Lomography Lomomatic 110 review
GPixel on the verge of IPO?
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From: http://www.myzaker.com/article/65d3ce24b15ec01a56438179
(Translated with Google Translate)
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Against the backdrop of an improving market, Changchun Changguangchenxin Microelectronics Co., Ltd. (hereinafter referred to as "Changguangchenxin"), a domestic company specializing in CMOS image sensors, has recently launched its IPO application on the Shanghai Stock Exchange Science and Technology Innovation Board. to the inquiry stage.
In this IPO, Changguang Chenxin plans to raise 1.557 billion yuan, and the funds are planned to be invested in the research and development and industrialization projects of CMOS image sensors in different directions, including the field of machine vision, scientific instruments, and professional imaging. At the same time, funds are also planned to be invested in high-end CMOS image sensor R&D center construction projects and to supplement working capital.
However, in recent years, Changguangchenxin's net profit has turned from profit to loss during the reporting period. Moreover, as a company that wants to be listed on the Science and Technology Innovation Board, Changguangchenxin's R&D expense rate has been decreasing year by year, and the detailed list of R&D expenses has been focused on by the Shanghai Stock Exchange.
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Canon designs recognized with internationally renowned iF Design Awards for 30th consecutive year
Canon converts 100% of power to renewable energy at five manufacturing sites for printing business
Canon converts 100% of power to renewable energy at five manufacturing sites for printing business
Andes and MetaSilicon collaborate on automotive CIS
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From Yahoo Finance news:
Andes Technology and MetaSilicon Collaborate to Build the World’s First Automotive-Grade CMOS Image Sensor Product Using RISC-V IP SoC
Hsinchu Taiwan, Feb. 22, 2024 (GLOBE NEWSWIRE) -- RISC-V IP vendor Andes Technology and edge computing chip provider MetaSilicon jointly announced that the MetaSilicon MAT Series is the world's first automotive-grade CMOS image sensor series using RISC-V IP SoC, using Andes' AndesCore™ N25F-SE processor. They are designed in accordance with the ISO26262 functional safety standard to achieve ASIL-B level and follow the AEC-Q100 Grade 2 to achieve a high level of safety and reliability. And by using technologies such as HDR, advanced imaging can be achieved in a simple, economical, and efficient system. They not only address the effects of high dynamic range, high sensitivity, and high color reproduction, but also meet the application requirements of ADAS decision-making.
The N25F-SE from Andes Technology is a 32-bit RISC-V CPU core that can support the standard IMACFD instruction set, which includes an efficient integer instruction set and a single/double precision floating point operation instruction set. The N25F-SE's high-efficiency five-stage pipeline achieves a good balance between high operating frequency and a streamlined design. It also has rich configurable options and flexible interface configuration, which greatly simplify the SoC development. In addition, the N25F-SE has obtained the ISO 26262 ASIL-B full compliance certification, which enables the image sensor chip to meet the vehicle-level safety requirement. For the development of MetaSilicon's automotive-grade chips, the N25F-SE and its safety package provide a good fit CPU solution and together with Andes’ technical support shorten the chip development time significantly.
MetaSilicon has first-class innovative R&D capabilities and has developed several cutting-edge technologies including LOFIC (Lateral Overflow Integration Capacitor) + DCG (Dual Conversion Gain) HDR (High-Dynamic Range), which meet the high-quality image requirements for smart car vision applications. The MAT Series 1MP CMOS image sensor chip has low power consumption and high dynamic range (HDR) characteristics. Its effective image resolution is 1280 H * 960 V, and it can support high dynamic range image output up to 60fps @120dB. The other MAT Series 3MP CIS has multiple capabilities such as low power consumption, ultra-high dynamic range (HDR), on-chip ISP, LFM, etc. Its effective image resolution is 1920 H * 1536 V, and can support up to 60fps frame rate, and the dynamic range can reach the industry-leading 140dB+. These chips can provide reliable high-quality image information for intelligent automotive applications.
"The N25F-SE provides a safety package, which includes a safety manual, safety analysis report and a development interface outline. The N25F-SE and its safety package are effective, high-performance and flexible automotive solutions. They can significantly reduce the time required to design automotive grade SoCs and to comply with the ISO 26262 standard", said Dr. Charlie Su, President and CTO of Andes Technology. "We are very pleased that N25F-SE's IP and safety package efficiently support MetaSilicon shorten the development time for its two automotive-grade chips. We also look forward to more cooperation between the two companies in the future to create more innovative products."
Jianhua Zheng, CTO of MetaSilicon said, “Among the various sensors used in automotive ADAS applications, visual image processing is particularly important. Once the image is not accurate and timely enough, it will directly lead to errors in the judgment of the back-end algorithm, so HDR performance requirements are extremely high. MetaSilicon's LOFIC+DCG HDR technology can achieve an ultra-high dynamic range of 140dB+ to meet practical application needs in the automotive ADAS field. We are honored to work closely with Andes Technology on two high-performance chips, using the world's first ISO 26262 certified RISC-V core N25F-SE that meets the functional safety standards. As a result, we can shorten the product development time and achieve functional safety goals."
