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ResearchInChina publishes "ADAS and AD Industry Chain Report, 2019-2020 -- LiDAR" report."

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Metrology.news: The National Institute of Standards and Technology (NIST) in the US, together with standards body ASTM Committee E57, have released proceedings of a workshop, held in 2019, to define standards for 3D imaging systems for robots in manufacturing.

Intel talks about the 3D image accuracy in its Realsense active stereo cameras:


Airy3D publishes its take of the 3D imaging standards.

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Nuvoton announces that the acquisition of semiconductor business of Panasonic has been completed. Following the completion of the Transfer, the business will be renamed as Nuvoton Technology Corporation Japan.

In the long term, Nuvoton is expected to enhance the technology capabilities, diversify the product line, enlarge its business scopes as well as revenue growth, gain additional market shares and therefore increase its visibility in both Japan and the global market.

In the short term, the acquisition may have a negative impact on Nuvoton's profitability, as per Digitimes quote of Arthur Chiao, chairman for Nuvoton and Winbond.

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LIPS designs ToF calibration machine for smartphone ToF modules:

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BusinessWire: SmartSens announces two automotive CMOS sensors—SC100AT and SC410GS. The SC100AT and SC410GS are the first offerings in the SmartSens Automotive Series with AEC-Q100 certification and an HDR of up to 140dB. SmartSens’ proprietary PixGain HDR® technology also gives the SC100AT the ability to produce readout noise levels as low as 0.58e-, resulting in clear and detailed night vision in low-light environments. The sensor’s primary use cases include blind spot monitoring, side-view mirror replacement, parking assistance, driving recording, back-up monitoring, and vehicle surround view.

The SC410GS features 4MP resolution, BSI global shutter pixels, and HDR that processes up to 12000mV/Lux-s, to resolve overexposures of signal lights at night.

“Recent growth in the construction and development of intelligent transportation systems around the world are creating new demand for image sensors that can empower smart cars and intelligent traffic management. Our SC100AT and SC410GS combine our CMOS sensor leadership with automotive-specific design that delivers the next level of reliability and performance required for tomorrow’s driving experiences,” said James Ouyang, Deputy GM of SmartSens.

SmartSens SC100AT and the SC410GS image sensors are available for testing immediately.

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ESSCIRC and ESSDERC conferences host a 6 hour-long on-line Workshop on Emerging Solutions for Imaging Devices, Circuits, and Systems chaired by Matteo Perenzoni (FBK) and Albert Theuwissen (Harvest Imaging). The program includes:

• Applications of single photon detection in computational and quantum imaging.
  Daniele Faccio (University of Glasgow, UK)
• Infrared detectors in the wake of visible sensors
  Patrick Robert (Lynred, France)
• Event cameras
  Tobi Delbruck (University of Zurich, Switzerland)
• Broadband image sensors based on 2D materials, integrated with silicon technology
  Frank Koppens (ICFO Barcelona, Spain)
• Vertical Deep Trench MOS Capacitance principle and application to CMOS Image Sensors
  François Roy (ST Microelectronics, France)
• Coded-exposure-pixel Image Sensors for Computational Photography
  Roman Genov (University of Toronto, Canada)

The presentations will be available online on-demand starting from September 7, 2020.

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Axiv.org paper "Learning Camera-Aware Noise Models" by Ke-Chi Chang, Ren Wang, Hung-Jin Lin, Yu-Lun Liu, Chia-Ping Chen, Yu-Lin Chang, and Hwann-Tzong Chen from Mediatek and National Tsing Hua University, Taiwan, automates image sensor model building:

"Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications. While most previous works adopt statistical noise models, real-world noise is far more complicated and beyond what these models can describe. To tackle this issue, we propose a data-driven approach, where a generative noise model is learned from real-world noise. The proposed noise model is camera-aware, that is, different noise characteristics of different camera sensors can be learned simultaneously, and a single learned noise model can generate different noise for different camera sensors. Experimental results show that our method quantitatively and qualitatively outperforms existing statistical noise models and learning-based methods."

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Photonis publishes a demo of its Nocturn color camera at 0.01 Lux scene illumination.

"The NOCTURN Color models are powered by the proprietary KAMELEON imaging sensor, a solid-state sensor that offers less than 4e- read noise, with SXGA (1280×1024) resolution at frame rates up to 100 Hz. The KAMELEON sensor provides large 9.72µm pixels with microlenses for optimum quantum efficiency in excess of 60%, providing high-resolution low light color images that extend the vision of the human eye."

