Sony A1 II review
2029 forecast: Image sensors market will be worth $29.62B
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Link: https://www.novuslight.com/image-sensors-market-worth-29-62-billion-by-2029_N13346.html
The global image sensor market is expected to be valued at USD 20.66 billion in 2024 and is projected to reach USD 29.62 billion by 2029, growing at a CAGR of 7.5% from 2024–2029 according to a new report by MarketsandMarkets. Additions to existing applications in various industries and technological advancements in image sensor product offerings are key factors driving the expansion of the image sensor market. Restraints such as High Manufacturing costs hinder market growth. However, factors such as Integration with other technologies provide lucrative opportunities for market players in the coming years.
Area Scan image sensors by array type to hold the highest CAGR during the forecast period.
Area scan image sensors will have the highest CAGR in the image sensor market for years due to versatile applications in numerous industries. Since it captures images in a two-dimensional format, area scan image sensors find broad application in machine vision in manufacturing, quality assurance, and automated inspection systems. Growing demand for automation of processes in industries is an imperative factor driving this growth. Area scan sensors make high-speed image acquisition possible with good measurement accuracy, which are essential factors for maintaining product quality as well as operational efficiency. Improvements in the form of better resolution and sensitivity along with AI integration are also improving the performance of area scan image sensors. Their high-speed, real-time image processing capacity supports applications in the automotive, healthcare, and logistics sectors, where swift decision-making is important. The rise of smart factories and Industry 4.0 projects has increased the demand for area scan sensors, which are essential for automation and data analytics functions. With more and more industries embracing high-performance imaging solutions, the best position of area scan image sensors will be leading in growth rates and innovation in the market.
More than 16 MP by resolution to exhibit highest market share during the forecast period
Over the next few years, image sensors with more than 16 MP resolution will likely rule the market because they can fulfill the fast-growing demands of high-quality imaging in various applications. Manufacturers are increasingly incorporating higher-resolution sensors into smartphones, digital cameras, and professional equipment due to increasing consumer demands for superior image quality. These further fuels the demand for visually beautiful images and videos because of the proliferation of social media and digital content creation. Other areas include the automotive, healthcare, and security fields. For example, advanced driver-assistance systems (ADAS) in automobiles would require detailed imaging of the lane and pedestrians; these pixels need to be greater, hence the requirement of such sensors. Medical imaging devices need high-resolution imaging for the accurate diagnostics that are provided. Thus, the increased low-light sensitivity and higher readout speed will make the high-resolution sensor more attractive. As such, the image sensors market greater than 16 MP will significantly increase as it goes well with the industry trend.
Industrial sector to hold the highest CAGR during the forecast period
Industrial, the largest application segment for image sensors, is anticipated to have the highest CAGR in the image sensor market during the next couple of years due to the growing application of automation, robotics, and machine vision systems. Rising efficiency and precision needs among industries in the manufacturing process also create an enormous demand for advanced imaging technologies. Therefore, image sensors play a very important role in quality control; real-time inspection and monitoring products are possible to ensure compliance with stringent quality standards. The establishment of Industry 4.0, which involves a convergence of IoT devices and smart technologies in the manufacturing process, is another reason behind the demand for high-performance image sensors. The sensors are more capable of collecting more data, which are analyzed for predictive purposes to minimize downtime.
Furthermore, developing more applications in the autonomous vehicles, logistics, and warehousing area significantly contributes to the increase in the requirement for advanced imaging solutions. Industrial applications will transform with the use oftransform using sensor technologies like 3D imaging and AI-enhanced vision systems. The system could offer clearer operational efficiency.
Asia Pacific in the image sensor industry to exhibit the highest CAGR during the forecast period
This will be where the highest CAGR in image sensors over the next years will emerge, spurred by various strong drivers in the region. The area is also where leading electronic manufacturing bases reside, among other factors that include some strong economies globally, like China, Japan, South Korea, and Taiwan. Some investment in this area for their development in researching and making discoveries is accelerating image sensor innovation in these markets. This growth is driven by the increasing demand for consumer electronics, including good-quality camera smartphones and tablets, as consumers want better imaging. Asia Pacific also grows due to fast industrialization and urbanization; image sensors are adopted in many industries, including automotive, healthcare, and surveillance. The automotive segment is especially booming for ADAS, which uses highly quality image sensors that include safety features. Furthermore, government projects like smart city projects help encourage surveillance and monitoring solutions; consequently, the demand also rises in the image sensor market. Collectively, these factors position the Asia Pacific region for robust growth, making it a key player in the global image sensor landscape.