Job Postings – Week of 3 March 2024
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Prophesee Internship - R&D - Sensor Simulation |
Paris, France |
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Sandia National Laboratories Postdoctoral Appointee Optoelectronics, HI & Quantum Device |
Albuquerque, New Mexico, USA |
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Sandia National Laboratories Intern - Photonic & Phononic Microsystems - R&D Undergrad Summer |
Albuquerque, New Mexico, USA |
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Tesla Engineering Technician, Camera |
Palo Alto, California, USA |
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University of London Silicon Detector Technician |
Mile End, London, England, UK |
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Turion Space Advanced Sensors Engineer |
Irvine, California, USA |
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SmartRay Sensor Application Engineer |
Penang, Malaysia |
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Joint Institute for Nuclear Research Postdoctoral Programme in Novel Cherenkov Detector Development |
Dubna, Russia |
VPS Semi presents a 600MP image sensor
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On September 6, the 24th China International Optoelectronics Expo kicked off at the Shenzhen Baoan International Convention and Exhibition Center. At this Optoelectronic Expo, Nanjing VPS Semiconductor Technology Co., Ltd. released a new product for the wide-area monitoring field - VPS800 large area array imaging. This series of chips has a pixel count of over 600 million, a pixel size of 0.7 microns, and supports 16 ROIs (regions of interest). It can provide imaging solutions at longer distances and a wider range, expanding the new boundaries of existing wide-area monitoring solutions.
The VPS800 large area array imaging chip is based on the internally-developed vertical charge transfer imaging device (VPS) as the core. It has a single-chip pixel size of more than 600 million, which can solve the problems of complexity, large volume, and high power consumption of existing large area array camera systems. It achieves long range and large field of view while reducing size, weight, power consumption, and cost, allowing coverage of a wider range clearly while obtaining more micro details. Currently, it is mainly used in security monitoring, commercial satellites, industrial inspection, etc.
For scenarios that require both large-scale observation and the acquisition of a large number of micro-details, the VPS800 large-area image sensor chip can support long-distance fixed-point shooting. With one imaging, large-scale observation can be achieved and the fine details of the entire image can be retained.
For scenarios presenting large target areas and high resolution such as commercial satellite surveillance, imaging sensors are required to be "small" and "light". The VPS800 large-area imaging chip can support a single-chip pixel size of more than 600 million without the need for splicing. It is small in size and light in weight - more in line with the demand scenarios of micro/nano satellites.
It is worth mentioning that the chip supports 16 ROI (Region of Interest) functions, which allows users to read sensor information from any area, thus reducing the amount of information read. The target can be continuously observed through one frame, and it can also achieve multi-target synchronous tracking. It can be used as a supplementary solution to existing security monitoring solutions, expanding the observation scope and application boundaries of existing security monitoring solutions.
STMicroelectronics announces new ToF Sensors
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VD55H1 Low-Noise Low-Power iToF Sensor
-- New design feat, packing 672 x 804 sensing pixels in a tiny chip size and can map a three-dimensional surface in great detail by measuring distance to over half a million points.
-- Lanxin Technology will use the VD55H1 for intelligent obstacle avoidance and high-precision docking in mobile robots; MRDVS will enhance its 3D cameras adding high-accuracy depth-sensing.
VL53L9 dToF 3D Lidar Module
-- New high-resolution sensor with 5cm – 9m ranging distance ensures accurate depth measurements for camera assistance, hand tracking, and gesture recognition.
-- VR systems use the VL53L9 to depict depth more accurately within 2D and 3D imaging, improving mapping for immersive gaming and other applications like 3D avatars.
The two new products announced will enhance safer mobile robots in industrial environments and smart homes as well as enable advanced VR applications.
The VL53L9CA is a state of the art, dToF 3D lidar (light detection and ranging) module with market leading resolution of up to 2.3k zones and accurate ranging from 5cm to 10m.
Full press release:
STMicroelectronics expands into 3D depth sensing with latest time-of-flight sensors
STMicroelectronics (NYSE: STM), a global semiconductor leader serving customers across the spectrum of electronics applications, announced an all-in-one, direct Time-of-Flight (dToF) 3D LiDAR (Light Detection And Ranging) module with market-leading 2.3k resolution, and revealed an early design win for the world’s smallest 500k-pixel indirect Time-of-Flight (iToF) sensor.
“ToF sensors, which can accurately measure the distance to objects in a scene, are driving exciting new capabilities in smart devices, home appliances, and industrial automation. We have already delivered two billion sensors into the market and continue to extend our unique portfolio, which covers all types from the simplest single-zone devices up to our latest high-resolution 3D indirect and direct ToF sensors,” said Alexandre Balmefrezol, General Manager, Imaging Sub-Group at STMicroelectronics. “Our vertically integrated supply chain, covering everything from pixel and metasurface lens technology and design to fabrication, with geographically diversified in-house high-volume module assembly plants, lets us deliver extremely innovative, highly integrated, and high-performing sensors.”
The VL53L9, announced today, is a new direct ToF 3D LiDAR device with a resolution of up to 2.3k zones. Integrating a dual scan flood illumination, unique in the market, the LiDAR can detect small objects and edges and captures both 2D infrared (IR) images and 3D depth map information. It comes as a ready-to-use low power module with its on-chip dToF processing, requiring no extra external components or calibration. Additionally, the device delivers state-of-the-art ranging performance from 5cm to 10 meters.
VL53L9’s suite of features elevates camera-assist performance, supporting macro up to telephoto photography. It enables features such as laser autofocus, bokeh, and cinematic effects for still and video at 60fps (frame per second). Virtual reality (VR) systems can leverage accurate depth and 2D images to enhance spatial mapping for more immersive gaming and other VR experiences like virtual visits or 3D avatars. In addition, the sensor’s ability to detect the edges of small objects at short and ultra-long ranges makes it suitable for applications such as virtual reality or SLAM (simultaneous localization and mapping).
ST is also announcing news of its VD55H1 ToF sensor, including the start of volume production and an early design win with Lanxin Technology, a China-based company focusing on mobile-robot deep-vision systems. MRDVS, a subsidiary company, has chosen the VD55H1 to add high-accuracy depth-sensing to its 3D cameras. The high-performance, ultra-compact cameras with ST’s sensor inside combine the power of 3D vision and edge AI, delivering intelligent obstacle avoidance and high-precision docking in mobile robots.
In addition to machine vision, the VD55H1 is ideal for 3D webcams and PC applications, 3D reconstruction for VR headsets, people counting and activity detection in smart homes and buildings. It packs 672 x 804 sensing pixels in a tiny chip size and can accurately map a three-dimensional surface by measuring distance to over half a million points. ST’s stacked-wafer manufacturing process with backside illumination enables unparalleled resolution with smaller die size and lower power consumption than alternative iToF sensors in the market. These characteristics give the sensors their excellent credentials in 3D content creation for webcams and VR applications including virtual avatars, hand modeling and gaming.
First samples of the VL53L9 are already available for lead customers and mass production is scheduled for early 2025. The VD55H1 is in full production now.
Pricing information and sample requests are available at local ST sales offices. ST will showcase a range of ToF sensors including the VL53L9 and explain more about its technologies at Mobile World Congress 2024, in Barcelona, February 26-29, at booth 7A61.
Canon requests removal of toner cartridges from Amazon.com, including Cool Toner brand cartridges sold by Epicartridges US based on Canon patent relating to toner cartridges having certain internal configurations
Canon requests removal of toner cartridges from Amazon.com, including Cool Toner brand cartridges sold by Epicartridges US based on Canon patent relating to toner cartridges having certain internal configurations
Canon requests removal of toner cartridges from Amazon.com, including Cool Toner brand cartridges sold by Epicartridges US based on Canon patent relating to toner cartridges having certain internal configurations
Canon requests removal of toner cartridges from Amazon.com, including Cool Toner brand cartridges sold by Epicartridges US based on Canon patent relating to toner cartridges having certain internal configurations
Five Jobs from Omnivision in Norway and Belgium
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Omnivision has sent us the following list of openings in their CMOS sensor development teams -
In Oslo, Norway:
Analog Characterization Engineer Link
Functional Safety Verification Engineer Link
Sr. Digital Design Engineer Link
Staff Digital Design Engineer Link
In Mechelen, Belgium:
Staff Characterization Engineer Link
Jobs Submitted by Employers
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Euresys (21 Mar 2024) Link
onsemi (11 Feb 2024) Link
Sony (7 Feb 2024) Link
Qurv (3 Feb 2024) Link
Photonis - (31 Jan 2024) Link
Sony Semiconductor Solutions - America (25 Jan 2024) Link
CEA Leti (23 Jan 2024) Link
ISAE SUPAERO (23 Jan 2024) Link
Transformative Optics (20 Jan 2024) Link
Teledyne (13 Dec 2023) Link
Job Postings – Week of 25 February 2024
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Sony UK Technology Centre Industrial Engineer |
Penceod, Wales, UK |
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Apple Image Quality Analyst |
San Diego, California, USA |
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Jenoptik Imaging Engineer |
Camberley, England, UK |
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NASA Postdoc - Materials and Process Development for Ultraviolet Detector Technologies (apply by 1 Mar 2024) |
Pasadena, California, USA |
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ASML Research Group Lead Sensor Modelling and Computational Imaging |
Veldhoven, Netherlands |
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Brookhaven National Laboratory Deputy Director-Instrumentation Division |
Upton, New York, USA |
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Axon Principal Systems Engineer (Remote) |
Scottsdale, Arizona, USA |
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Rochester Institute of Technology Tenure Track Faculty – Center for Imaging Science |
Rochester, New York, USA |
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Science and Technology Facilities Council – Rutherford Appleton Detector Scientist Industrial Placement |
Didcot, Oxfordshire, England, UK |
Job Postings – Week of 25 February 2024
Image Sensors World Go to the original article...
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Sony UK Technology Centre Industrial Engineer |
Penceod, Wales, UK |
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Apple Image Quality Analyst |
San Diego, California, USA |
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Jenoptik Imaging Engineer |
Camberley, England, UK |
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NASA Postdoc - Materials and Process Development for Ultraviolet Detector Technologies (apply by 1 Mar 2024) |
Pasadena, California, USA |
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ASML Research Group Lead Sensor Modelling and Computational Imaging |
Veldhoven, Netherlands |
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Brookhaven National Laboratory Deputy Director-Instrumentation Division |
Upton, New York, USA |
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Axon Principal Systems Engineer (Remote) |
Scottsdale, Arizona, USA |
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Rochester Institute of Technology Tenure Track Faculty – Center for Imaging Science |
Rochester, New York, USA |
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Science and Technology Facilities Council – Rutherford Appleton Detector Scientist Industrial Placement |
Didcot, Oxfordshire, England, UK |
Conference List – August 2024
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International Symposium on Sensor Science - 1-4 Aug 2024 - Singapore - Website
Quantum Structure Infrared Photodetector (QSIP) International Conference - 12-16 Aug 2024 - Santa Barbara, California, USA - Website
SPIE Optics & Photonics - 18-22 Aug 2024 - San Diego, California, USA - Website
International Conference on Sensors and Sensing Technology - 29-31 August 2024 - Valencia, Spain - Website
If you know about additional local conferences, please add them as comments.
Return to Conference List index
Teledyne acquires Adimec
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From Metrology News: https://metrology.news/teledyne-to-acquire-high-performance-camera-specialist-adimec/
Teledyne to Acquire High-Performance Camera Specialist Adimec
Teledyne Technologies has announced that it has entered into an agreement to acquire Adimec Holding B.V. and its subsidiaries (Adimec). Adimec, founded in 1992 and headquartered in Eindhoven, Netherlands, develops customized high-performance industrial and scientific cameras for applications where image quality is of paramount importance.
“Adimec possesses uniquely complementary technology, products and customers in the shared strategic focus areas of healthcare, global defense, and semiconductor and electronics inspection,” said Edwin Roks, Chief Executive Officer of Teledyne. “For decades and from our own X-ray imaging business headquartered in Eindhoven, I have watched Adimec grow to become a leader in niche applications requiring truly accurate images for precise decision making in time-critical processes.”
Joost van Kuijk, Adimec’s Chief Executive Officer, commented, “It is with great pleasure that we are able to announce publicly that Adimec will become part of Teledyne. Adimec’s success has always been built on ensuring imaging excellence in demanding applications through an unwavering focus on individual customer requirements by our expert engineers and designers.”
Adimec co- Chief Executive Officer, Alex de Boer added, “As a leader in advanced imaging technologies for industrial and scientific markets, Teledyne is the perfect company to build further on the strong foundation the founders and management have established over the past three decades. The entire Adimec team is looking forward to contributing to an exciting future with Teledyne while extending technical boundaries to support our customers with cameras – perfectly optimized to their application needs.”
Teledyne acquires Adimec
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From Metrology News: https://metrology.news/teledyne-to-acquire-high-performance-camera-specialist-adimec/
Teledyne to Acquire High-Performance Camera Specialist Adimec
Teledyne Technologies has announced that it has entered into an agreement to acquire Adimec Holding B.V. and its subsidiaries (Adimec). Adimec, founded in 1992 and headquartered in Eindhoven, Netherlands, develops customized high-performance industrial and scientific cameras for applications where image quality is of paramount importance.
“Adimec possesses uniquely complementary technology, products and customers in the shared strategic focus areas of healthcare, global defense, and semiconductor and electronics inspection,” said Edwin Roks, Chief Executive Officer of Teledyne. “For decades and from our own X-ray imaging business headquartered in Eindhoven, I have watched Adimec grow to become a leader in niche applications requiring truly accurate images for precise decision making in time-critical processes.”
Joost van Kuijk, Adimec’s Chief Executive Officer, commented, “It is with great pleasure that we are able to announce publicly that Adimec will become part of Teledyne. Adimec’s success has always been built on ensuring imaging excellence in demanding applications through an unwavering focus on individual customer requirements by our expert engineers and designers.”
Adimec co- Chief Executive Officer, Alex de Boer added, “As a leader in advanced imaging technologies for industrial and scientific markets, Teledyne is the perfect company to build further on the strong foundation the founders and management have established over the past three decades. The entire Adimec team is looking forward to contributing to an exciting future with Teledyne while extending technical boundaries to support our customers with cameras – perfectly optimized to their application needs.”
Computational Imaging Photon by Photon
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Fujifilm X100 VI review
Canon celebrates 21st consecutive year of No. 1 share of global interchangeable-lens digital camera market
SolidVue develops solid-state LiDAR chip
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SolidVue, Korea's Exclusive Developer of LiDAR Sensor Chips Showcasing World-Class Technological Capabilities
SEOUL, South Korea, Dec. 19, 2023 /PRNewswire/ -- SolidVue Inc., Korea's exclusive enterprise specialized in CMOS LiDAR (Light Detection and Ranging) sensor IC development, once again proved its global technological prowess by announcing its achievement of two LiDAR-related papers being accepted at the upcoming 'ISSCC (International Solid-State Circuits Conference) 2024'.
Established in 2020, SolidVue focuses on designing SoCs (System-on-Chip) for LiDAR sensors that comprehensively assesses the shapes and distances of surrounding objects. This is a pivotal technology assured to see significant growth in industries such as but not limited to autonomous vehicles and smart cities.
Jaehyuk Choi, the CEO of SolidVue, disclosed the company's development of Solid-State LiDAR sensor chips, aiming to replace all components of traditional mechanical LiDAR with semiconductors. This innovation is expected to reduce volume by up to one-tenth and costs by around one-hundredth compared to the aforementioned mechanical LiDAR.
Utilizing its proprietary CMOS SPAD (Single Photon Avalanche Diode) technology, SolidVue's LiDAR sensor chips flawlessly detect even minute particles of light, enhancing measurement precision. The company focuses on all LiDAR detection ranges (short, medium, long), notably making advancements in the medium-to-long distance sector suited for autonomous vehicles and robotics. By the third quarter of this year, they meticulously developed an Engineering Sample (ES) of a Solid-State LiDAR sensor chip capable of measuring up to 150 meters, and are aiming for mass production by the end of 2024.
Choi emphasized SolidVue's independent development of various core technologies such as SPAD devices, LiDAR sensor architectures, and integrated image signal processors, while also highlighting the advantage of SolidVue's single-chip design in cost and size reduction compared to the multi-chip setup of traditional mechanical LiDAR sensors.
SolidVue's technological prowess has been repeatedly acknowledged at the ISSCC, marking a remarkable achievement for a Korean fabless company. At the forthcoming ISSCC 2024, SolidVue is set to showcase its groundbreaking advancements, including a 50-meter mid-range Solid-State LiDAR sensor that features a resolution of 320x240 pixels and optimized memory efficiency. Additionally, a 10-meter short-range Flash LiDAR will be presented, characterized by its 160x120 pixel resolution and an ultra-low power consumption of 3-uW per pixel. These significant innovations are the result of collaborative efforts between SolidVue, Sungkyunkwan University, and UNIST.
Ahead of full product commercialization, SolidVue's focal point is securing domestic and international clients as well as attracting investments. In January, they plan to make their debut at the 'CES 2024', the world's largest electronics exhibition, by showcasing their 150-m LiDAR sensor chip ES products with the aim of initiating discussions and collaborations with leading global LiDAR suppliers.
Since its establishment, SolidVue has secured a cumulative $6 million in investments. Key Korean VCs such as KDB Bank, Smilegate Investment, Quantum Ventures Korea, Quad Ventures, among others, have participated as financial investors. Additionally, Furonteer, a company specializing in automated equipment for automotive camera modules, joined as SolidVue's first strategic investor.
CEO Choi stated, "Aligning with the projected surge in LiDAR demand post-2026, we are laying the groundwork for product commercialization." He added, "We are heavily engaged in joint research and development with major Korean corporations, discussing numerous LiDAR module supply deals, and exploring collaborations with global companies for overseas market penetration."
Job Postings – Week of 18 February 2024
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Pacific Biosciences Staff CMOS Sensor Test Engineer |
Menlo Park, California, USA |
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Vilnius University PostDoc in Experimental HEP |
Vilnius, Lithuania |
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Precision Optics Corporation Electrical Engineer |
Windham, Maine, USA |
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CEDES (Senior) Design Engineer in Product Development |
Singapore |
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Karl Storz Image Processing Engineer V |
Goleta, California, USA |
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Karl Storz Development Engineer - Image Processing |
Tuttlingen, Germany |
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University of Warwick PhD Studentship: Towards Silicon Photonics Based Gas Sensors |
Coventry, UK |
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Leidos Optical Test Engineer |
Dayton, Ohio, USA |
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Teledyne e2v Semiconductors MBE Growth Production Engineer |
Camarillo, California, USA |
Conference List – July 2024
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The 9th International Smart Sensor Technology Exhibition - 3-5 Jul 2024 - Seoul, Korea (South) - Website
17th International Conference
on Scintillating Materials and their Applications - 8-12 Jul 2024 - Milan, Italy - Website
Optica Sensing and Imaging Congresses - 15-19 Jul 2024 - Toulouse, France - Website
International Conference on Imaging, Signal Processing and Communications - 19-21 Jul 2024 - Fukuoka, Japan - Website
American Association of Physicists in Medicine Annual Meeting - 21-25 Jul 2024 - Los Angeles, California, USA - Website
If you know about additional local conferences, please add them as comments.
Return to Conference List index
Semiconductor Engineering article about noise in CMOS image sensors
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Semiconductor Engineering published an article on dealing with noise in CMOS image sensors: https://semiengineering.com/dealing-with-noise-in-image-sensors/
Dealing With Noise In Image Sensors
The expanding use and importance of image sensors in safety-critical applications such as automotive and medical devices has transformed noise from an annoyance into a life-threatening problem that requires a real-time solution.
In consumer cameras, noise typically results in grainy images, often associated with poor lighting, the speed at which an image is captured, or a faulty sensor. Typically, that image can be cleaned up afterward, such as reducing glare in a selfie. But in cars, glare in an ADAS image system can affect how quickly the brakes are applied. And in vehicles or medical devices, systems are so complex that external effects can affect images, including heat, electromagnetic interference, and vibration. This can be particularly problematic in AI-enabled computer vision systems where massive amounts of data need to be processed at extremely high speeds. And any of this can be affected by aging circuits, due to dielectric breakdown or changes in signal paths due to electromigration.
Thresholds for noise tolerance vary by application. “A simple motion-activated security camera or animal-motion detection system at a zoo can tolerate much more noise and operate at much lower resolution than a CT scanner or MRI system used in life-saving medical contexts,” said Brad Jolly, senior applications engineer at Keysight. “[Noise] can mean anything that produces errors in a component or system that acquires any form of image, including visible light, thermal, X-ray, radio frequency (RF), and microwave.”
Tolerance is also determined by human perception, explained Andreas Suess, senior manager for novel image sensor systems in OmniVision’s Office of the CTO. “Humans perceive an image as pleasing with a signal-to-noise ratio (SNR) of >20dB, ideally >40dB. But objects can often be seen at low SNR levels of 1dB or less. For computational imaging, in order to deduce what noise level can be accepted one needs to be aware of their application-level quality metrics and study the sensitivity of these metrics against noise carefully.”
Noise basics for imaging sensors
No noise is ideal, but it’s an unrealistic goal. “With an image sensor, noise is inevitable,” said Isadore Katz, senior marketing director at Siemens Digital Industries Software. “It’s when you’ve got a pixel value that’s currently out of range with respect to what you would have expected at that point. You can’t design it out of the sensor. It’s just part of the way image sensors work. The only thing you can do is post-process it away. You say to yourself, ‘That’s not the expected value. What should it have been?’”
Primarily noise is categorized as fixed pattern noise and temporal noise, and both explain why engineers must cope with its inevitability. “Temporal noise is a fundamental process based on the quantization of light (photons) and charge (electrons),” said Suess. “When capturing an amount of light over a given exposure, one will observe a varying amount of photons which is known as photon shot noise, which is a fundamental noise process present in all imaging devices.” In fact, even without the presence of light, a dark signal, also known as dark current, can exhibit shot noise.
Worse, even heat alone can cause noise, which can cause difficulties for ADAS sensors under extreme conditions. “An image sensor has to work over the brightest and darkest conditions; it also has to work at -20 degrees and up to 120 degrees,” said Jayson Bethurem, vice president of marketing and business development at Flex Logix. “All CMOS sensors run slower and get noisier when it’s hotter. They run faster, a little cleaner, when it’s cold, but only up to a certain point. When it gets too cold, they start to have other negative effects. Most of these ICs self-heat when they’re running, so noise gets inserted there too. The only way to get rid of that is to filter it out digitally.”
Fixed-pattern noise stems from process non-uniformities, as well as design choices and can cause offset, gain or settling artifacts. Fixed pattern noise can manifest itself as variations in quantum efficiency, offset or gain, as well as read noise. Mitigating fixed pattern noise requires effort on process, device, circuit design, and signal processing levels.
Fig. 2: Flicker from LED traffic lights or traffic signs poses a serious challenge for HDR solutions, preventing driver-assistance and autonomous driving systems from being able to correctly detect lighted traffic signs. Source: OmniVision
Imaging basics for ADAS
While noise would seem to be a critical problem for ADAS sensors, given the potential for harm or damage, it’s actually less of an issue than for something like a consumer camera, where out-of-range pixels can ruin an image. ADAS is not concerned with aesthetics. It focuses on a binary decision — brake or not brake. In fact, ADAS algorithms are trained on lower-resolution images, and ignore noise that would be a product-killer in a consumer camera.
For example, to find a cat in the middle of an image, first the image is “segmented,” a process in which a bounding box is drawn around a potential object of interest. Then the image is fed into a neural net, and each bounding region is evaluated. The images are labeled, and then an algorithm can train itself to identify what’s salient. “That’s a cat. We should care about it and brake. It’s a skunk. We don’t care about it. Run it over,” said Katz. That may sound like a bad joke, but ADAS algorithms actually are trained to assign lower values to certain animals.
“It is about safety in the end, not so much ethics,” Katz said. “Even if someone does not care about moose, the car still has to brake because of the danger to the passengers. Hitting the brakes in any situation can pose a risk.” But higher values are assigned to cats and dogs, rather than skunks and squirrels.
If an object is fully or partly occluded by another object or obscured by light flare, it will require more advanced algorithms to correctly discern what it is. After the frame is received from the camera and has gone through basic image signal processing, the image is then presented to a neural net.