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Nanjing University, China, publishes and MPDI review paper "Low-Cost Microbolometer Type Infrared Detectors" by Le Yu, Yaozu Guo, Haoyu Zhu, Mingcheng Luo, Ping Han, and Xiaoli Ji. The review belongs to "Miniaturized Silicon Photodetectors: New Perspectives and Applications" special issue.

"The complementary metal oxide semiconductor (CMOS) microbolometer technology provides a low-cost approach for the long-wave infrared (LWIR) imaging applications. The fabrication of the CMOS-compatible microbolometer infrared focal plane arrays (IRFPAs) is based on the combination of the standard CMOS process and simple post-CMOS micro-electro-mechanical system (MEMS) process. With the technological development, the performance of the commercialized CMOS-compatible microbolometers shows only a small gap with that of the mainstream ones. This paper reviews the basics and recent advances of the CMOS-compatible microbolometer IRFPAs in the aspects of the pixel structure, the read-out integrated circuit (ROIC), the focal plane array, and the vacuum packaging."

One interesting type of microbolometer is based on forward-biased SOI diodes:

"The typical value of the sensitivity for a single diode at 300 K is ~2 mV/K under a bias voltage of 0.6 V [59], which is equivalent to a temperature coefficient of only ~0.33%/K. However, as the number of the diodes in the series increases, the temperature coefficient could become comparable to the TCR of VOx. For instance, when n = 8, the diodes in series connection have a temperature coefficient of ~3%/K. Meanwhile, benefiting from the high uniformity of the CMOS process and the low defect density in the SOI film, the diode type microbolometer usually exhibits much better noise."

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Xiaomi publishes a Youtube video showing its 3rd generation under-display camera. The company expects to put it in a mass production phone next year:



GizmoChina reports that the 1st and 2nd generation used OLED displays with reduced pixel density in the camera area. The 3rd generation uses the same OLED pixel pitch, but the OLED "fill factor" is reduced to that light can penetrate to the camera. That way, pixel density, color accuracy, color gamut, and brightness in the camera area is similar to the rest of the display.


SparrowsNews adds few more details and links to the Chinese sources:

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Senseeker Engineering introduces quarter wafers of the Oxygen RD0092 digital readout IC (DROIC). This allows customers to acquire a reduced minimum order quantity of ICs at lower-cost for evaluation and prototyping.

Each fully tested quarter wafer is supplied with a minimum number of guaranteed good die. A full data pack that includes a GUI-based clickable wafer map is also furnished. The wafer map provides color-coded grade information for each die along with a top-level summary (die yield, results of each individual test, and final grade). Clicking any die on the map displays a detailed test summary plot that contains test images, histograms for the test images, pixelwise differences used to reject bad pixels with pass/fail thresholds indicated, bad pixel map image and a bar graph showing the measured supply currents in the screen test state.

To further simplify the evaluation and development experience using the Oxygen RD0092, Senseeker offers an evaluation kit that can be used for cooled or uncooled lab testing. The evaluation kit comes complete with software and is easily connected to a host PC with a frame grabber card for image display.

"We are focused on making it as inexpensive and easy as possible for customers to get up-and-running with Senseeker's commercial readout products," said Kenton Veeder, President at Senseeker Engineering. "Our goal is to lower the barriers-to-entry of using advanced digital readout ICs by making them available off-the-shelf in lower quantities than a full wafer. We also believe that it is critical to provide the whole ecosystem of tools that are required to expedite the development process."

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Yole Developpement 1, Yole Developpement 2: “The price drop in LiDAR in the past three years has been massive,” says Pierrick Boulay, Technology & Market Analyst, Solid-state Lighting at Yole Développement (Yole). “Indeed, it is the result of strategies by different companies and not due to the result of mass-production. Volumes have not evolved significantly in these three years and mass adoption of LiDAR still has to happen. However, this price drop of LiDAR has a significant impact on market forecast. At Yole, we expect that the unit price of LiDAR will continue to decline, and large volumes will be needed in order to maintain the market.”

"A new trend in the LiDAR business appeared a few years ago, which might dramatically change the shape of LiDAR market, namely price drops. Velodyne has announced a plan to reach an average unit price of $600 by 2024, from $17,900 in 2017. Chinese LiDAR companies, which usually have LiDAR unit prices one-fifth of other companies and usually below $1,000, are gaining market share and expanding their business. LiDAR with lower unit prices is expected to enter new industrial applications including factory, logistics and security. However, because of lower LiDAR unit prices, the industrial segment is expected to have moderate growth between 2019 and 2025, expanding from $390M to $567M."