Key Players
The image sensor companies includes major Tier I and II players like Sony Corporation (Japan), Samsung. (South Korea), Omnivision (US), Semiconductor Components Industries, LLC (US) and STMicroelectronics (Switzerland), Panasonic Holdings Corporation (Japan), Canon Inc. (Japan), HAMAMATSU PHOTONICS KK. (Japan), Teledyne Technologies Incorporated. (US), SK HYNIX INC. (South Korea), Himax Technologies Inc. (Taiwan) and others. These players have a strong market presence in advanced packaging across various countries in North America, Europe, Asia Pacific, and the Rest of the World (RoW).
Canon SELPHY QX20 review
Single Photon Avalanche Diodes – Buyer’s Guide
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Photoniques magazine published an article titled "Single photon avalanches diodes" by Angelo Gulinatti (Politecnico di Milano).
Abstract: Twenty years ago the detection of single photons was little more than a scientific curiosity reserved to a few specialists. Today it is a flourishing field with an ecosystem that extends from university laboratories to large semiconductor manufacturers. This change of paradigm has been stimulated by the emergence of critical applications that rely on single photon detection, and by technical progresses in the detector field. The single photon avalanche diode has unquestionably played a major role in this process.
Full article [free access]: https://www.photoniques.com/articles/photon/pdf/2024/02/photon2024125p63.pdf
Figure 1: Fluorescence lifetime measured by time-correlated single-photon counting (TCSPC). The sample is excited by a pulsed laser and the delay between the excitation pulse and the emitted photon is measured by a precision clock. By repeating multiple times, it is possible to build a histogram of the delays that reproduces the shape of the optical signal.
Figure 3: By changing the operating conditions or the design parameters, it is possible to improve some
performance metrics at the expenses of others.
Conference List – February 2025
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Electronic Imaging (EI 2025) - 2-6 Feb 2025 - Burlingame, California - Website
MSS Detectors and Materials, and Passive Sensors Conference (clearance may be required) - 10-14 Feb 2025 - Orlando, Florida, USA - Website
IEEE International Solid-State Circuits Conference (ISSCC) - 16-20 Feb 2025 - San Francisco, California, USA - Website
SPIE Medical Imaging - 16-20 Feb 2025 - San Diego, California, USA - Website
innoLAE (Innovations in Large-Area Electronics) - 17-19 Feb 2025 - Cambridge, UK - Website
Wafer-Level Packaging Symposium - 18-20 Feb 2025 - San Francisco, California, USA - Website
Return to Conference List Index
IEDM 2024 Program is Live
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70th Annual IEEE International Electron Devices Meeting (IEDM) will be held December 7-11, 2024 in San Francisco California. Session #41 is on the topic of "Advanced Image Sensors":
https://iedm24.mapyourshow.com/8_0/sessions/session-details.cfm?scheduleid=58
Title: 41 | ODI | Advanced Image Sensors
Description:
This session includes 6 papers on latest image sensor technologies developments. To be noticed this year the multiple ways of stacking layer with new features. The first stack involves a dedicated AI image processing layer based on neural networks for a 50 Mpix sensor. The second one shows progress on small pixel noise with 2-layer pixel and additional intermediate interconnection. Third stack, very innovative with organic pixel on top of conventional Si based ITOF pixel for true single device RGB-Z sensor. All three papers are authored by Sony Semiconductors. InAs QD image sensors are also reported for the first time as a lead-free option for SWIR imaging by both IMEC and Sony Semiconductors Also progress in conventional IR global shutter with newly nitrated MIM capacitor and optimized DTI filling for crosstalk and QE improvement is presented by Samsung semiconductor.
