Archives for December 2020

The Great Wavelength Debate in Automotive LiDARs

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 ON Semi Director of Business Development of SensL Division Bahman Hadji publishes a video "Which Wavelength Will Prevail for Automotive LiDAR – The Great Debate."


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The Great Wavelength Debate in Automotive LiDARs

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 ON Semi Director of Business Development of SensL Division Bahman Hadji publishes a video "Which Wavelength Will Prevail for Automotive LiDAR – The Great Debate."


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Samsung Plans to Leapfrog Sony with New 20nm Process

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JoongAng Ibo: Samsung VP  Yong-in Park has been recently promoted from HR to the System LSI Division Strategic Marketing Manager. One of his first decisions was to convert the remaining DRAM capacity on Line 11 to image sensor manufacturing.

The reason Samsung Electronics is converting its DRAM line to image sensor is that it is building a large-scale new DRAM production facility at the Pyeongtaek plant. The Pyeongtaek plant will mass-produce the 4th generation 10-nano class (1a) DRAM using the EUV process from next year. Due to the massive increase in DRAM production capacity, Hwaseong Line 11, which made 20-nano or higher-class DRAM, will be converted into an image sensor for line efficiency.

The newspaper says that (in Microsoft translation) "Sony is still more of ahead in its optical ability to convert light into images. Apple and Huawei have been using Sony products instead of using Samsung image sensors."

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2020 Acquisitions & IPOs

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As 2020 nears its end, there was a number of image sensor companies acquisitions:

  1. Smartsens acquired Allchip (automotive image sensors)
  2. Nordson acquired vivaMOS (X-Ray sensors)
  3. GE Health acquired Prismatic Sensors (X-Ray sensors)
  4. Goodix acquired Dreamchip (digital design services team)
  5. TE Connectivity acquired First Sensor (SPADs, APDs, InGaAs, and p-i-n photodiodes)
  6. LeddarTech acquired VayaVision (sensor fusion and perception software for LiDARs)
  7. Allegro acquired Voxtel (LiDARs)
  8. Seegrid acquired Box Robotics (LiDARs)
  9. ams acquires Osram (adds laser and LED products to complete 3D sensing portfolio)
  10. Nuvoton acquired Panasonic semiconductor business (including image sensor and stake in TPSCo fab)
  11. Jenoptik acquired Trioptics (camera module test and measurement equipment)
  12. Sony acquired Insightness (event-driven sensors)
  13. Celepixel was acquired by Will Semiconductor (event-driven sensors)
There was a number of IPO announcements, although not all of the deals are closed till the end of the year:
  1. Galaxycore (mobile sensors)
  2. Velodyne (LiDAR, merger with SPAC)
  3. Luminar (LiDAR, merger with SPAC)
  4. Aeva (LiDAR, merger with SPAC)
  5. Innoviz (LiDAR, merger with SPAC)
  6. Ouster (LiDAR, merger with SPAC)

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The Richest Man in China’s Semiconductor Industry is "Image Sensor Man"

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Halo Finance, DayDayNews: Will Semiconductor chairman and Omnivision CEO Renrong Yu is the richest man in China semiconductor industry. Will Semi is a mother company of Omnivision, Superpix, and Celepixel.

This year, Renrong Yu is ranked 65th on the Forbes China Rich List with a wealth of 51.38 billion yuan ($7.86 billion), an increase of 21.12 billion yuan over the last year. Compared with 2017, the value has increased by nearly 15 times.

On May 4, 2017, at IPO time, the stock price of Will Semi shares was 7 yuan. On December 25 this year, the stock price of Weir shares was 220 yuan, with a total market value of 190.872 billion. The stock price has increased by more than 30 times in 3.5 years.

Will Semi shares have become a "dark horse" with a market value of 100 billion, thanks to the "snake swallowing elephant" acquisition of Beijing Omnivision. It is worth mentioning that in 2018, when Will Semi decided to acquire Omnivision  at a price of 13 billion yuan, Omnivision's total assets were almost 5 times that of Will's and its net assets were nearly 8 times.

Renrong Yu has graduated from Radio Department of Tsinghua University in 1990. He belongs to the group of alumni of this University that many Chinese semiconductor executives originating from. The incomplete list includes Zhao Lixin, founder of Galaxycore Microelectronics, Zhao Weiguo, founder of Tsinghua Unigroup, Shu Qingming, one of the founders of GigaDevice, Feng Chenhui, co-founder of Maxscend Microelectronics, and Zhao Lidong, founder of Enflame Technology, all studied at Tsinghua University Radio Department in 1985-1990.

