Archives for May 2020

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CEI announces a special coronavirus edition of Advanced Course on Image Sensor Technology by Albert Theuwissen. The course is to be held on-line on June 1-5, 2020. The course is divided into 5 sessions of 4 hours each.

• Date: June 1-5, 2020
• Time: 1 PM – 5 PM CET, Monday to Friday. Live broadcast
• Platform: Zoom Pro. Per invite, no need to purchase a license or download software.
• Course link: https://www.cei.se/course-020-advanced-course-on-image-sensor-technology-group.html
• Course material: Printed book will be posted to home address before start.

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Quanergy adapts its LiDARs to check social distancing in public places:



IEEE Spectrum, Arstechnica: Volvo partners with Luminar to deliver Level 3 hands-free, eyes-off-the-road highway driving in 2022. Volvo, owned by Geely Holdings of China, said that models based on its upcoming SPA2 platform (for “Scalable Product Architecture”) will be hardware-enabled for Luminar’s roof-mounted lidar system, including the upcoming electric Polestar 3 and a range of Volvo-branded cars and SUVs. Henrik Green, Volvo CTO, says the optional “Highway Pilot” system would allow full autonomous driving, but only “when the car determines it is safe to do so.”

“At that point, your Volvo takes responsibility for the driving and you can relax, take your eyes off the road and your hands off the wheel,” Green said. “Over time, updates over-the-air will expand the areas in which the car can drive itself. For us, a safe introduction of autonomy is a gradual introduction.”

Volvo car roof with integrated Luminar LiDAR

Renault publishes Arxiv.org paper "Lidar for Autonomous Driving: The principles, challenges, and trends for automotive lidar and perception systems" by You Li, Javier Ibanez-Guzman.

"This article presents a review of state-of-the-art automotive LiDAR technologies and the perception algorithms used with those technologies. LiDAR systems are introduced first by analyzing the main components, from laser transmitter to its beam scanning mechanism. Advantages/disadvantages and the current status of various solutions are introduced and compared. Then, the specific perception pipeline for LiDAR data processing, from an autonomous vehicle perspective is detailed. The model-driven approaches and the emerging deep learning solutions are reviewed. Finally, we provide an overview of the limitations, challenges and trends for automotive LiDARs and perception systems."

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Nature paper "High performance planar germanium-on-silicon single-photon avalanche diode detectors" by Peter Vines, Kateryna Kuzmenko, Jarosław Kirdoda, Derek C. S. Dumas, Muhammad M. Mirza, Ross W. Millar, Douglas J. Paul, and Gerald S. Buller from Heriot-Watt University and University of Glasgow, UK, present clloed SPADs with over 30% PDE in SWIR.

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Mediatek announces its new 5G smartphone SoC Dimensity 1000+ with new imaging features:

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Tsinghua University, Beijing, China publishes MDPI paper "A Low-Power Column-Parallel Gain-Adaptive Single-Slope ADC for CMOS Image Sensors" by Jingwei Wei, Xuan Li, Lei Sun, and Dongmei Li.

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GlobeNewswire: Himax quarterly report updates on its image sensing business:

Ultralow power smart sensing

The Company is seeing a surging demand for battery-powered smart devices with AI-enabled, ultralow power intelligent sensing, especially in markets such as home appliances, door lock, doorbell, TV, notebook, building control and security.

WiseEye, the Company’s total solution for AI-based ultralow power smart sensing, is built on Emza’s unique AI-based algorithm, on top of Himax’s proprietary computer vision processor and CMOS image sensor, all equipped with ultralow power design. Currently laptop is the market of focus. Himax WiseEye 2.0 NB solution provides a ‘laptop-ready’ 3-in-1 RGB/IR/AI solution, respecting privacy while enhancing security for notebook users. A number of leading notebook OEMs and ODMs demonstrated the Company’s WiseEye NB solution in their next generation premium notebooks with positive feedbacks. In addition to notebook, the Company has also made progress with more OEMs in WiseEye solution into the displays to enable consumer privacy protection in real time and a reference design of the world’s first battery-powered human sensing solution for IoT market. Although the Covid-19 disrupted the development schedule, Himax sees customers already starting product promotion.

Moreover, for those customers/partners whose main business is to provide AI processor, Himax can offer its ultralow power image sensors without its AI processor and algorithm. The Company is pleased to report that its industry-first ultralow power backside-illuminated VGA CMOS image sensor has already been commercialized. It’s designed with low latency and autonomous modes for always-on, intelligent visual sensing applications which enables, with extremely low power consumption, human presence detection and tracking, gaze detection, behavioral analysis, and pose estimation for growing markets such as smart home, smart building, healthcare, smartphone and AR/VR devices. The VGA resolution also support greater than 90-degree wide field-of-view lens that makes it ideal in monitoring, detecting and image capturing.