Wednesday, December 11, 2024 - 01:35 PM
41-1 | A Novel 1/1.3-inch 50 Megapixel Three-wafer-stacked CMOS Image Sensor with DNN Circuit for Edge Processing
This study reports the first ever 3-wafer-stacked CMOS image sensor with DNN circuit. The sensor was fabricated using wafer-on-wafer-on-wafer process and DNN circuit was placed on the bottom wafer to ensure heat dissipation. This device can incorporate the HDR function and enlarge the pixel array area to remarkably improve image-recognition.
Wednesday, December 11, 2024 - 02:00 PM
41-2 | Low Dark Noise and 8.5k e− Full Well Capacity in a 2-Layer Transistor Stacked 0.8μm Dual Pixel CIS with Intermediate Poly-Si Wiring
This paper demonstrates a 2-layer transistor pixel stacked CMOS image sensor with the world’s smallest 0.8μm dual pixel. We improved the layout flexibility with intermediate poly-Si wiring technique. Our advanced 2-layer pixel device achieved low input-referred random noise of 1.3 e−rms and high full well capacity of 8.5k e−.
Wednesday, December 11, 2024 - 02:25 PM
41-3 | A High-Performance 2.2μm 1-Layer Pixel Global Shutter CMOS Image Sensor for Near-Infrared Applications
A high performance and low cost 2.2μm 1-layer pixel near infrared (NIR) global shutter (G/S) CMOS image sensor (CIS) was demonstrated. In order to improve quantum efficiency (QE), thick silicon with high aspect ratio full-depth deep trench isolation (FDTI) and backside scattering technology are implemented. Furthermore, thicker sidewall oxide for deep trench isolation and oxide filled FDTI were applied to enhance a modulation transfer function (MTF). In addition, 3-dimensional metal-insulator-metal capacitors were introduced to suppress temporal noise (TN). As a result, we have demonstrated industry-leading NIR G/S CIS with 2.71e- TN, dark current of 8.8e-/s, 42% QE and 58% MTF.
Wednesday, December 11, 2024 - 03:15 PM
41-4 | First Demonstration of 2.5D Out-of-Plane-Based Hybrid Stacked Super-Bionic Compound Eye CMOS Chip with Broadband (300-1600 nm) and Wide-Angle (170°) Photodetection
We propose a hybrid stacked CMOS bionic chip. The surface employs a fabrication process involving binary-pore anodic aluminum oxide (AAO) templates and integrates monolayer graphene (Gr) to mimic the compound eyes, thereby enhancing detection capabilities in the ultraviolet and visible ranges. Utilizing a 2.5D out-of-plane architecture, it achieves a wide-angle detection effect (170°) equivalent to curved surfaces while enhancing absorption in the 1550 nm communication band to nearly 100%. Additionally, through-silicon via (TSV) technology is integrated for wafer-level fabrication, and a CMOS 0.18-µm integrated readout circuit is developed, achieving the super-bionic compound eye chip based on hybrid stacked integration.
Wednesday, December 11, 2024 - 03:40 PM
41-5 | Pseudo-direct LiDAR by deep-learning-assisted high-speed multi-tap charge modulators
A virtually direct LiDAR system based on an indirect ToF image sensor and charge-domain temporal compressive sensing combined with deep learning is demonstrated. This scheme has high spatio-temporal sampling efficiency and offers advantages such as high pixel count, high photon-rate tolerance, immunity to multipath interference, constant power consumption regardless of incident photon rates, and motion artifact-free. The importance of increasing the number of taps of the charge modulator is suggested by simulation.
Wednesday, December 11, 2024 - 04:05 PM
41-6 | A Color Image Sensor Using 1.0-μm Organic Photoconductive Film Pixels Stacked on 4.0-μm Si Pixels for Near-Infrared Time-of-Flight Depth Sensing
We have developed an image sensor capable to simultaneously acquire high-resolution RGB images with good color reproduction and parallax-free ranging information by 1.0-μm organic photoconductive film RGB pixels stacked on 4.0-μm NIR silicon pixels for iToF depth sensing.