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Silicon Integrated Raises $25M in Round B

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I missed this announcement in June 2020. Chinese ToF sensor company Silicon Integrated raised a RMB180M ($25.28M) series B round of financing led by CTC Capital.

Silicon Integrated develops ToF sensor chips and 3D vision solutions, and has already launched mature products. In March 2020, the company has released a BSI ToF sensor chip with independent intellectual property rights. The chip can be widely used in smartphones, face recognition, machine vision and other scenes which require high-performance 3D sensing and imaging effects.

Zhang Xingchen, partner at Source Code Capital, said: "3D sensor chips and modules represented by ToF are becoming a new generation of technological infrastructure. Unlike traditional chip design companies, Silicon Integrated has the ability to define and differentiate hardware through software algorithms, which will promote them to stand out in this field."

Proceeds of the round will be used to expand mass production of BSI ToF products, and the development of lidar, optical sensing and multi-sensing fusion technologies.


The company's first ToF product family SIF2X10 features:
  • HVGA (480 x 360) resolution for SIF2310 and VGA (640 x 480) resolution for SIF2610
  • Back-side illumination
  • Ambient light immunity
  • Compatible with 850nm/940nm LED/VCSEL light source
  • QE>30% at 940nm
  • Up to 100MHz modulation frequency
  • 240fps raw data frame rate
  • Region of interest (ROI) function
  • Absolute accuracy < 1% up to 5m
  • Global shutter
  • Opto-package
Silicon Integrated presents a set of pictures (raw data without correction and processing) taken by SIF2310 with a 940nm light source, an average light source power of 140mw, and a target distance of 2m:


According to South China Morning Post, Silicon Integrated's co-founders Rui Quan and CEO Liu Deheng studied engineering at Delft University of Technology in The Netherlands and both landed jobs at Dutch semiconductor companies after graduating.

Liu worked as a research engineer for Philips in Eindhoven for two years while Quan was a senior analogue design engineer at NXP Semiconductors for four years.

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Silicon Integrated Raises $25M in Round B

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I missed this announcement in June 2020. Chinese ToF sensor company Silicon Integrated raised a RMB180M ($25.28M) series B round of financing led by CTC Capital.

Silicon Integrated develops ToF sensor chips and 3D vision solutions, and has already launched mature products. In March 2020, the company has released a BSI ToF sensor chip with independent intellectual property rights. The chip can be widely used in smartphones, face recognition, machine vision and other scenes which require high-performance 3D sensing and imaging effects.

Zhang Xingchen, partner at Source Code Capital, said: "3D sensor chips and modules represented by ToF are becoming a new generation of technological infrastructure. Unlike traditional chip design companies, Silicon Integrated has the ability to define and differentiate hardware through software algorithms, which will promote them to stand out in this field."

Proceeds of the round will be used to expand mass production of BSI ToF products, and the development of lidar, optical sensing and multi-sensing fusion technologies.


The company's first ToF product SIF2X10 features:
  • HVGA (480 x 360) resolution for SIF2310 and VGA (640 x 480) resolution for SIF2610
  • Back-side illumination
  • Ambient light immunity
  • Compatible with 850nm/940nm LED/VCSEL light source
  • QE>30% at 940nm
  • Up to 100MHz modulation frequency
  • 240fps raw data frame rate
  • Region of interest (ROI) function
  • Absolute accuracy < 1% up to 5m
  • Global shutter
  • Opto-package
Silicon Integrated presents a set of pictures (raw data without correction and processing) taken by SIF2310 with a 940nm light source, an average light source power of 140mw, and a target distance of 2m:


According to South China Morning Post, Silicon Integrated's co-founders Rui Quan and CEO Liu Deheng studied engineering at Delft University of Technology in The Netherlands and both landed jobs at Dutch semiconductor companies after graduating.

Liu worked as a research engineer for Philips in Eindhoven for two years while Quan was a senior analogue design engineer at NXP Semiconductors for four years.