“Now you’ve left the domain of image signal processing and entered the domain of computer vision, which starts with a frame or sequence of frames that have been cleaned up and are ready for presentation,” said Katz. “Then you’re going to package those frames up and send them off to an AI algorithm for training, or you’re going to take those images and then process them on a local neural net, which will start by creating bounding boxes around each of the artifacts that are inside the frame. If the AI can’t recognize an object in the frame it’s examining, it will try to recognize it in the following or preceding frames.”
In a risky situation, the automatic braking system has about 120ms to respond, so all of this processing needs to happen within the car. In fact, there may not even be time to route from the sensor to the car’s own processor. “Here are some numbers to think about,” said Katz. “At 65 mph, a car is moving at 95 feet per second. At 65 mph, it takes about 500 feet to come to a complete stop. So even at 32.5 mph in a car, it will travel 47 feet in 1 second. If the total round trip from sensor to AI to brake took a half-second, you would be 25 feet down the road and still need to brake. Now keep in mind that the sensor is capturing images at about 30 frames per second. So every 33 milliseconds, the AI has to make another decision.”
In response, companies are using high-level synthesis to develop smart sensors, in which an additional die — with all the traditional functions of an image signal processor (ISP), such as noise reduction, deblurring, and edge detection — is sandwiched directly adjacent to the sensor.
“It’s now starting to include computer vision capability, which can be algorithmic or AI-driven,” said Katz. “You’ll start to see a smart sensor that has a neural net built inside. It could even be a reprogrammable neural net, so you can make updates for the different weights and parameters as soon as it gets smarter.”
If such a scheme succeeds, it means that a sensor could perform actions locally, allowing for real-time decisions. It also could repackage the information to be stored and processed in the cloud or car, for later training to increase accurate, rapid decision-making. In fact, many modern ISPs can already dynamically compensate for image quality. “For example, if there is a sudden change from bright light to low light, or vice-versa, the ISP can detect this and change the sensor settings,” he said. “However, this feedback occurs well before the image gets to the AI and object detection phase, such that subsequent frames are cleaner going into the AI or object detection.”
One application that already exists is driver monitoring, which presents another crucial noise issue for designers. “The car can have the sun shining right in your face, saturating everything, or the complete opposite where it’s totally dark and the only light is emitting off your dashboard,” said Bethurem. “To build an analog sensor and the associated analog equipment to have that much dynamic range and the required level of detail, that’s where noise is a challenge, because you can’t build a sensor of that much dynamic range to be perfect. On the edges, where it’s really bright or over-saturated bright, it’s going to lose quality, which has to get made up. And those are sometimes the most dangerous times, when you want to make sure the driver is doing what they’re supposed to be doing.”
AI and noise
The challenges of noise and the increasing intelligence of sensors have also attracted the attention of the AI community.
“There are already AI systems capable of filling in occluded parts of a digital image,” said Tony Chan Carusone, CTO at Alphawave Semi. “This has obvious potential for ADAS. However, to perform this at the edge in real-time will require new dedicated processing elements to provide the immediate feedback required for safety-critical systems. This is a perfect example of an area where we can expect to see new custom silicon solutions.”
Steve Roddy, chief marketing officer at Quadric, notes that path already is being pioneered. “Look at Android’s/Google’s ‘Magic Eraser’ functionality in phones – quickly deleting photo-bombers and other background objects and filling in the blanks. Doing the same on an automotive sensor to remove occlusions and ‘fill in the blanks’ is a known solved problem. Doing it in real time is a simple compute scaling problem. In 5nm technology today, ~10mm2 can get you a full 40 TOPs of fully programmable GPNPU capability. That’s a tiny fraction of the large (> 400 mm2) ADAS chips being designed today. Thus, there’s likely to be more than sufficient programmable GPNPU compute capability to tackle these kinds of use cases.”
Analyzing noise
Analyzing noise in image sensors is a challenging and active area of research that dates back more than 50 years. The general advice from vendors is to talk to them directly to determine if their instrumentation aligns with a project’s specific needs.
“Noise is of a lot of interest to customers,” said Samad Parekh, product manager for analog/RF simulation at Synopsys. “There are many different ways of dealing with it, and some are very well understood. You can represent the noise in a closed form expression, and because of that you can very accurately predict what the noise profile is going to look like. Other mechanisms are not as well understood or are not as linear. Because those are more random, there’s a lot more effort required to characterize the noise or design with that constraint in mind.”
Best practices
Keysight’s Jolly offered day-to-day advice for reducing and managing noise in image sensor projects:
- Clearly define the objectives of the sensor as part of the overall system. For example, a slow, low-resolution thermal imager or vector network analyzer may reveal information about subcutaneous or subdural disease or injury that would be invisible to a high-resolution, high-speed visible light sensor. Work with your component and module vendors to understand what noise analysis and denoising they have already done. You will learn a lot and be able to leverage a lot of excellent work that has already been accomplished. Also, consider image noise throughout the total product life cycle and use simulation tools early in your design phase to minimize issues caused by sub-optimal signal integrity or power integrity.
