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Argo.ai Keynote on SWIR SPAD LiDAR


Omnivision CameraCubeChip Reverse Engineering

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SystemPlus Consulting publishes a reverse engineering report of OVM6948 CameraCubeChip:

"The smallest camera in the world, it is a Video Graphics Array (VGA) camera module. It integrates a Wafer-Level Packaged (WLP) OmniVision CMOS Image Sensor (CIS) and a small Wafer-Level Optic (WLO) manufactured by VisEra. The entire camera module is provided in a 0.65mm x 0.65mm x 1.2mm 4-pin package including a 0.58mm x 0.58mm CIS die. The CIS die is packaged by Xintec’s new WLP technology for CIS. The bumps on the backside are connected with Through Silicon Vias (TSVs). A complex stacking of eight optical layers in 1mm is necessary to provide the wide 120 degree field of view and an extended focus range of 3mm to 30mm. Moreover, the OMV6948 is a fully wafer bonded solution.

The endoscopy market was worth $6B in 2019, with reusable flexible endoscopy being the major market, worth more than $4B. However the new standard for small diameter endoscopes, specifically bron-choscopes and urethroscopes, is now becoming disposable flexible endoscopes. Omnivision is one of the leaders in providing very small camera modules aiming at supplying this new, developing market.
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Samsung Tetracell Promotional Video

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Samsung keeps publishing its image sensor promotional videos. The 3rd video in the series talks about Tetracell pixels:

OmniVision Presents its First 0.702um Pixel and 64MP Sensor for Smartphones

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PRNewswire: OmniVision announces the OV64B, the industry’s only 64MP sensor with a 0.702um pixel size, enabling 64 MP resolution in a 1/2” optical format for the first time. Built on OmniVision’s PureCel Plus stacked die technology, this sensor provides 4K video recordings with EIS, as well as 8K video at 30fps.

This year, TSR estimates there will be 127 million image sensors with 64 MP or higher resolution shipped to smartphone manufacturers,” said Arun Jayaseelan, staff marketing manager at OmniVision. “The OV64B, with the industry’s smallest size for a 64 MP sensor, is further enabling this trend among high end and high mainstream smartphone designers who want the best resolution with the tiniest cameras.

The OV64B supports 3-exposure, staggered HDR timing for up to 16 MP video modes. It integrates a 4-cell CFA with on-chip hardware re-mosaic, which provides 64 MP Bayer output in real time. In low light conditions, this sensor can use near-pixel binning to output a 16 MP image with 4X the sensitivity, offering 1.4um equivalent performance.

The sensor features type-2, 2x2 microlens phase detection AF (ML-PDAF) to boost autofocus accuracy, especially in low light. It also provides a C-PHY interface and supports slow motion video for 1080p at 240 fps and 720p at 480 fps. Other output formats include 64 MP at 15 fps, 8K video at 30fps, 16 MP captures with 4-cell binning at 30fps, 4K video at 60fps and 4K video with EIS at 30fps.

Samples of the OV64B are expected to be available in May 2020.

Teledyne e2v Expands its Emerald Family with 3.2MP GS Sensor

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GlobeNewswire: Teledyne e2v announces its new Emerald 3.2MP CMOS sensor for emerging applications such as security, drones and embedded vision, as well as traditional machine vision. With its 2.8 µm global shutter pixel, the new 3.2M sensor shares all of the characteristics of the Emerald sensor series: low-noise performance, compact format, easy integration and a wide range of embedded features.

The sensor has been designed in an ultra-compact light package format with low power to address the challenge of optimizing SWaP-C (Size, Weight, Power and Cost). The device also features a MIPI interface and is pin-to-pin and optically compatible with Emerald 2M and Emerald 5M, so that multiple resolutions are supported from one single design, saving cost.

This new sensor completes Teledyne e2v’s Emerald product portfolio which includes sensors in resolutions from 2MP to 67MP. Evaluation Kits and samples of Emerald 3.2M are now available.