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Global TCAD Solutions for CIS

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Global TCAD Solutions GmbH, a spin-off from Vienna University of Technology (TU Wien), Austria, presents its tools for CIS pixel simulations:

One common type of APS cell consists of a Pinned Photodiode (PPD) with four NMOS transistors. Such structure can be Backside Illuminated (BSI) or use a transfer gate (TG) transistor with vertical channel for more compact pixels. This produces a 3D cell structure, with:
  1. A pinned photodiode (PPD),
  2. adjacent Transfer Gate (TG) transistor and Floating Diffusion (FD) region,
  3. a readout circuit, usually consisting of
    Source Follower Attenuator (SFA)
    Reset (RST)
    Row Select (RS) transistors

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2-stage LOFIC Sensor with 120dB DR

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IEEE TED publishes an open access paper "An Over 120 dB Single Exposure Wide Dynamic Range CMOS Image Sensor With Two-Stage Lateral Overflow Integration Capacitor" by Yasuyuki Fujihara, Maasa Murata, Shota Nakayama, Rihito Kuroda, and Shigetoshi Sugawa from Tohoku University. It appears to be a version of an earlier EI 2020 paper.

"This article presents a prototype linear response single exposure CMOS image sensor with two-stage lateral overflow integration capacitors (LOFIC) exhibiting over the 120-dB dynamic range (DR) with 11.4 Me − full well capacity (FWC) and maximum signal-to-noise ratio (SNR) of 70 dB. The measured SNR at all switching points were over 35 dB thanks to the proposed two-stage LOFIC."

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Sony Article about Awards for Stacked Sensors

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Sony publishes an article about Taku Umebayashi who has been awarded by Medal with Purple Ribbon, one of the medals of honor granted by the Japanese government in April 2020. He also received a number of other awards:

"The Medal with Purple Ribbon is awarded in recognition of outstanding inventions and discoveries in science and technology and excellent achievements in the academic, sports and arts fields. It is conferred twice a year in the spring and autumn. Umebayashi received this medal of honor for his accomplishments in the development of the stacked CMOS image sensor structure.

For this development, he received the Prime Minister’s Award of the National Commendation for Invention for fiscal 2016 (awarded by Japan Institute of Invention and Innovation).

On the recommendation of the institute, he was given the Awards for Science and Technology (Development Category) of the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology in fiscal 2018.

The institute also endorsed Umebayashi for the Medal with Purple Ribbon awarded this time."

Taku Umebayashi says:

"First of all, I would like to say that I am very delighted to have received such a renowned medal. I would not have been able to receive it without the cooperation of many fellow workers, so I would like to once again extend my appreciation to them here. I believe I was granted the medal on behalf of Sony.

The technology for which I received the medal is the stacked CMOS image sensor. This structure came to my mind when I was first assigned to the image sensor section in 2008. Loaded with various functions, the sensor has a structure that is compact and suitable for mass production. I presented the idea directly to the boss and received a green light to proceed with the development.

The development of the sensor thus started on impulse. It was put on the market and ended up being well received, but I remember having a very hard time for the first two years because I was always asked whether it would really sell. It took long to establish evidence and the development project had not progressed so well. However, I think it was very good that I took on a challenge that nobody had attempted before and eventually made a product that had not existed in the world. I believe Sony’s corporate culture, which allowed me to take on such a challenge provides a good organizational climate, and served as a driving force behind my reception of the medal.

I was given the medal for this idea, as I was the first to protect it with a patent. Thinking of this, I believe every engineer has a chance to receive such an honor if they write a good patent and attempt to put it into practice. I hope they will take on new challenges and keep creating new things."

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Sony Article about Awards for Stacked Sensors

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Sony publishes an article about Taku Umebayashi who has been awarded by Medal with Purple Ribbon, one of the medals of honor granted by the Japanese government in April 2020. He also received a number of other awards:

"The Medal with Purple Ribbon is awarded in recognition of outstanding inventions and discoveries in science and technology and excellent achievements in the academic, sports and arts fields. It is conferred twice a year in the spring and autumn. Umebayashi received this medal of honor for his accomplishments in the development of the stacked CMOS image sensor structure.

For this development, he received the Prime Minister’s Award of the National Commendation for Invention for fiscal 2016 (awarded by Japan Institute of Invention and Innovation).

On the recommendation of the institute, he was given the Awards for Science and Technology (Development Category) of the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology in fiscal 2018.

The institute also endorsed Umebayashi for the Medal with Purple Ribbon awarded this time."

Taku Umebayashi says:

"First of all, I would like to say that I am very delighted to have received such a renowned medal. I would not have been able to receive it without the cooperation of many fellow workers, so I would like to once again extend my appreciation to them here. I believe I was granted the medal on behalf of Sony.