- Analyze the problem from the perspective of the end user. What are their objectives? What are their concerns? What skills do they possess? Can they make appropriate interventions and modifications? What is their budget? It may turn out, for example, that a fully automated system with a higher amount of noise may be more appropriate for some applications than a more complex system that can achieve much lower noise.
- Become familiar with camera, optical, and imaging standards that are available, such as ISO 9358, 12232, 12233, 14524, and 15739, as well as European Machine Vision Association (EMVA) 1288.
- Investigate the latest research on the use of higher mathematics, statistics, and artificial intelligence in de-noising. Some of these techniques include expectation maximization estimation, Bayesian estimation, linear minimum mean square error estimation, higher-order partial differential equations, and convolutional neural networks.
Future approaches
While current ADAS systems may tolerate more noise than other forms of imaging, that may not be the case in the future. A greater variety of use cases will push image sensors towards higher resolutions, which in turn will require more localized processing and noise reduction.
“A lot of the image processing in the past was VGA, but applications like internal cabin monitoring, such as eye-tracking the driver and passengers to recognize what’s going inside the cabin — including monitoring driver alertness or whether someone got left behind in the backseat — are going to start to drive us towards higher-resolution images,” Katz said. “In turn, that’s going to start to mandate increasing levels of noise reduction, dealing with image obstructions, and with being able to process a lot more data locally. When you go from VGA to 720 to 1020 up to 4k, you’re increasing the number of pixels you have to operate with by 4X. Every one of these demands more and more localized processing. That’s where we’ll end up going.”
Talk on digital camera misunderstandings and HDR
Image Sensors World Go to the original article...
Wayne Prentice presented a talk titled "Digital Camera Myths, Mis-statements and Misunderstandings" at the NY chapter meeting of IS&T (Society for imaging Science and Tech.) on 17 Jan. 2024.
Abstract: The digital camera system is deceptively complex.
Understanding camera operation/design requires some knowledge of the
parts: photometry, radiometry, optics, sensor physics, sensor design,
signal processing, image processing, color science, statistics, human
perception, and image/video encoding. With all these parts, it is easy
to miss something. This talk was inspired by interactions with
co-workers and clients. It has been my experience that some subtle, yet
important points are often missed and can lead to suboptimal product
and design decisions that could be avoided. The goal of this talk is to
fill in some of those gaps.
Another version of the talk at RIT imaging science weekly seminar on Feb 7, 2024:
Wayne Prentice also gave a talk in 2022 on HDR at the NY IS&T chapter meeting:
Bio: Wayne has been working in the imaging industry for over 35 years. He has a BSEE from Clarkson University and a Masters in Imaging Science from RIT. Wayne has worked on imaging equipment ranging from x-ray, CAT scanners, MRI, extra-terrestrial imaging, and digital cameras. Much of Wayne's digital camera experience came from 17 years working at Kodak R&D, product development for digital cameras. He holds 16 US patents in digital imaging. At Kodak Wayne became the lead image scientist and manager for Digital Camera R&D group. He was responsible for competitive testing, image quality testing, new feature development, and image science aspects of product commercialization. Wayne has worked as an independent contractor over the past 5 years providing solutions to a wide range of imaging challenges, mostly in the areas of developing custom camera applications, computer vision and HDR imaging.
Canon named a Leader in IDC MarketScape: Worldwide Sustainability Programs and Services Hardcopy
A message from IEEE Sensors 2024 conference co-chair
Image Sensors World Go to the original article...
In my role as Industrial Co-chair of IEEE SENSORS 2024 conference to
be held this year in Kobe, Japan, in October, I want to invite the
participation of the image sensor community. SENSORS
is a vibrant conference – 1000 attendees in Vienna for SENSORS 2023 –
covering sensors devices and systems. I can testify that there is much
overlap in the issues addressed in sensors, but for historical reasons
it appears that this is a conference that the image sensor community has
not had on their radar. I, along with my Industrial Co-Chair Sozo
Yokogawa of SONY Semiconductor, would like to change this.
Our
proposal is to highlight image sensor technology at the conference
through a combination of focused sessions, keynote speakers, a workshop,
tutorial, and networking possibilities. I would like to use as a model
the success efforts that I have been involved in over many years as part
being involved with the technical committees at IEDM and ISSCC. To
accomplish this we would like to reach out to our image sensor community
to help promote this goal through networking and through volunteering
informally or formally.
The sponsoring IEEE Sensor Council,
of which I am an AdCom member, has two initiatives that are of note
related to this proposal. One initiative is to increase industrial
involvement in a way that prioritizes the healthy technical interaction
of industry, academia, and laboratories. The other initiative is to
develop close ties between conference participation and the high-impact
council-sponsored Sensor Journal and Sensor Letters, enabling both the
publishing of work from the conference in the journals and providing a
path where accepted papers in the journals are accepted also for
presentation at SENSORS.
I have discussed this informally in our
community over the last year with positive comments. I look forward to
feedback, but most importantly, support of this goal. I look forward to
hearing from you and seeing many of you in Kobe.
Dan McGrath
TechInsights Inc.
AdCom member, IEEE Solid State Circuits Society & IEEE Sensor Council
dmcgrath@ieee.org
