Lucid Vision Labs discusses EMVA 1288 specs for Sony IMX492

Lucid Vision Labs has released a new video overview of Sony's rolling shutter 47MP IMX492 sensor.

The video discusses quantum efficiency (time stamp 2:02), saturation capacity (3:04), temporal dark noise (3:15), and dynamic range (3:27). It also compares it to some of other higher resolution sensors (31.4MP IMX342, 24.5MP IMX530, 20MP IMX183)

Full EMVA 1288 data is also available on Lucid's product page under the "EMVA 1288 Data" Tab here: https://thinklucid.com/product/atlas10-47mp-imx492/#tab-emva-1288-data

Vayyar Raises Series-E

From TechCrunch:

Vayyar, a company developing radar-imaging sensor technologies, today announced that it raised $108 million in a Series E round led by Koch Disruptive Technologies, with participation from GLy Capital Management, Atreides Management LP, KDT, Battery Ventures, Bessemer Ventures, More VC, Regal Four and Claltech. The round brings Vayyar’s total raised to over $300 million, which CEO Raviv Melamed said is being put toward expanding across verticals and introducing a “family” of machine learning-powered sensor solutions for robotics, retail, public safety and “smart” building products.

“We are pleased and proud to progress our partnership with existing investors including KDT, as well as additional backers which are joining forces with us for the first time,” Melamed said in a statement. “During a challenging period for the global economy, this new funding round is a ringing endorsement of our mission and a clear vote of confidence in the strength of our technology and the strategic agility of our organization.”

Founded in 2011 by Miri Ratner, Naftali Chayat and Melamed, who was previously VP of Intel’s architecture group, Vayyar initially developed its sensor technology to provide an alternative means of screening for early-stage breast cancer. Leveraging MIMO antennas, short for “multiple input, multiple output,” Vayyar’s products can deliver a high-resolution mapping of their surroundings by sending and receiving signals from dozens of antennas.

Vayyar later expanded its “radar-on-chip” technology from healthtech to a number of other sectors, including automotive, senior care, retail, smart home and commercial property. Vayyar sells Vayyar Care, a fall detection system for monitoring people at higher risk of tripping and falling in bedrooms, bathrooms and other living spaces. In the automotive industry, Vayyar offers solutions for collision warnings, parking assistance, adaptive cruise control, seatbelt detection and automatic breaking. And in construction, Vayyar provides a handheld sensor called Walabot for detecting leaky pipes behind walls.

Vayyar competes with Entropix, Photonic Vision, Noitom Technology, Aquifi and ADI, among others, which offer their own flavors of MIMO-based sensors. But the company has long asserted that its software and algorithms set it apart from the competition. Evidently, they were impressive enough to convince Amazon to partner with Vayyar for fall detection on Alexa Together, a subscription service that remotely monitors and assists family members in their homes.

In recent years, Vayyar has entered into customer relationships with brands like Piaggio Group, which will deploy Vayyar’s sensors on some of its forthcoming motorbikes. The company also claims to have supply contracts with automakers from Japan and Vietnam as well as a joint venture agreement with Haier subsidiary HCH Ventures to leverage the latter’s “senior care technology” in China-based businesses.

Signaling ambitions in the Asia-Pacific market in particular, Vayyar noted in a press release that it engaged China International Capital Corporation Limited, a Beijing-based investment company, as its lead financial adviser for the Series E explicitly to “support investor outreach in China.” (One of Vayyar’s newer offices is in China.) Somewhat unusually, Vayyar’s Series E came just under its Seres D, which totaled $109 million. It’s unclear whether the valuation has changed — TechCrunch last reported that Vayyar was valued “north” of $600 million. 

https://techcrunch.com/2022/06/06/imaging-sensor-startup-vayyar-lands-108m-to-fuel-expansion/

In the News: Yole Webcast, Prophesee Software Suite

The CIS market is back to strong growth: Are we at the beginning of the much-awaited sensing era?

Yole will host a webcast on Thursday 16, June 2022

https://www.i-micronews.com/event/the-cis-market-is-back-to-strong-growth-are-we-at-the-beginning-of-the-much-awaited-sensing-era/

The image sensor market struggled through a mixed 2021 but appears to have emerged strongly positioned. Could 2022 be the beginning of strong growth on the back of sensing applications?

In this webcast we will explore what the next few quarters and years hold for the CMOS image sensor (CIS) industry, including market demand, industry revenue and capacity.

This webcast will take a quick look back at 2021 to review the recent history of CIS before focusing on the near and mid-term prospects for the CIS industry. It will also cover market dynamics, supply, and pricing, with particular focus on answering the question, “Are we at the beginning of strong growth on the back of sensing applications?”

Prophesee releases its entire event-based vision software suite for free, including commercial license, further enabling community of thousands of Engineers and Researchers Worldwide

https://www.i-micronews.com/prophesee-releases-its-entire-event-based-vision-software-suite-for-free-including-commercial-license-further-enabling-community-of-thousands-of-engineers-and-researchers-worldwide/

New release of 5X award-winning suite includes a complete set of Machine Learning tools, new key Open-Source modules, ready-to-use applications, code samples and allows for completely free evaluation, development and release of products with the included commercial license.

With this advanced toolkit, engineers can easily develop computer vision applications on a PC for a wide range of markets, including industrial automation, IoT, surveillance, mobile, medical, automotive and more.

“We have seen a significant increase in interest and use of Event-Based Vision and we now have an active and fast-growing community of more than 4,500 inventors using Metavision Intelligence since its launch. As we are opening the event-based vision market across many segments, we decided to boost the adoption of MIS throughout the ecosystem targeting 40,000 users in the next two years. By offering these development aids, we can accelerate the evolution of event-based vision to a broader range of applications and use cases and allow for each player in the chain to add its own value,” said Luca Verre, co-founder and CEO of Prophesee.

Camera Arrays for Large Scale Surveillance

From the journal Light Science and Applications, in a paper titled "A modular hierarchical array camera" X. Yuan et al. write:

Abstract: Array cameras removed the optical limitations of a single camera and paved the way for high-performance imaging via the combination of micro-cameras and computation to fuse multiple aperture images. However, existing solutions use dense arrays of cameras that require laborious calibration and lack flexibility and practicality. Inspired by the cognition function principle of the human brain, we develop an unstructured array camera system that adopts a hierarchical modular design with multiscale hybrid cameras composing different modules. Intelligent computations are designed to collaboratively operate along both intra- and intermodule pathways. This system can adaptively allocate imagery resources to dramatically reduce the hardware cost and possesses unprecedented flexibility, robustness, and versatility. Large scenes of real-world data were acquired to perform human-centric studies for the assessment of human behaviours at the individual level and crowd behaviours at the population level requiring high-resolution long-term monitoring of dynamic wide-area scenes.

Given the potential applications shown (large scale surveillance), it is quite intriguing that the "Ethics Declaration" section of this paper is empty.

Open access link: https://www.nature.com/articles/s41377-021-00485-x

See also: https://image-sensors-world.blogspot.com/2022/06/surveillance-market-and-smartsens.html

Sony Investor Relations Day 2022

Slides from the Imaging and Sensing Solutions Segment from Sony's Investor Relations day:

https://www.sony.com/en/SonyInfo/IR/library/presen/irday/pdf/2022/ISS_E.pdf

Review of Quanta Image Sensors for Ultralow-Light Imaging (IEEE TED June 2022)

[As mentioned in some recent comments on this blog, the latest (vol. 69 no. 6, June 2022) issue of IEEE Transactions on Electron Devices has many interesting papers related to image sensors. I will post summaries here in the coming days.]

In an invited paper in the June 2022 issue of IEEE TED, Jiaju Ma et al. write:

The quanta image sensor (QIS) is a photon counting image sensor that has been implemented using different electron devices, including impact ionization gain devices, such as the single-photon avalanche detectors (SPADs), and low-capacitance, high conversion-gain devices, such as modified CMOS image sensors (CIS) with deep sub-electron read noise and/or low noise readout signal chains. This article primarily focuses on CIS QIS, but recent progress of both types is addressed. Signal processing progress, such as denoising, critical to improving apparent signal-to-noise ratio, is also reviewed as an enabling co-innovation.

https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9768129

Special Issue: Solid State Image Sensors on IEEE TED

My Friend Michael Guidash just informed me that the special issue for solid state image sensors on IEEE Transactions on Electron Devices in now available online.

Here is a link to the table of content: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9780655

The list of papers can be found here: https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=16 

Surveillance market and SmartSens

From DigiTimes Asia news: https://www.digitimes.com/news/a20220527PD203/sensor-surveillance.html

China security surveillance market boom buoys SmartSens

The expanding security surveillance market in China continues to boost the shipments of CMOS image sensor (CIS) chips from Chinese CIS startup SmartSens Technology, which has entered the supply chains of China's first-tier security camera vendors including Hikvision Digital Technology, Uniview Technologies and Dahua Technology, according to industry sources.

IDC statistics show China's security surveillance market scale reached US$16.2 billion in 2021 and is estimated to grow to US$20.1 billion in 2022, for a CAGR of 13.6% for the period. High-definition security camera lenses have become the tipping point of market growth, fast driving CIS sales in China, the sources said.

Since launching its first CIS chip SC1035 in 2014, SmartSens has quickly built a strong presence in the security surveillance sector. Its CIS shipments topped 100 million in 2017 and grew all the way to 146 million in 2020, registering the highest global market share at 35% in the security CIS sector, according to Frost & Sullivan statistics.

Over the years, SmartSens has been dedicated to developing high-performance CIS chips with higher light sensitivity and signal-to-noise ratios, as well as better low-light performance as the core requirements, while deepening deployments in AI, intelligent perception and machine vision capabilities, the industry sources noted.

In terms of future security-use CIS development, its co-founder and CEO Richard Xu has said that as the surveillance lens application scenarios continue to expand, the features of low light and wide dynamic range (WDR) will be increasingly highlighted for security camera solutions so that they can penetrate higher-end applications.

Since late April this year, SmartSens has kicked off a plan to list its shares on China's Sci-Tech Innovation Board (STAR Market), aiming to raise CNY2.82 billion to finance equipment procurement and system construction for its R&D center as well as the development of car-use CIS products, the sources said.

Growth in wafer capacity for image sensors

From Semiconductor Digest news: 

Global installed capacity for image sensors was one million 200mm-equivalent wafers per month at the end of 2021. According to the new Global Wafer Capacity 2022 report, image sensor capacity is forecast to increase 13% in 2022.

By the end of 2026, installed capacity for image sensors is projected to be 1.8 million 200mm-equiv. wafers per month. That’s an average annual growth rate of 12.5% over the forecast period, making image sensor capacity among the fastest growing segments.

While the Covid-19 pandemic negatively impacted the image sensor market in 2020, growth returned in 2021. Demand for digital imaging is increasing in virtually all areas, including cellphones, automotive, machine vision, security cameras, webcams, drones, and more.

While Sony in Japan is the industry’s leading CMOS image sensor supplier, the combined CIS capacity of Samsung and SK Hynix made Korea the industry’s biggest source for production of image sensors at the end of 2021.

More than a decade ago, Sony set a goal to become the largest supplier of image sensors for cellphones. After claiming the top spot, Sony in 2014 took aim at becoming the largest supplier of CMOS image sensors for automotive systems and it is pursuing machine vision applications in factory automation and drones as well as image-recognition security cameras. Sony also sells 3D imaging sensors for depth ranging, face recognition, artificial intelligence, and machine vision.

Sony was the first to manufacture image sensors on 300mm wafers. The company has continued expanding its CIS capacity by converting 300mm fabs from logic to image sensor production and by acquiring 300mm fabs from other companies in Japan looking to exit the business of fabricating ICs. Sony has eight 300mm fab lines at four sites in Japan, with the newest being Fab 5 in Nagasaki. Fab 5 started mass production in 2021 and the construction of an expansion is already underway.

Samsung entered the CMOS image sensor business to diversify its business beyond DRAM and NAND flash. Since the fabrication technologies and tool sets for CIS devices are like that of DRAM, Samsung repurposed older DRAM fabs to begin making image sensors. The company became the industry’s second largest supplier of image sensors by serving most of the camera module needs of its huge cellphone business. Samsung’s image sensor production exists primarily at a large 300mm fab facility in Hawseong, South Korea.

SK Hynix has used the same strategy of turning older DRAM fabs into capacity for CMOS image sensors but lacks the benefit of having another related SK Hynix operation to buy its CIS devices. The company has a small but growing share of the global image sensor market.

The industry’s third largest supplier of image sensors is OmniVision but it relies on external foundries for the fabrication of its CIS wafers. OmniVision’s primary sources of foundry capacity are TSMC in Taiwan and SMIC and HLMC in China.

https://www.semiconductor-digest.com/strong-growth-in-wafer-capacity-for-image-sensors-expected/

Review article on photonics + deep learning

A team from UCLA has published a review article titled "At the intersection of optics and deep learning: statistical inference, computing, and inverse design" in Optica Advances in Optics and Photonics:

Deep learning has been revolutionizing information processing in many fields of science and engineering owing to the massively growing amounts of data and the advances in deep neural network architectures. As these neural networks are expanding their capabilities toward achieving state-of-the-art solutions for demanding statistical inference tasks in various applications, there appears to be a global need for low-power, scalable, and fast computing hardware beyond what existing electronic systems can offer. Optical computing might potentially address some of these needs with its inherent parallelism, power efficiency, and high speed. Recent advances in optical materials, fabrication, and optimization techniques have significantly enriched the design capabilities in optics and photonics, leading to various successful demonstrations of guided-wave and free-space computing hardware for accelerating machine learning tasks using light. In addition to statistical inference and computing, deep learning has also fundamentally affected the field of inverse optical/photonic design. The approximation power of deep neural networks has been utilized to develop optics/photonics systems with unique capabilities, all the way from nanoantenna design to end-to-end optimization of computational imaging and sensing systems. In this review, we attempt to provide a broad overview of the current state of this emerging symbiotic relationship between deep learning and optics/photonics.

https://opg.optica.org/aop/abstract.cfm?uri=aop-14-2-209

Free (author copy) pdf: https://innovate.ee.ucla.edu/wp-content/uploads/2022/05/aop-14-2-209-compressed.pdf