The technology for which I received the medal is the stacked CMOS image sensor. This structure came to my mind when I was first assigned to the image sensor section in 2008. Loaded with various functions, the sensor has a structure that is compact and suitable for mass production. I presented the idea directly to the boss and received a green light to proceed with the development.

The development of the sensor thus started on impulse. It was put on the market and ended up being well received, but I remember having a very hard time for the first two years because I was always asked whether it would really sell. It took long to establish evidence and the development project had not progressed so well. However, I think it was very good that I took on a challenge that nobody had attempted before and eventually made a product that had not existed in the world. I believe Sony’s corporate culture, which allowed me to take on such a challenge provides a good organizational climate, and served as a driving force behind my reception of the medal.

I was given the medal for this idea, as I was the first to protect it with a patent. Thinking of this, I believe every engineer has a chance to receive such an honor if they write a good patent and attempt to put it into practice. I hope they will take on new challenges and keep creating new things."

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ADI Unveils 1MP 3.5um Pixel BSI ToF Sensor

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Analog Devices unveils what appears to be the first fruit of cooperation with Microsoft ToF group (former Canesta). The ADSD3100 sensor targets smartphones, AR/VR systems, and machine vision applications in logistics, inventory, industrial, and consumer fields.

The new sensor features:

  • 1024 (horizonal) × 1024 (vertical) pixel array
  • 3.5 μm × 3.5 μm square pixels
  • 1/3.6 inch optical format
  • BSI
  • Depth and intensity imaging
  • 4-wire SPI or 2-wire I2C serial interface
  • Die size: 5.364 mm × 9.799 mm
  • MIPI CSI-2 Tx interface with support for 1, 2, or 4 data lanes, programmable up to 1.5 Gbps per lane
  • Dual, 3.3 V and 1.27 V external supplies, 1.8 V I/O section


For comparison, below are the figures from Microsoft ISSCC 2018 presentation:

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BrightWay Presents is Automotive Gated Imaging Camera

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BrightWay Imaging publishes its presentation at Autosens Brussels this year:


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Credit Suisse on Smartphone Camera Market

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IFNews quotes Credit Suisse market report saying that "nearly all 5G smartphones hitting the market continue to feature at least 3 cameras. However, the ratio of quad-camera models has declined (from 62% in Apr–Jun 2020 to 45% in Jul–Sep 2020), while the ratio of triple-camera models has risen (from 38% to 50%). This is because shipments of mid-market smartphones increased. Quad-cam products continue to account for a high proportion of sales in the premium segment (USD800 models and above). In addition, the quad-cam ratio is still rising for 4G and earlier generation smartphones."


Credit Suisse estimates that CIS production capacity increased by about 14.5% YoY in 2020 and expects it to rise by another 12% in 2021.


According to Pingan Securities, smartphones in 2019 had 3.1 cameras on average, and this number is forecasted to increase to 4.3 in 2021. The market size of mobile phone CIS in 2019 was $13.6B, and is expected to reach $21.8B in 2022 at YoY growth rate of 17%.

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Huawei Unveils its First Automotive LiDAR and Begins Pilot Production

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CnTechPost, GizChina, InfNews, Huawei: Huawei announces its first automotive LiDAR product. Few key points from the announcement:

  • 120 x 25 deg FOV
  • 0.25 x 0.26 deg resolution
  • 96 lines
  • 150m range at 10% target reflectivity
  • 200m range at 50% target reflectivity
  • BAIC (Beijing Automotive) is the first customer
  • Huawei has built a pilot production line with capacity of 100K units per year
  • The development has started in 2016 and took 4 years
Now, an interesting question is whether Huawei succeeds to capture a major LiDAR player position, like it did in smartphones?

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Hot, Cold, Warm, and Cool Pixels in Event-Driven Cameras

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Australian National University paper "Event Camera Calibration of Per-pixel Biased Contrast Threshold" by Ziwei Wang, Yonhon Ng, Pieter van Goor, and Robert Mahony discusses pixel mismatch issues in event-driven cameras:

  • Hot Pixels are pixels that have lower threshold values than the assumed value. This means that both positive and negative events are generated more often than expected.
  • Cold Pixels are pixels that have higher threshold values than the assumed value. This means that both positive and negative events are generated less often than expected.
  • Warm Pixels are pixels that have negative bias values. This means positive events are triggered more often, and negative events are triggered less often than expected.
  • Cool Pixels are pixels that have positive bias values. This means negative events are triggered more often, and positive events are triggered less often than expected.

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BMW In-cabin Monitoring with Melexis ToF Camera

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Melexis publishes a video on its Autosens-Detroit presentation ofToF in-cabin monitoring camera in BMW cars:

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Ouster Goes Public via Merger with SPAC

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BusinessWire: San Francisco-based LiDAR startup Ouster is said to close a deal to go public at a about $1.9B valuation through a merger with SPAC Colonnade Acquisition Corp. Up to now, Ouster has raised $142M in the previous investment rounds.

The new transaction is expected to provide up to $300M in gross proceeds, comprised of Colonnade Acquisition Corp.’s $200M of cash held in trust and a $100M fully committed common stock PIPE.

The company's Investor Presentation talks about its LiDAR sales and forecasts:

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2021 International Image Sensor Workshop Call for Papers

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The next International Image Sensor Workshop (IISW) is going to be an on-line event on Sept. 20-24, 2021. The First Call for Papers has been published on International Image Sensor Society web site:

"The 2021 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. Now in its 35th year, the workshop 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 its tradition, the 2021 workshop will emphasize an open exchange of information among participants.

Submission of abstracts:

An abstract should consist of a single page of maximum 500-words text with up to two pages of illustrations, and include authors’ name(s) and affiliation, mailing address, telephone and e-mail address. The deadline for abstract submission is April 17th, 2021 (CST).

Please visit http://imagesensors.org/CFP2021 for the abstract and paper submission procedures.

Abstracts will be considered on the basis of originality and quality. High quality papers on work in progress are also welcome. Abstracts will be reviewed confidentially by the Technical Program Committee and the IISS Board.

Authors will be notified of the acceptance of their abstract by June 3th, 2021.
Final-form 4-page paper submission date is August 6th, 2021.
Presentation material submission date is September 13th, 2021.

Location and format: 

The IISW 2021 is planned to be held Sept 20-24th. Given the outlook of the pandemic situation and related travel restrictions, the workshop is expected to be an online event, which will be supported by several initiatives to preserve its interactive and open atmosphere. The workshop will not be delayed: in any case the selected papers will be presented in September 2021. More details on the format will be provided in February 2021 with the final call for papers."

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Review of MoS2 Based Photodetectors

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Royal Society of Chemistry publishes "A review of molybdenum disulfide (MoS2) based photodetectors: from ultra-broadband, selfpowered to flexible devices" by Hari Singh Nalwa from Advanced Technology Research, CA.

"Two-dimensional transition metal dichalcogenides (2D TMDs) have attracted much attention in the field of optoelectronics due to their tunable bandgaps, strong interaction with light and tremendous capability for developing diverse van der Waals heterostructures (vdWHs) with other materials. Molybdenum disulfide (MoS2) atomic layers which exhibit high carrier mobility and optical transparency are very suitable for developing ultra-broadband photodetectors to be used from surveillance and healthcare to optical communication. This review provides a brief introduction to TMD-based photodetectors, exclusively focused on MoS2-based photodetectors. The current research advances show that the photoresponse of atomic layered MoS2 can be significantly improved by boosting its charge carrier mobility and incident light absorption via forming MoS2 based plasmonic nanostructures, halide perovskites–MoS2 heterostructures, 2D–0D MoS2/quantum dots (QDs) and 2D–2D MoS2 hybrid vdWHs, chemical doping, and surface functionalization of MoS2 atomic layers. By utilizing these different integration strategies, MoS2 hybrid heterostructure-based photodetectors exhibited remarkably high photoresponsivity raging from mA W^−1 up to 1010 A W^−1, detectivity from 1e7 to 1e15 Jones and a photoresponse time from seconds (s) to nanoseconds (1e−9 s), varying by several orders of magnitude from deep-ultraviolet (DUV) to the long-wavelength infrared (LWIR) region. The flexible photodetectors developed from MoS2-based hybrid heterostructures with graphene, carbon nanotubes (CNTs), TMDs, and ZnO are also discussed. In addition, strain-induced and self-powered MoS2 based photodetectors have also been summarized. The factors affecting the figure of merit of a very wide range of MoS2-based photodetectors have been analyzed in terms of their photoresponsivity, detectivity, response speed, and quantum efficiency along with their measurement wavelengths and incident laser power densities. Conclusions and the future direction are also outlined on the development of MoS2 and other 2D TMD-based photodetectors."