Himax expects demand for the ultralow power sensing AIoT market to explode in the near future and numerous customers/ecosystem partners are expressing interest in the Company’s unique technology where it has made extraordinary progress in AI TV, smart home appliance, smart door lock/bell, smart surveillance applications that integrate voice and audio activation beyond facial recognition on edge device.

CMOS Image Sensor

Himax has covered its ultralow power smart sensing product status above. Now turning to the CMOS image sensor business update. The Company expects to see strong growth in this business due to the accelerated adoption of home working and online education.

The Company’s industry first 2-in-1 CMOS image sensor, which is another critical part of the WiseEye 2.0 NB total solution, is currently available for its partners/customers. This hybrid CMOS image sensor combines high quality HD image capabilities with ultralow power output for AI visual sensing applications, specifically for NBs. Featured in unique design and small form factor, it enables laptop makers to achieve ultra-narrow bezel design which is on track to become the mainstream in the next couple of years. The Company’s sensor has also incorporated an RGB-IR design to enable Windows Hello facial recognition. It helps reduce cost by eliminating the need to add an additional camera. Himax expects a small volume shipment for this product in 2020 with much expanded volume in the years after.

For the traditional human vision segments, Himax sees strong demand in notebooks, where the Company is one of the market leaders, and has experienced increased shipments for multimedia applications such as car recorders, surveillance, drones, home appliances, and consumer electronics, among others.

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NXP EdgeReady MCU-based machine vision solution leverages the i.MX RT106F crossover MCU to quickly and easily add face recognition capabilities to various, sometimes unexpected, devices: washing machines, dryers, ovens, refrigerators, stoves, dishwashers, microwaves, coffee machines, rice cookers, thermostats, HVAC, lighting control, power tools, etc.

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Teledyne e2v has been awarded funding in two separate UK Defence and Security Accelerator (DASA) competitions enabling the development of “Radiation-Hard Infrared Detectors for Space Applications” and novel detector materials addressing multiple wavebands or photon counting in the IR range.

The areas of development that funding has been awarded for are:

• III-V Barrier Diode Radiation-Hard Infrared Detectors for Space Applications
• 2-Colour T2SL Detector Technology – deep-dive investigation

InGaAs and InSb as well as other III-V compound semiconductor configurations as CMOS/ROIC designs and Type 2 Super Lattice (T2SL) has gained a lot of interest for IR detection applications. These devices are band-gap engineered by varying the composition and doping of the thin semiconductor layers.

With respect to T2SL detectors The artificial periodicity introduced by the multilayer structure produces super lattices. With type-1 super lattices, the electrons and holes are contained in the same layer. For type-2 super lattices, the electrons and holes are located in adjacent layers.

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GlobeNewswire: Teledyne e2v states that it will continue its role as a long-term partner in the development, fabrication, and supply of CCD detectors to the high science market – including space exploration, Earth observation, and ground-based scientific endeavours in the fields of microscopy, spectroscopy and astronomy.

While other technology companies have migrated to CMOS technology over continuing development of CCD technology, Teledyne Imaging, through its European business, e2v, and with Teledyne DALSA’s foundry in Bromont, Canada, will continue to supply high quality, mission critical CCD detectors to enable the most demanding of imaging applications. In addition, the group will continue to invest in complementary technologies such as CMOS, x-ray, spectroscopy, and infrared technologies, providing a well-balanced set of business lines to address a growing customer base across existing and emerging markets.

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NIT releases its latest SWIR sensor – NSC1902T-SI with innovative design of its InGaAs photodiode array coupled to a ROIC. The new sensor’s highlights include low noise and ultra-low dark current. It can operate with an FPA temperature as low as -20°C only with internal air cooling.

Among its key features are:

• Lowest dark current of its class: less than 1500 e-/pixels/s @-20°C
• High QE: 90% typical
• Sensor noise: less than 40e-
• Integration time: 10 µs to 112 sec
• Frame rate: Up to 230fps full frame

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Yole Developpement report "Sensing and Computing for ADAS Vehicle 2020" forecasts:

"The auto industry has seen the impact of the coronavirus crisis evolve from a supply shock to a global demand shock. The production of new cars is expected to decline by 30% compared to the 2019 production level.

It is expected that three years will be needed to recover and get back to the same level of output. In 2020, it is expected that the global market for radars, cameras, LiDARs and computing hardware should reach $7.1B. More than half of this market revenue will be generated by radars with $4.2B, followed by cameras with $2.7B. LiDARs and computing hardware will not be significant, accounting for $0.04B and $0.2B respectively.