Wednesday, December 11, 2024 - 04:30 PM
41-7 | Pb-free Colloidal InAs Quantum Dot Image Sensor for Infrared
We developed an image sensor using colloidal InAs quantum dot (QD) for photoconversion. After spincoating the QDs on a wafer and standard semiconductor processing, the sensor exhibited infrared sensitivity and imaging capability. This approach facilitates easier production of lead-free infrared sensors for consumer use.
Wednesday, December 11, 2024 - 04:55 PM
41-8 | Lead-Free Quantum Dot Photodiodes for Next Generation Short Wave Infrared Optical Sensors
Colloidal quantum dot sensors are disruptingimaging beyond the spectral limits of silicon. In this paper,we present imagers based on InAs QDs as alternative for 1stgeneration Pb-based stacks. New synthesis method yields 9nm QDs optimized for 1400 nm and solution-phase ligandexchange results in uniform 1-step coating. Initial EQE is17.4% at 1390 nm on glass and 5.8% EQE on silicon(detectivity of 7.4 × 109 Jones). Using metal-oxide transportlayers and >300 hour air-stability enable compatibility withfab manufacturing. These results are a starting point towardsthe 2nd generation quantum dot SWIR imagers.
Also of interest, the following talk in Tuesday's session "Major Consumer Image Sensor Innovations Presented at IEDM"
Description: Authors: Albert Theuwissen, Harvest Imaging
Image Sensors past, and progress made over the years
Job Postings – Week of 17 November 2024
Image Sensors World Go to the original article...
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Apple Camera Sensing Systems Engineer |
Cupertino, California, USA |
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Camera Image Sensor Digital Design Engineer Lead |
Austin, Texas, USA |
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Fairchild Imaging Director of Sensor Product Engineering |
San Jose, California, USA |
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NASA Development of infrared detectors and focal plane arrays for space instruments - Postdoc |
Pasadena, California, USA |
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Ouster Silicon Photonics Packaging Engineer |
San Francisco, California, USA |
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DESY PhD Student in cryogenic detector systems |
Hamburg, Germany |
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Teledyne Senior Program Manager - Thermal Cameras |
Montreal, Quebec, Canada |
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Sandia National Laboratories Postdoctoral Appointee - Integrated Photonics for Imaging and Remote Sensing Applications |
Albuquerque, New Mexico, USA |
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Shanghai Jiao Tong University Postdoc-Experiment, Particle and Nuclear Division |
Shanghai, China |
Job Postings – Week of 17 November 2024
Image Sensors World Go to the original article...
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Apple Camera Sensing Systems Engineer |
Cupertino, California, USA |
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Camera Image Sensor Digital Design Engineer Lead |
Austin, Texas, USA |
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Fairchild Imaging Director of Sensor Product Engineering |
San Jose, California, USA |
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NASA Development of infrared detectors and focal plane arrays for space instruments - Postdoc |
Pasadena, California, USA |
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Ouster Silicon Photonics Packaging Engineer |
San Francisco, California, USA |
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DESY PhD Student in cryogenic detector systems |
Hamburg, Germany |
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Teledyne Senior Program Manager - Thermal Cameras |
Montreal, Quebec, Canada |
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Sandia National Laboratories Postdoctoral Appointee - Integrated Photonics for Imaging and Remote Sensing Applications |
Albuquerque, New Mexico, USA |
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Shanghai Jiao Tong University Postdoc-Experiment, Particle and Nuclear Division |
Shanghai, China |
AMS Osram Q3 2024 Results
Videos from EPIC Neuromorphic Cameras Online Meeting
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Presentations from the recent EPIC Online Technology Meeting on Neuromorphic Cameras are available on YouTube:
IKERLAN – DVS Pre-processor & Light-field DVS – Xabier Iturbe, NimbleAI EU Project Coordinator
IKERLAN is a leading technology centre in providing competitive value to industry, since 1974. They offer integral solutions in three main areas: digital technologies and artificial intelligence, embedded electronic systems and cybersecurity, and mechatronic and energy technologies. They currently have a team of more than 400 people and offices in Arrasate-Mondragón, Donostialdea and Bilbao. As a cooperative member of the MONDRAGON Corporation and the Basque Research and Technology Alliance (BRTA), IKERLAN represents a sustainable, competitive business model in permanent transformation.
FlySight – Neuromorphic Sensor for Security and Surveillance – Niccolò Camarlinghi, Head of Research
FlySight S.r.l. (A single member Company) is the Defense and Security subsidiary company of Flyby Group, a satellite remote sensing solutions company.
FlySight team offers integrated solutions of data exploitation, image processing, avionic data/sensors fusion. Our products are mainly dedicated to the exploitation of data captured by many sensors typeand our solutions are intended both for the on-ground as well as for the on-board segments.
Through itsexperience in C4ISR (Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance), FlySight offers innovative software development and geospatial application technology programs (GIS) customized for the best results.
Our staff can apply the right COTS for your specific mission.
The instruments and products developed for this sector can find application as dual use tools also in many civil fields like Environmental Monitoring, Oil & Gas, Precision Farming and Maritime/Coastal Planning.
VoxelSensors – Active Event Sensors : an Event-based Approach to Single-photon Sensing of Sparse Optical Signals – Ward van der Tempel, CTO
VoxelSensors is at the forefront of 3D perception, providing cutting-edge sensors and solutions for seamless integration of the physical and digital worlds. Our patented Switching Pixels® Active Event Sensor (SPAES) technology represents a novel category of efficient 3D perception systems, delivering exceptionally low latency with ultra-low power consumption by capturing a new Voxel with fewer than 10 photons. SPAES is a game-changing innovation that unlocks the true potential of fully immersive experiences for both consumer electronics and enterprise AR/VR/MR wearables.
PROPHESEE – Christoph Posch, Co-Founder and CTO
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, actionable motion information in the scene, not a succession of conventional images.
SynSense – Neuromorphic Processing and Applications – Dylan Muir, VP, Global Research Operations
SynSense is a leading-edge neuromorphic computing company. It provides dedicated mixed-signal/fully digital neuromorphic processors which overcome the limitations of legacy von Neumann computers to provide an unprecedented combination of ultra-low power consumption and low-latency performance. SynSense was founded in March 2017 based on advances in neuromorphic computing hardware developed at the Institute of Neuroinformatics of the University of Zurich and ETH Zurich. SynSense is developing “full-stack” custom neuromorphic processors for a variety of artificial-intelligence (AI) edge-computing applications that require ultra-low-power and ultra-low-latency features, including autonomous robots, always-on co-processors for mobile and embedded devices, wearable health-care systems, security, IoT applications, and computing at the network edge.
Thales – Eric Belhaire, Senior Expert in the Technical Directorate
Thales (Euronext Paris: HO) is a global leader in advanced technologies specialized in three business domains: Defence & Security, Aeronautics & Space, and Cybersecurity & Digital identity. It develops products and solutions that help make the world safer, greener and more inclusive.
"Photon inhibition" to reduce SPAD camera power consumption
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In a paper titled "Photon Inhibition for Energy-Efficient Single-Photon Imaging" presented at the European Conference on Computer Vision (ECCV) 2024 Lucas Koerner et al. write:
Single-photon cameras (SPCs) are emerging as sensors of choice for various challenging imaging applications. One class of SPCs based on the single-photon avalanche diode (SPAD) detects individual photons using an avalanche process; the raw photon data can then be processed to extract scene information under extremely low light, high dynamic range, and rapid motion. Yet, single-photon sensitivity in SPADs comes at a cost — each photon detection consumes more energy than that of a CMOS camera. This avalanche power significantly limits sensor resolution and could restrict widespread adoption of SPAD-based SPCs. We propose a computational-imaging approach called photon inhibition to address this challenge. Photon inhibition strategically allocates detections in space and time based on downstream inference task goals and resource constraints. We develop lightweight, on-sensor computational inhibition policies that use past photon data to disable SPAD pixels in real-time, to select the most informative future photons. As case studies, we design policies tailored for image reconstruction and edge detection, and demonstrate, both via simulations and real SPC captured data, considerable reduction in photon detections (over 90% of photons) while maintaining task performance metrics. Our work raises the question of “which photons should be detected?”, and paves the way for future energy-efficient single-photon imaging.