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100Mfps HDR Sensor

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University of Strasbourg and CNRS, France, publishes a paper "A High Dynamic Range High Speed Pixel Operating at 100 Million Frames Per Second" by Mathieu Hugoud, Wilfried Uhring, Jean-Baptiste Kammerer, and Jean-Bapstiste Schell presented at 2020 18th IEEE International New Circuits and Systems Conference (NEWCAS).

"The burst imaging concept is a specific imaging method than allows achieving a pixel rate of about 1 Tera pixel per second. This huge data rate can be reached by storing the video frames within the sensor, thus circumventing the bottleneck of the input/output of the sensor. Consequently, a frame rate of several Mega frames per second (Mfps) can be obtained and the use of a fast pixel front end is mandatory. In this paper, a pixel front able to operate at a frame rate of 100 Mfps is proposed. Based on a current mirroring integration approach, it offers a high dynamic range feature compatible with the record of the very fast moving object without blurring effect. The feature is carried out by mirroring in parallel the photocurrent into several integration capacitances. The pixel consumption is as low as 12 μW for one single gain branch at 10 Mfps and 118μW at a frame rate of 100 Mpfs."

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Review of ToF Approaches

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Arxiv.org paper "An Overview of Depth Cameras and Range Scanners Based on Time-of-Flight Technologies" by Radu Horaud, Miles Hansard, Georgios Evangelidis, and Clement Menier from INRIA Grenoble, Queen Mary University of London, and 4D View Solutions mostly repeats 2016 paper published by Springer.

"Time-of-flight (TOF) cameras are sensors that can measure the depths of scene-points, by illuminating the scene with a controlled laser or LED source, and then analyzing the reflected light. In this paper, we will first describe the underlying measurement principles of time-of-flight cameras, including: (i) pulsed-light cameras, which measure directly the time taken for a light pulse to travel from the device to the object and back again, and (ii) continuous-wave modulated-light cameras, which measure the phase difference between the emitted and received signals, and hence obtain the travel time indirectly. We review the main existing designs, including prototypes as well as commercially available devices. We also review the relevant camera calibration principles, and how they are applied to TOF devices. Finally, we discuss the benefits and challenges of combined TOF and color camera systems."

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Intel Introduces "Visual Sensing Controller" for PC

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Intel presents a new addition to its EVO PC platform:

"A new platform addition we’re excited to unveil today is the Intel Visual Sensing Controller (codenamed “Clover Falls”), a secure companion chip that helps make PCs more smart and secure through the power of Intel artificial intelligence. This companion module will first arrive in commercial systems, bringing new low-power capabilities to the PC and helping it sense and adapt to its surroundings. For example, the module could help the system automatically adjust display brightness after detecting user presence."

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Image Sensors at 2021 Electronic Imaging Conference: 0.7-0.8um Pixels, Under-Display Cameras, More…

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EI 2021 will be held on-line and span over two weeks from January 18 to 28. The Image Sensors and Systems track features 10 image sensor papers, 4 of them come from Samsung. Out of these 4 papers, two are devoted to under-display smartphone cameras:

