LiDAR with Entangled Photons

EPFL and Glasgow University publish an Optics Express paper "Light detection and ranging with entangled photons" by Jiuxuan Zhao, Ashley Lyons, Arin Can Ulku, Hugo Defienne, Daniele Faccio, and Edoardo Charbon.

"Single-photon light detection and ranging (LiDAR) is a key technology for depth imaging through complex environments. Despite recent advances, an open challenge is the ability to isolate the LiDAR signal from other spurious sources including background light and jamming signals. Here we show that a time-resolved coincidence scheme can address these challenges by exploiting spatio-temporal correlations between entangled photon pairs. We demonstrate that a photon-pair-based LiDAR can distill desired depth information in the presence of both synchronous and asynchronous spurious signals without prior knowledge of the scene and the target object. This result enables the development of robust and secure quantum LiDAR systems and paves the way to time-resolved quantum imaging applications."

Polarization Event Camera

AIT Austrian Institute of Technology, ETH Zurich, Western Sydney University, and University of Illinois at Urbana-Champaign publish a pre-print paper "Bio-inspired Polarization Event Camera" by Germain Haessig, Damien Joubert, Justin Haque, Yingkai Chen, Moritz Milde, Tobi Delbruck, and Viktor Gruev

"The stomatopod (mantis shrimp) visual system has recently provided a blueprint for the design of paradigm-shifting polarization and multispectral imaging sensors, enabling solutions to challenging medical and remote sensing problems. However, these bioinspired sensors lack the high dynamic range (HDR) and asynchronous polarization vision capabilities of the stomatopod visual system, limiting temporal resolution to ~12 ms and dynamic range to ~ 72 dB. Here we present a novel stomatopod-inspired polarization camera which mimics the sustained and transient biological visual pathways to save power and sample data beyond the maximum Nyquist frame rate. This bio-inspired sensor simultaneously captures both synchronous intensity frames and asynchronous polarization brightness change information with sub-millisecond latencies over a million-fold range of illumination. Our PDAVIS camera is comprised of 346x260 pixels, organized in 2-by-2 macropixels, which filter the incoming light with four linear polarization filters offset by 45 degrees. Polarization information is reconstructed using both low cost and latency event-based algorithms and more accurate but slower deep neural networks. Our sensor is used to image HDR polarization scenes which vary at high speeds and to observe dynamical properties of single collagen fibers in bovine tendon under rapid cyclical loads."

SWIR Startup Trieye Collaborates with Automotive Tier 1 Supplier Hitachi Astemo

PRNewswire:  TriEye announces collaboration with Hitachi Astemo, Tier 1 automotive supplier of world-class products. Trieye's SEDAR (Spectrum Enhanced Detection And Ranging), has also received significant recognition when it was named CES 2022 Innovation Award Honoree, in the Vehicle Intelligence category.

"We believe that TriEye's SEDAR can provide autonomous vehicles with ranging and accurate detection capabilities that are needed to increase the safety and operability under all visibility conditions," says John Nunneley, SVP Design Engineering, Hitachi Astemo Americas, Inc.

SeeDevice Focuses on SWIR Sensing and Joins John Deere's 2022 Startup Collaborator Program

GlobeNewswire: Deere & Company announces the companies that will be part of the 2022 cohort of their Startup Collaborator program, including SeeDevice. This program launched in 2019 to enhance and deepen its interaction with startup companies whose technology could add value for John Deere customers.

SeeDevice is said to be a pioneer in CMOS-based SWIR image sensor technology, the first of its kind, based in quantum tunneling and plasmonic phenomena in standard logic CMOS process. A fabless quantum image sensor licensing company, Seedevice will collaborate with John Deere to implement its Quantum Photo-Detection-- QPD CMOS SWIR image sensor technology for agricultural and industrial applications and solutions. SeeDevice's unique technology is capable of broad-spectrum detection ability from a single CMOS pixel to detect spectral wavelengths from visual and near infrared -NIR (~400nm - 1,100nm), up to short-wave infrared -SWIR (~1,600nm), manufactured on a normal logic CMOS process.

"We're very honored to be invited to Deere's Start-up Collaborator program. The feasibility of a single-sensor solution from visible to SWIR wavelengths opens the doors to new industrial use-cases previously not possible due to the limitations of performance, cost, power, and size. To our knowledge, it is the first in the industry to achieve this level of performance, so we're excited to be working with John Deere to enhance next-generation image sensing devices with quantum sensing," said Thomas Kim, CEO and Founder of SeeDevice. 

SeeDevice has redesigned its website emphasizing the SWIR sensitivity of its image sensors:

Omnivision Unveils its New Logo

Omnivision publishes short videos explaining its new logo:

UV Sensors in SOI Process

Tower publishes a MDPI paper "Embedded UV Sensors in CMOS SOI Technology" by Michael Yampolsky, Evgeny Pikhay, and Yakov Roizin.