With high penetration rates of radars and cameras in cars, the associated market revenues will recover rapidly from the coronavirus crisis. Camera market revenue will take two years to surpass 2019’s level and will reach $4.9B in 2025 at a CAGR of 13%. LiDAR market revenue is quite limited today as only one OEM is implementing this sensor as an option in some of its cars. Other OEMs are expected to follow in coming years, but the implementation will remain limited to luxury vehicles, and therefore low volumes are expected. In this context, LiDAR market revenue is expected to reach $1.6B in 2025 at a CAGR of 111%. LiDAR is a complex sensor for OEMs and Tier-1s to integrate and radars and cameras are, at the same time, continuously improving their performance.

...the penetration rate of forward ADAS mono cameras will increase from 38% in 2020 to 55% in 2025. This type of camera is multi-purpose and is used for AEB for also for other functionalities like Lane Keeping Assist (LKA) or Traffic Sign Recognition (TSR) in mainstream cars. For most advanced cars, forward ADAS triple cameras are used to develop advanced automated driving features like Tesla’s.

On the LiDAR side, technology is moving from a macro-mechanical scanning to MEMS scanning and flash. Most LiDAR manufacturers are involved in these solid-state technologies. One of the issues for LiDAR is its integration into the vehicle. Today it is integrated in the grill, but that may not be the ideal solution. Two other positions, in headlamps or behind the windshield, are targeted by Tier-1s and OEMs.

To do so, more R&D will be necessary to reduce the volume of this sensor and allow its integration. Another issue for LiDAR is the need to process the large quantity of data it generates. High computing power, over 25 teraoperations per second (Tops), will be necessary. The last issue with LiDAR is its cost compared to the two other technologies. It is about 10 times costlier than an ADAS mono camera. Alongside volume reduction, cost reduction will also be required for significant adoption by OEMs."

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Yole Developpement report "Sensing and Computing for ADAS Vehicle 2020" forecasts:

"The auto industry has seen the impact of the coronavirus crisis evolve from a supply shock to a global demand shock. The production of new cars is expected to decline by 30% compared to the 2019 production level.

It is expected that three years will be needed to recover and get back to the same level of output. In 2020, it is expected that the global market for radars, cameras, LiDARs and computing hardware should reach $7.1B. More than half of this market revenue will be generated by radars with $4.2B, followed by cameras with $2.7B. LiDARs and computing hardware will not be significant, accounting for $0.04B and $0.2B respectively.

With high penetration rates of radars and cameras in cars, the associated market revenues will recover rapidly from the coronavirus crisis. Camera market revenue will take two years to surpass 2019’s level and will reach $4.9B in 2025 at a CAGR of 13%. LiDAR market revenue is quite limited today as only one OEM is implementing this sensor as an option in some of its cars. Other OEMs are expected to follow in coming years, but the implementation will remain limited to luxury vehicles, and therefore low volumes are expected. In this context, LiDAR market revenue is expected to reach $1.6B in 2025 at a CAGR of 111%. LiDAR is a complex sensor for OEMs and Tier-1s to integrate and radars and cameras are, at the same time, continuously improving their performance.

...the penetration rate of forward ADAS mono cameras will increase from 38% in 2020 to 55% in 2025. This type of camera is multi-purpose and is used for AEB for also for other functionalities like Lane Keeping Assist (LKA) or Traffic Sign Recognition (TSR) in mainstream cars. For most advanced cars, forward ADAS triple cameras are used to develop advanced automated driving features like Tesla’s.

On the LiDAR side, technology is moving from a macro-mechanical scanning to MEMS scanning and flash. Most LiDAR manufacturers are involved in these solid-state technologies. One of the issues for LiDAR is its integration into the vehicle. Today it is integrated in the grill, but that may not be the ideal solution. Two other positions, in headlamps or behind the windshield, are targeted by Tier-1s and OEMs.

To do so, more R&D will be necessary to reduce the volume of this sensor and allow its integration. Another issue for LiDAR is the need to process the large quantity of data it generates. High computing power, over 25 teraoperations per second (Tops), will be necessary. The last issue with LiDAR is its cost compared to the two other technologies. It is about 10 times costlier than an ADAS mono camera. Alongside volume reduction, cost reduction will also be required for significant adoption by OEMs."

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ON Semi shows its triple-exposure HDR sensor AR0239 with Pinnacle Denali ISP platform:

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Caltech publishes Nature paper "Single-shot ultrafast imaging attaining 70 trillion frames per second" by Peng Wang, Jinyang Liang, and Lihong V. Wang.