  1. 0.8 um color pixels with wave-guiding structures for low optical crosstalk image sensors
    Y. Chang, C. Lin, Z. Tu, J. Lee, S. Cheng, C. Wu, K. Wu, H. Tsai,
    VisEra Technologies Company, Hsinchu City , Taiwan
  2. 2D, or not 2D, that is the question: How 3D-stacking is shaping the future of SPAD image sensors
    E. Charbon,
    École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
  3. A 64M CMOS image sensor using 0.7µm pixel with high FWC and switchable conversion gain
    J. Jung,
    Omnivision Technologies, Inc., Campbell, California, United States
  4. A low-voltage 0.7 µm pixel with 6000 e- full-well capacity for a low-power CMOS image sensor
    S. Lee, S. Cha, D. Jang, M. Kim, H. Lee, N. Lee, S. Kim, K. Oh, D. Lee, S. Hong, H. Lee, S. Oh, D. Park, Y. Kim, J. Ahn,
    System LSI, Samsung Electronics DS, Yongin, Giheung-gu, Republic of Korea
  5. A proposal of analog correlated multiple sampling with high density capacitors for low noise CMOS image sensors
    S. Kamoshita, M. Suzuki, R. Kuroda, S. Sugawa,
    Tohoku University, Sendai, Miyagi, Japan
  6. A single chip PPG sensor with enhanced IR sensitivity for low power and small size
    J. Lim, J. Kim, L. Yan, H. Noh, J. Pyo, J. Yun, S. Jung, D. Seol, K. Lee, T. NAGANO, J. Ahn,
    Pixel development team, Samsung Electronics Device Solutions, Hwaseong, Republic of Korea;
    T. Jung,
    Samsung Electronics, Yongin-city, Republic of Korea
  7. Computational photography at the point of capture
    M. Levoy,
    Adobe Inc., San Francisco, California, United States
  8. Deep-trench isolation: The holy grail for image sensors?
    A. Theuwissen,
    Harvest Imaging, Bree, Belgium;
    EE, TU Delft, Delft , Netherlands
  9. Under display camera image recovery through diffraction compensation
    J. Lee, Y. Choi, H. Lee, E. Heo, D. Lim, G. Lee, S. Song,
    Samsung Electronics, Hwaseong, Republic of Korea
  10. Under display camera Quad Bayer raw image restoration using deep learning
    I. Kim, Y. Choi, H. Ko, D. Lim, Y. Seo, J. Lee, G. Lee, E. Heo, S. Song, S. Lim,
    S.LSI, Samsung, Hwaseong, Gyeonggi-do, Republic of Korea

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Advantest to Test 64 CIS Simultaneously at 4.8Gbps Data Rate Each

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GlobenewswireAdvantest launches a new high-speed CMOS image capture module for its T2000 test platform that enables parallel, 64-site testing of both D-PHY and C-PHY devices for the smart phone market. The new T2000 4.8-Gbps CMOS image capture module, known as the 4.8GICAP, is designed to efficiently transfer data from CIS to the T2000 tester’s image processor engine (IPE). It is the first mass-produced test solution to achieve a maximum data rate of 3.5 Gsps for C-PHY version 1.2 devices as well as the industry’s fastest capture speed of 4.8 Gbps for D-PHY version 2.1 devices.

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Corning-Varioptics Liquid Lens Extends Iris Recognition Distance to Several Meters

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Corning publishes a white paper "Improving iris recognition with liquid lens technology." The main highlights are:

  • Liquid lens-based AF allow the optical system to maximize the sharpness of an image. This compact, low-cost, and low-power solution extends the iris reading distance from a few millimeters to several meters.
  • COVID-19 has escalated the already growing demand for non-contact identification systems.
  • Liquid lenses possess a fast response time, as low as 10 ms. This feature enables auto-focus and continuous focus for biometric applications.

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Oregon University Proposes Event-Driven Pixel with No Transistors

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AIP Applied Physics Letters publishes Oregon State University paper "A perovskite retinomorphic sensor" by Cinthya Trujillo Herrera and John G. Labrama.

"We found that capacitors based on metal halide perovskites will output a brief voltage spike in response to changes in incident light intensity, but output zero voltage under constant illumination. Such a sensor is not only optimized for use with spiking neuromorphic processors but also anticipated to have broad appeal from fields such as light detection and ranging, autonomous vehicles, facile recognition, navigation, and robotics."

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ON Semi Presents its HDR Sensors

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ON Semi video by Sergey Velichko presents the company's automotive HDR sensors:

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Velodyne Explains its Solid State LiDAR Design

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AutonmouStuff publishes Velodyne webinar explaining its new Velarray H800 operation:


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AIStorm Raises $16M in Round B to Commercialize its AI-in-Sensor Chip

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BusinessWireAIStorm has closed $16M in a Series B financing round from strategic investors that include AsusTek, Egis Technology, Knowles Corporation, Meyer Corporation, and Senvest Management, a New York-based venture capital firm. In 2019, AIStorm raised $13.2M in Round A funding.

AIStorm’s approach is the only technology that allows the sensor to couple directly to popular convolutional neural networks. This allows AIStorm to deliver true, template-based ‘always-on’ at the edge—at prices that deep-submicron digital competitors cannot match for the same performance. This is a winning formula in the highly competitive IoT sector,” said David Schie, CEO of AIStorm.

AIStorm’s charge-domain processing is said to accept charge directly from the sensor, such as electrons from a pixel, and multiplies that charge directly. AIStorm’s partners benefit from an AI-at-the-edge technology that is scalable, offers MAC efficiencies up to several thousand TOPS per watt, and works with conventional tool flows.

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