"We report on ultraviolet (UV) sensors employing high voltage PIN lateral photodiode strings integrated into the production RF SOI (silicon on isolator) CMOS platform. The sensors were optimized for applications that require measurements of short wavelength ultraviolet (UVC) radiation under strong visible and near-infrared lights, such as UV used for sterilization purposes, e.g., COVID-19 disinfection. Responsivity above 0.1 A/W in the UVC range was achieved, and improved blindness to visible and infrared (IR) light demonstrated by implementing back-end dielectric layers transparent to the UV, in combination with differential sensing circuits with polysilicon UV filters. Degradation of the developed sensors under short wavelength UV was investigated and design and operation regimes allowing decreased degradation were discussed. Compared with other embedded solutions, the current design is implemented in a mass-production CMOS SOI technology, without additional masks, and has high sensitivity in UVC."

Nanostructure Modifiers for Pixel Spectral Response

University of California – Davis and W&WSens publish an Arxiv.org paper "Reconstruction-based spectroscopy using CMOS image sensors with random photon-trapping nanostructure per sensor" by Ahasan Ahamed, Cesar Bartolo-Perez, Ahmed Sulaiman Mayet, Soroush Ghandiparsi, Lisa McPhillips, Shih-Yuan Wang, M. Saif Islam.

"Emerging applications in biomedical and communication fields have boosted the research in the miniaturization of spectrometers. Recently, reconstruction-based spectrometers have gained popularity for their compact size, easy maneuverability, and versatile utilities. These devices exploit the superior computational capabilities of recent computers to reconstruct hyperspectral images using detectors with distinct responsivity to different wavelengths. In this paper, we propose a CMOS compatible reconstruction-based on-chip spectrometer pixels capable of spectrally resolving the visible spectrum with 1 nm spectral resolution maintaining high accuracy (>95 %) and low footprint (8 um x 8 um), all without the use of any additional filters. A single spectrometer pixel is formed by an array of silicon photodiodes, each having a distinct absorption spectrum due to their integrated nanostructures, this allows us to computationally reconstruct the hyperspectral image. To achieve distinct responsivity, we utilize random photon-trapping nanostructures per photodiode with different dimensions and shapes that modify the coupling of light at different wavelengths. This also reduces the spectrometer pixel footprint (comparable to conventional camera pixels), thus improving spatial resolution. Moreover, deep trench isolation (DTI) reduces the crosstalk between adjacent photodiodes. This miniaturized spectrometer can be utilized for real-time in-situ biomedical applications such as Fluorescence Lifetime Imaging Microscopy (FLIM), pulse oximetry, disease diagnostics, and surgical guidance."

Image Sensor Facts for Kids

Kiddle, an encyclopedia for kids, publishes a page about image sensors:

Recent Videos: EnliTech, IPVM, Scantinel, Infiray, Omron, Ibeo

EnliTech presents its CIS wafer testing solutions:

IPVM publishes "Intro to Surveillance Cameras:"

   

Scantinel presents its FMCW LiDAR:

Infiray presents bright future for thermal cameras in ADAS applications:

Guide Sensmart presents the world's first smartphone thermal camera with AF:

Omron publishes a webinar about its QVGA ToF sensor capable of 100klux ambient light operation:

Ibeo publishes a webinar about its SPAD-based automotive "Digital LiDAR:"

Bankrupt HiDM is Acquired by Rongxin Semiconductor

JW Insights reports that Rongxin Semiconductor acquired through an auction the bankrupt HiDM (Huaian Imaging Device manufacturing Corporation) in Huaian, Jiangsu province. Rongxin Semiconductor was founded in April 2021 in Ningbo, Jiangsu province. Rongxin paid RMB1.666 billion ($262.1 million) for HiDM assets.

As a private capital, Rongxin’s participation in wafer manufacturing by rescuing HiDM represents a new source of solutions to failed mega semiconductor projects that had occurred over the last several years. It is also regarded as a new force in improving China’s foundry capacity.

Rongxin mainly focuses on 90-55nm 12-inch chip production lines of CIS and other semiconductors. The company's WLCSP TSV packaging focuses on advanced packaging and testing of CIS products.

RongSemi has formed strategic cooperation partnerships with several companies, including OmniVision. Currently, Rongxin is completing the fab construction and hiring its personnel now. The company needs a total of about 1,500 employees, including 70 management personnel, 650 technical personnel, and 780 production personnel.

EI 2022 Course on Signal Processing for Photon-Limited Imaging

Stanley Chan from Purdue University publishes slides for his 2022 Electronic Imaging short course "Signal Processing for Photon-Limited Imaging." Few slides out of 81: