future of Image Sensors
50:22 - Discussion

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New! IISW25 Technical Program (preliminary): Link

Venue: Awaji Yumebutai Int. Conf. Center, Hyogo, Japan.
Date: 2–5 June, 2025
 
New! Pre-registration information: Link

Authors can find the Paper Numbers or Poster Numbers in the Program to complete the required pre-registration.

After collecting all the camera-ready files, the final Program with timetables will be posted here.

New! IISW25 Right to Publish Form: Link

Authors need to download, sign, print to PDF, and submit it along with the camera-ready 4-page paper by 03/22/25.

Submit files to the same CMT site where you submitted the abstracts : https://cmt3.research.microsoft.com/IISW2025
 
 
General Workshop Co-Chairs
Yusuke Oike – Sony (Japan)
Shoji Kawahito – Shizuoka University and SUiCTE
Technical Program Chairs
Calvin Chao – TSMC
Rihito Kuroda – Tohoku University
IISS Board of Directors
Calvin Chao – TSMC
Boyd Fowler – OmniVision
Robert Henderson – The University of Edinburgh
Vladimir Koifman – Analog Value
Rihito Kuroda – Tohoku University
Guy Meynants – Photolitics
Junichi Nakamura – Brillnics
Shouleh Niksad – Jet Propulsion Lab.
Yusuke Oike – Sony (Japan)
Johannes Solhusvik – Sony (Norway)
Daniel Van Blerkom – Forza Silicon-Ametek
Yibing Michelle Wang – Samsung Semiconductor

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Discover TriEye's high-performance SWIR-based machine vision solutions, designed to enhance visibility and accuracy across various applications. This webinar explores the unique capabilities of SWIR (Short-Wave Infrared) technology and its impact on machine vision systems.

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A recent article in IEEE Spectrum discusses three approaches to improve color throughput in low-light settings: nano-prisms, light pillars, and color splitters.

Link: https://spectrum.ieee.org/smartphone-camera-sensors-next-gen/nano-light-pillars-bring-low-light-images-into-focus

 

Using color splitters, an image sensor can increase its overall sensitivity by having light appropriate to each sensor channeled directly to it. (imec)

“Nano-pillars” are a light channeling form of a metasurface that, a little like Imec's color splitter, also direct specific wavelengths of light to the detector pixels best suited to receive the light. (VisEra Technologies)

Samsung's new nano-prism image has a sensitivity to light sources at more oblique angles compared to some conventional pixel tech today. (Samsung)

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TLDR; Register as soon as possible starting February 17, as the number of attendees is limited! 

IISW 2025 Announcement of Pre-registration
 
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 on the Awaji Island in Hyōgo, Japan.
 
The pre-registration, along with the workshop program, will be open from February 17th, 2025. Details about pre-registration have been made available in advance at:
 
https://imagesensors.org/2025-international-image-sensor-workshop/
 
Priority seating will be given to presenters of accepted papers, resulting in a limited number of seats available for other attendees. Registration will generally be on a first-come, first-served basis. However, in line with the workshop’s commitment to fostering diverse and lively discussions, the organizers reserve the right to adjust allocations to ensure a balanced representation of affiliations.

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Link: https://thinklucid.com/tech-briefs/triton2-evs-explained-optimizing-event-based-imaging/

Lucid Vision Labs has published an in-depth article on their analysis of the bias and threshold features of Sony's IMX636 and IMX637 event-based sensors. The report goes into details on how the sensor can be controlled so that users can tweak and tune the event based data.

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Link: https://www.vision-systems.com/cameras-accessories/image-sensors/article/55264400/gpixel-launches-new-large-format-image-sensor

Gpixel Launches New Large Format Image Sensor

Sensor especially designed for physical science, astronomy vision applications.

Gpixel has launched a new large format monochrome CMOS image sensor, the GSENSE1517BSI. This backside illuminated sensor has 4116 x 4100, 16.8 MPixel resolution with 15 x 15 µm pixel size, 61.74 x 61.5 imaging area, and 4 fps frame rate. It has 92% peak QE and minimum read noise of 1.2e. It has both dual gain HDR and 14-bit ADC, which enables a wide variety of imaging modes. It can achieve up to 95.3db dynamic range. It has an operating temperature range of -60°C to 50° C.

This sensor is especially designed for scientific applications such astronomy related vision tasks, including space situational awareness, and orbital object tracking.

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ST's Ultra Low Power Image Sensor VD55G1

 

LYNRED Eyesential SW, VGA 10 µm pitch SWIR imaging sensor, provides leading-edge performance in sensitivity, low noise and ease-of-use for machine vision, scientific imaging and spectroscopy, where delivering affordability is key

 

Teledyne/FLIR Webinar on Sony's 4th Gen Pregius

amsOSRAM TMF8806 single-zone dToF Sensors for high accuracy in ultra low power mode

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