Princeton Instruments Super Deep Depletion CCD Achieves 75% QE at 1000nm

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It came to my attention that Teledyne Princeton Instruments Blaze CCD-based cameras achieve 75% QE at 1000nm wavelength and are quite sensitive even at 1050nm. This CCD is a fairly new product manufactured since 2017:

"Proprietary BLAZE HR-Sensors are “super-deep-depletion” CCDs manufactured from high-resistivity bulk silicon in order to yield the highest near-infrared quantum efficiency of any silicon device. The silicon depletion region of each HR-Sensor is almost 4x thicker than that of a conventional deep-depletion (NIR-sensitive) CCD, affording quantum efficiency up to 7x greater at 1 µm than the best other deep-depletion sensors.

Spatial resolution for HR-Sensors is optimized by applying a bias voltage, resulting in a “fully depleted” silicon region with no diffusion of charge. The bias voltage generates an electric field that pushes the charge toward the correct pixels and does not allow charge to migrate to adjacent pixels.

The new sensors are offered in either 1340x100 or 1340x400 array formats with 20 µm pixels.
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Assorted News: Actlight, AImotive, Brookman, Akasha Imaging, Quanergy

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PRNewswire: ActLight has signed a license agreement with a "leading semiconductor company" that intends to use ActLight's dynamic photodiode in healthcare applications.

"Now that the COVID-19 pandemic is spreading throughout the globe, we are proud to offer our Dynamic PhotoDiode technology to the healthcare segment together with a prestigious semiconductor company. In these times of trouble we all need to join forces to exploit innovative technologies at the service of the impacted communities," said Roberto Magnifico, Chief Commercial Officer at ActLight.


Edge AI and Vision Alliance publishes an interesting presentation by Gergely Debreczeni, Chief Scientist at AImotive, talking about many different ways to estimate the distance. The presentation slides are available here. Surprisingly, there too many camera-based approaches than anybody can think of:



Brookman publishes a video presentation of the company in Japanese:



Akasha Imaging startup led by CEO Kartik Venkataraman (ex-Pelican Imaging founder and CTO) apparently goes to combine polarization with 3D sensing:

"Akasha Imaging is a Khosla Ventures backed MIT Media Lab spinout founded on breakthrough technology using polarized light."


Quanergy adapts its LiDAR software to track social distancing during coronavirus pandemic:

In order for communities and cities to re-open and for the public to feel safe re-entering society, there must be a way to responsibly enforce social distancing,” said Kevin J. Kennedy, Chairman and CEO of Quanergy. “We believe LiDAR can play a key role in accelerating our return to work and restarting our economy. Quanergy is working closely with our current and new global partners to deploy solutions to instill confidence for businesses and the public in returning to our lives outside our homes.

Apple iPad and Ouster LiDARs Compared

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Ouster publishes an article "Why Apple chose digital lidar" by Raffi Mardirosian comparing its own design choices with Apple's. Few quotes:

"The iPad Pro is equipped with a Digital Flash Lidar (a type of solid-state lidar) system. As the name suggests, just like a camera’s flash, a flash lidar detects an object by emitting a light wall, instead of scanning the laser beam point by point in a traditional mechanical rotary lidar.

The system uses vertical cavity surface emitting lasers (VCSELs) paired with and single photon avalanche diodes (SPADs) for the light detectors, the same as with FaceID. These two technologies form the foundation of Digital Lidar and are ideally suited for commercialization for a number of reasons:
  1. VCSELs and SPADs offer a superior performance, form factor, and cost profile. VCSELs are smaller, lighter, more durable, and easier to manufacture compared with other emitter technologies. SPADs can be densely packed on a chip, count individual photons, and have excellent time resolution, resulting in a simpler, smaller, more durable, and natively digital architecture in contrast to legacy analog lidar detectors such as APDs or SiPMs (which could not fit in a consumer device).
  2. VCSELs and SPADs support a more rugged and robust system because they can both be integrated onto a chip. Printing all the lasers and all the detectors onto chips greatly reduces the number of components in the system and improves durability and ruggedness.
  3. VCSELs and SPADs have costs that fall faster with scale, are cheaper to produce in high-resolution implementations, and are improving along with Moore’s Law — whereas edge-emitting lasers and legacy analog APD and SiPM detectors are mature and have little room for improvement.
We are happy to see Apple come to the same conclusion that we did when we first designed our high-performance digital lidar sensors.

In fact, since we first designed our system in 2015, we’ve seen the performance of our VCSELs and SPADs improve by ~1000% while there has been little change in the analog technology used in other spinning lidar sensors.
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Sony Employee Awarded Purple Ribbon Medal for Multi-Layer Stacked Image Sensor

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Sony announces that Taku Umebayashi, an employee of the Sony, will be awarded the Purple Ribbon Medal for his achievements in the development of a laminated multifunctional CMOS image sensor structure. The Purple Ribbon Medal Award is given for outstanding inventions and discoveries in the field of science and technology and in the academic, sports, and arts and culture fields.

"We succeeded in mass-producing CMOS image sensor of the laminated structure which superimposed the pixel portion where the back illuminated pixel was formed on the chip that the signal processing circuit was formed instead of the support substrate of the conventional back-illuminated CMOS image sensor. This laminated structure enables large-scale circuits to be mounted at small chip sizes, and the pixel and circuit parts that are capable of independent formation can be adopted by a specialized manufacturing process, enabling miniaturization, high image quality, and high functionality at the same time. In addition, by adopting a cutting-edge process on the chip in which the circuit is formed, it is possible to achieve faster signal processing and low power consumption. In recent years, further improvements in performance have been applied as a basic technology to promote high functionality of various sensing devices, including image sensors."

ADAS and AV Sensor Suites

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ReesearchInChina reports that automatic parking solutions are mostly based on ultrasonic sensors with camera-based solutions are quickly gaining share:


"Rare application of ultrasonic + visual fusion solution in the past lies in lack of algorithms and powerful compute. Tesla, the pioneer going intelligent, has long resorted to ultrasonic solutions, and its automated parking capability has not performed well. Even Smart Summon launched in the second half of 2019 is not so successful, either."

Another ResearchInChina report compares Tier 1's approaches to ADAS and autonomous driving sensors. Most of them are using cameras and about 25% are using LiDARs:


In yet another report, ResearchInChina compares L4 AV sensor suites from different companies:

SK Hynix on Smart Eye Sensor

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SK Hynix publishes an article "“Smart Eye”, A Computer Inside Our Eyes."

"The story we are going to tell you now is about “Smart Eye”, something we might see in the future, thanks to the development of semiconductor technology.

...the current CIS technology has not reached the level of human eyes in terms of major features such as resolution, three-dimensionality, and sensitivity. While the resolution of human eyes is 576 megapixels (MP), the highest resolution CIS can currently realize is only 108Mp. When brightness of surrounding environment changes in a sudden, CIS is also likely to suffer from latency accepting visual information.

Ho-young Cho, Technical Leader (TL) at CIS Marketing Strategy of SK hynix said, “While human eyes’ main purpose is to recognize rather than display the collected visual information, CIS is designed for securing visual information for output. If CIS can recognize at the same level as human eyes do in the future, it will also function as a displaying device that outputs the collected information.”

Cho continued, “Unlike human eyes, CIS is designed as individual modules for various purposes. As a result, CIS is detachable, and users can equip different CIS depending on various situations. Such flexibility will make our daily lives more convenient with no doubt.”
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Techinsights Publishes Pixel Cross-section of iPad LiDAR SPAD

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Techinsights twits about the first results of Apple iPAD 2020 LiDAR reverse engineering:

"Our analysis continues for #Sony d-ToF sensor from #Apple iPad Pro LiDAR system. TechInsights confirms stacked back-illuminated SPAD sensor; pixel-level DBI & metal filled B-DTI."


Thanks to RF for the pointer!

nanoLambda Seeks Partnerships and Funding

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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:

CML Reports that Tier 1 Smartphone Adopts its ToF Technology

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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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Trieye First Public SWIR Image

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

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

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

EPFL Presentation on LiDAR Fundamentals

HDR: Where to Go Next?

Lucid Vision Labs Compares 4 Generations of Sony Global Shutter Pixels

Tower and Technion Integrate Organic PD into CMOS Process

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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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