"Real-time imaging of countless femtosecond dynamics requires extreme speeds orders of magnitude beyond the limits of electronic sensors. Existing femtosecond imaging modalities either require event repetition or provide single-shot acquisition with no more than 1013 frames per second (fps) and 3 × 10^2 frames. Here, we report compressed ultrafast spectral photography (CUSP), which attains several new records in single-shot multi-dimensional imaging speeds. In active mode, CUSP achieves both 7 × 10^13 fps and 103 frames simultaneously by synergizing spectral encoding, pulse splitting, temporal shearing, and compressed sensing—enabling unprecedented quantitative imaging of rapid nonlinear light-matter interaction. In passive mode, CUSP provides four-dimensional (4D) spectral imaging at 0.5 × 10^12 fps, allowing the first single-shot spectrally resolved fluorescence lifetime imaging microscopy (SR-FLIM). As a real-time multi-dimensional imaging technology with the highest speeds and most frames, CUSP is envisioned to play instrumental roles in numerous pivotal scientific studies without the need for event repetition."

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PRNewswire: OmniVision announces its 1.3MP OX01E10 SoC for entry-level rearview cameras (RVC). In a single, 1/4" optical format package, the OX01E10 integrates a 3um image sensor and an ISP. Additionally, the OX01E10 provides two onscreen display overlay layers for driver guidelines, as well as distortion correction to straighten any curved edges from lenses with a wide viewing angle.

The OX01E10 features power consumption that is over 35% lower than competitors' and significantly reduces temperature. This is said to be the only imaging device for entry-level RVC that does not require a metal heat sink, allowing for the use of plastic camera module bodies to reduce costs. With its compact package size, it also enables smaller cameras that can fit in much tighter spaces. In addition, by integrating both the image sensor and ISP into a single chip, designers can save on both cost and space by eliminating the second PCB in typical two-chip implementations. OmniVision's dual conversion gain (DCG) technology is employed in this SoC to achieve a HDR of 120dB with two captures.

The OX01E10 SoC is AEC-Q100 Grade 2 certified and samples are available now, with mass production expected in Q3 2020.

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Tower and Technion, Israel Institute of Technology, publish a Nature paper "Hybrid image sensor of small molecule organic photodiode on CMOS – Integration and characterization" by Himanshu Shekhar, Amos Fenigstein, Tomer Leitner, Becky Lavi, Dmitry Veinger, and Nir Tessler.

"Here, we demonstrate seamless integration of a thermally deposited visible light sensitive small molecule OPD on a standard commercial CMOS substrate using optimized doped PCBM buffer layer. Under a standard power supply voltage of 3 V, this hybrid device shows an excellent photolinearity in the entire bias regime, a high pixel sensitivity of 2 V/Lux.sec, a dynamic range (DR) of 71 dB, and a low dark leakage current density of 1 nA/cm2. Moreover, the integrated OPD has a minimum bandwidth of 400 kHz. The photoresponse nonuniformity being only 1.7%, achieved under research lab conditions, strengthens the notion that this fully-CMOS compatible technology has the potential to be applied in high-performance large-scale imaging array."

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Lucid Vision Labs assembled a nice page comparing Sony Pregius GS pixel generations:

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INSTICC publishes Alan Chalmers' talk "High Dynamic Range: Where to next?" presented at VISIGRAPP in February 2020 at Malta.

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EPFL presentation "LiDAR Fundamentals" by Claudio Bruschini, Preethi Padmanabhan, Edoardo Charbon has been published by SENSE Detector School a year ago.

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Samsung 4th part of image sensor video series talks about Nonacell technology:

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Trieye Board of Directors member Ido Yablonka twits the company's first public SWIR image:

"Delivery >> corona crisis.
a sneak peek at a breakthrough in progress - amazing work by @TriEye_tech #swir #deeptech"

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Cambridge Mechatronics Ltd. reports: "The LiDAR scanner used by Apple in its recently released iPad Pro uses technology to increase the range to five metres and include more of the surroundings. However, this LiDAR technology results in a compromise to measurement resolution. Some reviewers highlighted performance inaccuracies and limitations.

However, CML has developed technology that increases the range to ten metres without compromising measurement resolution. Tier 1 smartphone supply chains are including this functionality in module samples planned to be available in Q3 this year.

The 3D sensing modules including CML’s technology will have double the working range compared to the LiDAR scanner and ten times superior measurement accuracy. This can deliver the most realistic AR experiences in a broader range of scenarios."

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NanoLambda publishes a Youtube video saying that its spectrometer module has more than 30 competitors now. So, the company looks for partnerships and funding for its technology:

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