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BusinessWire, The Elec: Samsung Display announced today that UL has just verified its new smartphone OLED hole display area as having image quality low in color deviation in terms of “hole area clarity.”

“Enabling uniform image quality on the display at the periphery of the camera hole allows users to feel a more in-depth sense of picture-taking immersion, in addition to directly benefiting from the ingenuity of the hole design itself,” said Dennis Choi, VP of mobile display marketing team for Samsung Display. “Without a doubt, our camera hole area clarity demonstrates that Samsung Display technological prowess can deliver optimal performance across an entire 5G smartphone display.”

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Melexis publishes a webinar on continuous wave ToF sensors:



The company also publishes another ToF video demoing its in-cabin monitoring:



Melexis also has a special Youtube channel dedicated to ToF imaging.

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Few more slides from TSMC Technology Symposium 2020 have been published at moore.live site. TSMC aims its 28nm CIS process to shrinking the pixel pitch from the current state of the art of 0.8um to 0.7um:


The next generation stacking process includes a fairly recent 12nm FinFET process for the bottom logic wafer:


Talking about the 12nm process intended use cases, TSMC mentions: "TSMC developed N12e specifically for AI-enabled IOT and other high efficiency, high performance edge devices. N12e brings TSMC’s world class FinFET transistor technology to IOT.

...Enhanced Machine Vision – insects, shadows or animals often falsely trigger connected security cameras. By moving the image classifier to the edge, the AI-enabled connected cameras can continually monitor for humans – even with facial recognition but ignore pets and insects without sending gigabytes of HD video into the cloud for inferencing."

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ON Semi publishes a webinar recording on automotive surround view cameras:

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ON Semi publishes a webinar recording on automotive surround view cameras:

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AnandTech: TSMC Technology Symposium being held on-line these days shows the foundry's lineup of the processes. The most advanced CIS process in development is 28nm, while the logic process is 7 generations ahead at 3nm:


TodayUSStock posts few more slides form the Symposium:

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BusinessWire: OmniVision announces the OS02G10 1080p30 security sensor with a 2.8um OmniPixel3-HS architecture. Compared with OmniVision’s prior-generation mainstream security sensor, it has a 60% better SNR1 and 40% lower power consumption.

OmniVision is using 12” wafers to produce this image sensor, instead of the 8” wafers that are in tight supply but are typically used for 2MP, 1080p sensors. This enables the company to better address the increasing demand for this resolution, which remains the most popular in the steadily growing market for consumer-grade, IoT security cameras, as well as low-end industrial and commercial surveillance cameras.

“The OS02G10 builds on the success of our previous-generation OmniPixel 3-HS sensor, which has been widely adopted in the mainstream security markets,” said Cheney Zhang, senior marketing manager for the security segment at OmniVision. “With this new generation, we have significantly improved low-light performance while continuing to offer the market greater value in the popular 1/2.9” optical format.”

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BusinessWire: After Velodyne, another LiDAR company, Luminar, goes public on NASDAQ by reverse merging with Gores Metropoulos. The transaction includes $400M of cash from Gores Metropoulos and an immediate $170M financing into Luminar. The combined company will have an implied pro forma enterprise value of approximately $2.9 billion and an equity value of approximately $3.4 billion at closing.

"Founded in 2012 by CEO Austin Russell, Luminar is the leading autonomous vehicle and lidar technology company for consumer cars and trucking. Luminar is partnered with 7 of the top 10 global automakers and is set to power the introduction of highway self-driving and next-generation safety systems. Over 350 people strong, Luminar has built a new type of lidar from the chip-level up with breakthroughs across all core components.

Luminar today also announced it has scaled its software team with the addition of 16 former members of Samsung’s Munich-based DRVLINE platform team that were previously responsible for delivering ADAS functionality to its mobility customers. Luminar will leverage this team to bring a full-stack lidar-based ADAS and Level 4 highway autonomy product offering to market."

Luminar's presentation talks about the company's achievements:


Like in case of Velodyne, becoming a public company gives us a rare opportunity to look into the LiDAR company economics:

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EENews: vivaMOS receives £4.8M (€5.3M) grant to develop an ultra-low noise X-Ray wafer scale sensor for optical astronomy and medical imaging. vivaMOS, based in Southampton, UK, spun out of the Rutherford Appleton laboratory in 2015 to commercialize the 6.7MP wafer-scale Lassena X-ray image sensor.

“We’ve been involved in several other projects detecting signals from very low radiation sources. Although these have resolved information to a promising level, they’re not quite there yet,” said Dan Cathie, CEO at vivaMOS. “We know the sensor is best-in-class on noise performance and have committed to pursuing it further to see if a product can be developed through this SPRINT ultra-low noise optical astronomy project."

VivaMOS presentation in CERN in 2019 discloses some parameters of the company's Lassena sensor:


Thanks to MN for the link!

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Arrow and Analog Devices propose to use its ToF camera solution in baby monitors:


ADI also publishes a nice article dated by Dec 2019 and summarizing the company's experience with continuous wave and pulsed ToF systems:

Advantages of Continuous-Wave Systems:

• For applications that do not have high precision requirements, a CW system may be easier to implement than a pulse-based system in that the light source does not have to be extremely short, with fast rising/falling edges, though it is difficult to reproduce a perfect sinusoidal wave in practice. However, if precision requirements become more stringent, higher frequency modulation signals will become necessary and may be difficult to implement in practice.
• Due to the periodicity of the illumination signal, any phase measurement from a CW system measurement will wrap around every 2π, meaning that there will be an aliasing distance. For a system with only one modulation frequency, the aliasing distance will also be the maximum measurable distance. To counteract this limitation, multiple modulation frequencies can be used to perform phase unwrapping, wherein the true distance of an object can be determined if two (or more) phase measurements with different modulation frequencies agree on the estimated distance. This multiple modulation frequency scheme can also be useful in reducing multipath error, which occurs when the reflected light from an object hits another object (or reflects internally within the lens) before returning to the sensor, resulting in measurement errors.
• Depending on their configuration, CMOS ToF imagers tend to have more flexibility and faster readout speed, so functions such as region-of-interest (RoI) output are possible.
• Calibrating a CW ToF system over temperature may be easier than that of a pulsed ToF system. As the temperature of a system increases, the demodulation signal and the illumination will shift with respect to each other because of the temperature variation, but this shift will only affect the measured distance with an offset error that is constant over the entire range, with the depth linearity remaining essentially stable.

Disadvantages of Continuous-Wave Systems:

• Though CMOS sensors have higher output data rates compared to that of other sensors, CW sensors require four samples of the correlation function at multiple modulation frequencies, as well as multiframe processing, to calculate depth. The longer exposure time can potentially limit the overall frame rate of the system, or can cause motion blur, which can limit its use to certain types of applications. This higher processing complexity can necessitate an external application processor, which may be beyond the application’s requirements.
• For longer distance measurements or environments with high levels of ambient light, higher continuous optical power (compared to that of pulsed ToF) will become necessary; this continuous illumination from the laser could cause thermal and reliability issues.

Advantages of Pulse-Based ToF Technology Systems:

• Pulse-based ToF technology systems often rely on high energy light pulses emitted in very short bursts during a short integration window. This offers the following advantages:
• It makes it easier to design a system that is robust to ambient light, therefore more conducive to outdoor applications.
• The shorter exposure time minimizes the effect of motion blur.
• The duty cycle of the illumination in a pulse-based ToF system is generally much lower than that of a comparable CW system, thereby offering the following benefits:
• It lowers the overall power dissipation of the system in longer range applications.
• It avoids interference from other pulsed ToF systems by placing the pulse bursts in a different location in the frame from that of the other systems. This can be done by coordinating the placement of the pulses in the frame of the various systems or by using an external photodetector to determine the location of the other system’s pulses. Another method is to dynamically randomize the location of the pulse bursts, which will eliminate the need to coordinate the timing between the various systems, but it will not completely eliminate the interference.
• Since the pulse timing and width do not need to be uniform, different timing schemes can be implemented to enable functions such as wider dynamic range and auto-exposure.

Disadvantages of Pulse-Based ToF Technology Systems:

• Since the pulse width of the transmitted light pulse and the shutter need to be the same, the timing control of the system needs to be highly precise, and a picosecond level of precision may be required depending on the application.
• For maximum efficiency, the illumination pulse width needs to be very short, but with very high power. For this reason, very fast rising/falling edges (less than 1 ns) are required from the laser driver.
• Temperature calibration may be more complicated, compared to that of CW systems since a variation in temperature will affect individual pulse widths, affecting not only the offset and gain, but also its linearity.

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