Image Sensors World        Go to the original article...

ETH Zurich publishes an Arxiv.org paper "V2E: From video frames to realistic DVS event camera streams" by Tobi Delbruck, Yuhuang Hu, and Zhe He. The V2E open source tool is available here.

"To help meet the increasing need for dynamic vision sensor (DVS) event camera data, we developed the v2e toolbox, which generates synthetic DVS event streams from intensity frame videos. Videos can be of any type, either real or synthetic. v2e optionally uses synthetic slow motion to upsample the video frame rate and then generates DVS events from these frames using a realistic pixel model that includes event threshold mismatch, finite illumination-dependent bandwidth, and several types of noise. v2e includes an algorithm that determines the DVS thresholds and bandwidth so that the synthetic event stream statistics match a given reference DVS recording. v2e is the first toolbox that can synthesize realistic low light DVS data. This paper also clarifies misleading claims about DVS characteristics in some of the computer vision literature. The v2e website is this https URL and code is hosted at this https URL."


The paper also explains some of the misconceptions about DVS sensors:

"Debunking myths of event cameras: Computer vision papers about event cameras have made rather misleading claims such as “Event cameras [have] no motion blur” and have “latency on the order of microseconds” [7]–[9], which were perhaps fueled by the titles (though not the content) of papers like [1], [10], [11]. Review papers like [5] are more accurate in their descriptions of DVS limitations, but are not very explicit about the actual behavior.

DVS cameras must obey the laws of physics like any other vision sensor: They must count photons. Under low illumination conditions, photons become scarce and therefore counting them becomes noisy and slow. v2e is aimed at realistic modeling of these conditions, which are crucial for deployment of event cameras in uncontrolled natural lighting."

Go to the original article...

Image Sensors World        Go to the original article...

Trioptics publishes ats presentation at the recent Autosens On-Line conference "From Lab to Fab – Assembly and testing of optical components for LiDAR sensors in prototyping and serial production" by Dirk Seebaum:



Blickfeld publishes a datasheet for its Cube LiDAR based MEMS mirror scanning and SPAD array. The datasheet includes performance in bright sunlight:


BusinessWire: Apple announces iPadOS 14 that features support for iPad Pro LiDAR: "ARKit 4 delivers a brand new Depth API that allows developers to access even more precise depth information captured by the new LiDAR Scanner on iPad Pro®. Developers can use the Depth API to drive powerful new features in their apps, like taking body measurements for more accurate virtual try-on, or testing how paint colors will look before painting a room."


Hong Kong University and Cornell University publish a paper "Depth Sensing Beyond LiDAR Range" by Kai Zhang, Jiaxin Xie, Noah Snavely, and Qifeng Chen.

Go to the original article...

Image Sensors World        Go to the original article...

Trioptics publishes ats presentation at the recent Autosens On-Line conference "From Lab to Fab – Assembly and testing of optical components for LiDAR sensors in prototyping and serial production" by Dirk Seebaum:



Blickfeld publishes a datasheet for its Cube LiDAR based MEMS mirror scanning and SPAD array. The datasheet includes performance in bright sunlight:


BusinessWire: Apple announces iPadOS 14 that features support for iPad Pro LiDAR: "ARKit 4 delivers a brand new Depth API that allows developers to access even more precise depth information captured by the new LiDAR Scanner on iPad Pro®. Developers can use the Depth API to drive powerful new features in their apps, like taking body measurements for more accurate virtual try-on, or testing how paint colors will look before painting a room."


Hong Kong University and Cornell University publish a paper "Depth Sensing Beyond LiDAR Range" by Kai Zhang, Jiaxin Xie, Noah Snavely, and Qifeng Chen.

Go to the original article...

Image Sensors World        Go to the original article...

Gpixel announces the GMAX32103, a large format Global Shutter CMOS sensor for industrial applications. The sensor is based on 3.2 µm charge domain GS pixel, provides 11276(H) x 9200(V) resolution (103 MP), and supports up to 28fps with 12bit output. GMAX32103 is aimed to the demanding machine vision applications and aerial imaging.

The 3.2 um pixel achieves a full well capacity of 10k e-, read noise less than 2 e- and maximum DR of 66dB. With the implementation of micro lens and light pipe technologies, the sensor provides a peak QE of 65%, a shutter efficiency of 1/15,000 and excellent angular response. GMAX32103 offers a large FOV to expand single-shot capabilities and a nearly square aspect ratio (1.27:1), which is optimal for inspection applications.

GMAX32103 uses 52 pairs of sub-LVDS channels, each run at a maximum speed of 960MHz. The sensor supports channel multiplexing for lower data rate implementations, and integrates a variety of read-out functions including up to 32 regions of horizontal windowing (region of interest), sub sampling and image flipping. GMAX32103’s is packaged in 209-pin uPGA ceramic package with an outer dimension of 49.5 mm x 48.1 mm.

“We are very thrilled with the introduction of GMAX32103. The further expansion of Gpixel’s line up of extremely high-resolution sensors based on an industry proven and widely accepted platform, empowers our customers to tackle demanding applications and to address the industry’s needs for ever increasing image accuracy and throughput. This product is part of our fast growing GMAX product family, which will be further expanded in the very near future with other exciting products,” says Wim Wuyts, CCO of Gpixel.

GMAX32103 engineering samples are expected in November 2020.

Go to the original article...

Image Sensors World        Go to the original article...

Canon has developed a prototype of what it calls "the world’s first single photon avalanche diode (SPAD) image sensor with signal-amplifying pixels capable of capturing 1-megapixel images."

The SPAD image sensor developed by Canon overcomes the longstanding difficulties of achieving high SPAD pixel counts. By adopting a new circuit technology, Canon was able to realize a digital image resolution of 1MP. Exposure time can be shortened to as little as 3.8ns. In addition, the sensor is capable of up to 24,000 fps with 1 bit output, thus enabling slow-motion capture of fast movement within an extremely short time frame.

The sensor also features a high time resolution as precise as 100 ps. With a high resolution of 1MP and high-speed image capture, it is also able to accurately perform 3D distance measurements.

The camera was jointly developed with scientists at the Swiss Federal Institute of Technology in Lausanne and published in OSA Optica.

Go to the original article...

Image Sensors World        Go to the original article...

Semiconductor Engineering quotes said David Uriu, technical director of product management at UMC, saying that CIS are the drivers at 65nm and 40nm process nodes. "CIS use 65nm/55nm. Some CIS devices will start to use 40nm, but this is not a significant part of the current CIS volume yet. 40nm will expand for some high-end pixel designs, but it is not expected to be a widely accepted node due to costs."

Electronics360 reports that fabs' investments into image sensor manufacturing equipment rise 60% over 2020 and add another 35% rise in 2021.

Innoviz publishes its webinar comparing LiDAR, camera, and radar in ADAS and AV applications:



Samsung publishes a promotional video of its 50MP, 1.2um pixel ISOCELL GN1 image sensor:

Go to the original article...

Image Sensors World        Go to the original article...

After 7 years in development, Stratio unveils BeyonSense, said to be "the world’s first germanium-based smartphone-compatible camera." The 11 x 8 pixel BeyonSense Pre camera is expected to be available for sale in a month from now, if COVID situation allows. The company says:

"Due to COVID-19, our fabrication facilities in Silicon Valley have been closed for the past few months and there is no clear timeline for when they will reopen.

As this is an incredibly dynamic situation, we can only expect to ship BeyonSense® Pre with 11x8 pixels in a month following the reopening of our facilities. You can be assured our team is working around the clock to make it possible to deliver BeyonSense® to you."

"The Stratio idea was conceived by three PhD students in a small corner desk at Stanford University.

As PhD students in Electrical Engineering, they knew about the myriad of advantages with infrared imaging – from material analysis to night vision. However, the technology was prohibitively expensive so that only a few could benefit from it. One day, they discussed how a new sensor material called germanium (Ge) could be responsive to infrared light waves in real life. They began digging deeper, consulted experts, and conducted countless experiments to find out how they would achieve low cost, small size, and low power consumption. It turned out to be a years-long journey, but a fruitful one. Hence Stratio was born, in January 2013."


Stratio shows a short demo video of its new camera:

Go to the original article...

Image Sensors World        Go to the original article...

i-Micronews: At the end of 2019, the CIS price rose of nearly 10% because of production reaching maximum worldwide capacity.

"Even though the COVID-19 lockdown led to a drop in smartphone shipments, the demand for mobile camera modules will maintain a 7% year-over-year (YoY) growth in 2020. In the COVID-19 situation, no evident substantial impact on the CIS supply chain has been identified, including on the purchase of raw materials by giant players. The overall impact will be slower growth this year, with respect to the 25% YoY growth last year.

Demand from mobile devices will keep thriving. The overall attachment rate for CIS cameras per phone will move beyond 3.4 in 2020. Also, the growth rate for CIS attachment is still expected to be over 10% in the automotive space. The short term impact of COVID-19 has led to a substantial decrease of car production in the range of -30%. The end point for 2020 is very uncertain, and the long-term horizon is at best flat. The downturn in car production will be mitigated by increased attachment rates for automotive cameras. Looking at all markets the demand is still growing. The expansion of investment in CIS and capacity transition from DRAM to CIS continues for most players."

Go to the original article...

Image Sensors World        Go to the original article...

ETH Zurich Robotics and Perception Group publishes a video presentation "Event Cameras: Opportunities and the Road Ahead (CVPR 2020)" by Davide Scaramuzza

Go to the original article...

Image Sensors World        Go to the original article...

University of Inner Mongolia, China, and CNRS, France, publish a paper "A Review of an Old Dilemma: Demosaicking First, or Denoising First?" by Qiyu Jin, Gabriele Facciolo, and Jean-Michel Morel.

"Image denoising and demosaicking are the first two crucial steps in digital camera pipelines. In most of the literature, denoising and demosaicking are treated as two independent problems, without considering their interaction, or asking which should be applied first. Several recent works have started addressing them jointly in works that involve heavy weight neural networks, thus incompatible with low power portable imaging devices. Hence, the question of how to combine denoising and demosaicking to reconstruct full color images remains very relevant: Is denoising to be applied first, or should that be demosaicking first? In this paper, we review the main variants of these strategies and carry-out an extensive evaluation to find the best way to reconstruct full color images from a noisy mosaic. We conclude that demosaicking should applied first, followed by denoising. Yet we prove that this requires an adaptation of classic denoising algorithms to demosaicked noise, which we justify and specify."

Go to the original article...

Image Sensors World        Go to the original article...

SystemPlus Consulting publishes Apple iPAD Pro 2020 LiDAR module reverse engineering report with few more pictures in addition to many that have already been published:

"This rear 3D sensing module is using the first ever consumer direct Time-of-Flight (dToF) CMOS Image Sensor (CIS) product with in-pixel connection.

The 3D sensing module includes a new generation of Near Infrared (NIR) CIS from Sony with a Single Photon Avalanche Diode (SPAD) array. The sensor features 10 µm long pixels and a resolution of 30 kilopixels. The in-pixel connection is realized between the NIR CIS and the logic wafer using hybrid Direct Bonding Interconnect technology, which is the first time Sony has used 3D stacking for its ToF sensors.

The LiDAR uses a vertical cavity surface emitting laser (VCSEL) coming from Lumentum. The laser is designed to have multiple electrodes connected separately to the emitter array. A new design with mesa contact is used to enhance wafer probe testing.

A wafer level chip scale packaging (WLCSP), five-side molded driver integrated circuit from Texas Instruments generates the pulse and drives the VCSEL power and beam shape. Finally, a new Diffractive Optical Element (DOE) from Himax is assembled on top of the VCSEL to generate a dot pattern."

Go to the original article...

Image Sensors World        Go to the original article...

MIT Vivienne Sze's presentation on energy efficient processing has a part about low power ToF imaging:


Intel announces an long range version of its active stereo 3D camera Realsense D455:

"The D455 camera increases the optimal range to 6 meters, making it twice as accurate as the current D400 cameras without sacrificing field of view. The D455 also includes global shutters for the depth and RGB sensors to improve correspondence between the two different data streams and to match the field of view between the depth sensors and the RGB sensor. In addition, this camera also integrates an IMU to allow for refinement of its depth awareness in any situation where the camera moves.

The D455 achieves less than 2% Z-error at 4 meters with several improvements. First, the depth sensors are located 95 millimeters apart, providing greater depth accuracy at a longer range. Second, the depth and RGB sensors are placed on the same stiffener, resulting in an improved alignment of color and depth. Lastly, the RGB sensor has the same field of view as the depth sensors, further improving correlation of depth and color points."


Sharp presentation on its distance measuring sensors explains their operation:


Sharp also makes SPAD-based ToF distance sensors:

Go to the original article...

Image Sensors World        Go to the original article...

PRNewswire: SmartSens Technology has completed acquisition and merger with Shenzhen-based 8-year old Allchip Microelectronics. SmartSens expects its acquisition and integration of Allchip further improve its cost structure and competitiveness in the automotive market while accelerating its innovation in smart car CIS solutions. Allchip products include a series of SOC image sensors that have been widely deployed in automobile cameras and other miniaturized video surveillance applications.

"The increasing adoption of image sensors in automobiles has brought new momentum to the imaging market. According to a projection by research firm Yole Développement, the volume of camera modules in the global automobile market will exceed US$8B by 2025. Our acquisition of Allchip Microelectronics is a strategic move for SmartSens that will significantly broaden our leadership and capacity in addressing this market," said Richard Xu, Founder and CEO of SmartSens. "Our combined advantage -- utilizing shared resources and technologies -- will deliver a true win-win for us and our customers, for years to come."

"We are thrilled to be part of the SmartSens family. We share the same set of core values, which emphasize the pursuit of technology innovation in service of our customers' needs. We look forward to combining Allchip's technical know-how in the automotive industry with SmartSens' excellent business channel to successfully launch class-leading products for Automotive ADAS systems and other smart sensing applications," said Mike Hu, current VP of Technology at SmartSens and former CEO of Allchip. Mr. Hu is a veteran in CMOS image sensor field since his key role in BYD Microelectronics time as the CTO back in ten years ago.

Go to the original article...

Image Sensors World        Go to the original article...

University of Wisconsin–Madison: In a dark room or a motion-heavy scene, conventional cameras face a choice: a quick look that freezes movement nicely but turns out dark, or a longer exposure that captures more light but blurs moving parts.

“That’s always been a fundamental trade-off in any kind of photography,” says Mohit Gupta, a University of Wisconsin–Madison computer sciences professor. “But we are working on overcoming that trade-off with a different kind of sensor.”

The researchers are using SPADs for what they call quanta burst photography — taking many images in bursts, and then processing those many images to squeeze one good picture from a poorly lit or fast-moving subject. The EPFL The SwissSPAD array from Edoardo Charbon's group used in the burst photography work is fast enough to record 100,000 single-photon frames per second.

“The result is good image quality in low-light, with reduced motion blur, as well as a wide dynamic range,” says Gupta, whose work is supported by the DARPA. “We have had good results even when the brightest spot in view is getting 100,000 times as much light as the darkest.”


The paper also compares the algorithms running on SPAD and Jot-based sensors:

Go to the original article...

Image Sensors World        Go to the original article...

BusinessWire: It appears that Outsight gives up on its own LiDAR hardware and switches over to Velodyne as the companies jointly announce a multi-year partnership agreement.

Velodyne’s lidar sensors enable the 3D Semantic Camera solution to capture 3D data and track people and objects in a way that preserves anonymity and trust. The autonomous system merges lidar data capture with RGB color data with an embedded AI processing unit to create a premises-wide, detailed situational understanding of facilities, such as airports, shopping malls and train stations.

“Velodyne’s lidar sensors play an essential role in helping our platform capture, process and understand congested environments so operators can work to increase operational efficiency and security,” said Cedric Hutchings, CEO, Outsight. “The Velodyne lidar sensors allow us to track each individual person and object with centimeter-level precision. They enable our solutions to precisely monitor movements, velocity and interactions between all persons and objects in real time.”

AEye publishes "Time of Flight vs. FMCW LiDAR: A Side-by-Side Comparison" whitepaper which is supposed to debunk FMCW companies' claims:


UCB publishes a PhD Thesis on FMCW LiDAR "FMCW Lidar: Scaling to the Chip-Level and Improving Phase-Noise-Limited Performance" by Phillip Sandborn.

"In this dissertation, I present my work in chip-scale integration of optical and electronic components for application in coherent lidar techniques. First, I will summarize the work to integrate a typically bulky FMCW lidar control system onto an optoelectronic chip-stack. The chip-stack consists of an SOI silicon-photonics chip and a standard CMOS chip. The chip was used in an imaging system to generate 3D images with as little as 10um depth precision at standoff distances of 30cm.

Second, I will summarize my work in implementing and analyzing a new post-processing method for FMCW lidar signals, called "multi-synchronous re-sampling" (MK-re-sampling)."


Forbes publishes an interview-based article "The Big Bend Theory And Beyond- Are We There Yet?"

"I interviewed 4 companies that approach solid-state LiDAR in different ways – technically and from a market perspective. They include Quanergy, Lumotive, Draper Labs and Baraja. I would like to thank them for being transparent and sharing the level of detail they have."

Livox extends the range of its Tele-15 automotive LiDAR to 320m:

"Now, objects with low reflectivity have an increased detection range of 60% from 200 meters to 320 meters at 10% reflectivity, and it will also detect objects at 500m with 50% reflectivity, previously requiring 80% reflectivity at that distance. Additionally, Tele-15 now supports a custom firmware, increasing detection range to a maximum of 1000 meters.

The Livox Tele-15 sensor is available for purchase today for $1,499."

Go to the original article...

Image Sensors World        Go to the original article...

Applied Research LLC; Rockville, MD, USA publishes MDPI paper "Demosaicing of CFA 3.0 with Applications to Low Lighting Images" by by Chiman Kwan, Jude Larkin, and Bulent Ayhan.

"Low lighting images usually contain Poisson noise, which is pixel amplitude-dependent. More panchromatic or white pixels in a color filter array (CFA) are believed to help the demosaicing performance in dark environments. In this paper, we first introduce a CFA pattern known as CFA 3.0 that has 75% white pixels, 12.5% green pixels, and 6.25% of red and blue pixels. We then present algorithms to demosaic this CFA, and demonstrate its performance for normal and low lighting images.

In addition, a comparative study was performed to evaluate the demosaicing performance of three CFAs, namely the Bayer pattern (CFA 1.0), the Kodak CFA 2.0, and the proposed CFA 3.0. Using a clean Kodak dataset with 12 images, we emulated low lighting conditions by introducing Poisson noise into the clean images. In our experiments, normal and low lighting images were used. For the low lighting conditions, images with signal-to-noise (SNR) of 10 dBs and 20 dBs were studied. We observed that the demosaicing performance in low lighting conditions was improved when there are more white pixels.

Moreover, denoising can further enhance the demosaicing performance for all CFAs. The most important finding is that CFA 3.0 performs better than CFA 1.0, but is slightly inferior to CFA 2.0, in low lighting images."

Go to the original article...

Image Sensors World        Go to the original article...

i-Micronews: Chinese OLED screen company Visionox is the first to present under-display selfie camera solution for mass-produces smartphones, Visionox Inv See:

Go to the original article...

Image Sensors World        Go to the original article...

PRNewswire: Axcelis announces that it has shipped the first Purion XEmax high energy system to a "leading CMOS image sensor manufacturer." The system is a new tool evaluation and has been shipped in Q2.

"The new Purion XEmax high energy implanter was designed for emerging, high performance image sensor applications," Bill Bintz, Executive Vice President, Product Development explained. "The enhanced beamline features multiple filtration systems to eliminate energetic metal contaminants which can otherwise result in compromised dark current and white pixel count levels. The new system is built on the industry leading Purion XE high energy implant platform and features Axcelis' new patented Boost Technology, which delivers beam energies up to 15 MeV. With innovative new technology, the Purion XEmax is delivering the tightest angle and overall process control to enable higher quality photodiode performance for next generation CIS devices."

Go to the original article...

Image Sensors World        Go to the original article...

Qualcomm announces Snapdragon 690 5G platform with ISP than rivals high-end smartphones from 2 years ago:

"Vivid 4K HDR video recording is new to this series and have fun with up to 192 MP photo capture, both produce professional-quality photos and videos. And now, with 5G connectivity, 4K HDR streaming delivers vibrant, immersive entertainment."


Even Qualcomm Robotics RB5 platform supports high resolution imaging:

"Qualcomm Spectra™ 480 Image Signal Processor (ISP) captures fast, professional-quality photos and videos, and can process 2 Gigapixels per second. This Gigapixel speed supports superior camera features, including Dolby Vision video capture, 8K video recording (at 30 FPS) and 200-megapixel photos, and simultaneously captures 4K HDR video (at 120 FPS) and 64 MP photos with zero shutter lag. The hardware accelerator utilizes the Engine for Video Analytics (EVA) to handle all Computer Vision (CV) tasks. Additional ISP features include HEIF photo capture, slow motion video capture, and advanced video capture formats (including Dolby Vision, HDR10, HDR10+, HEVC and HLG). Seven concurrent cameras facilitate simultaneous localization and mapping (SLAM), object detection and classification, autonomous navigation and path planning to efficiently and safely perform tasks in complex indoor and outdoor settings."

Go to the original article...

Image Sensors World        Go to the original article...

Gpixel announces the further expansion of its GSENSE product family with the GSENSE1516BSI, a large format BSI CMOS sensor for high-end scientific applications. The sensor is designed around Gpixel’s 15 µm rolling shutter pixel, provides 4096 x 4096 resolution (16.7 MP), and supports up to 9fps in dual gain HDR mode.

Like other sensors in the GSENSE family, the GSENSE1516BSI can read out a single exposure with two different gain settings, providing two separate images that when recombined achieve up to 90dB intra-scene dynamic range. Using the low gain channel, the sensor’s full well capacity is 134ke–, maximizing signal to noise in the bright parts of the image. Through the high gain channel, the sensor achieves a read noise of 4e–, perfect for the measurement of faint signals.

The 15 µm pixel has 95% peak QE. Engineering samples of the GSENSE1516BSI will be available for evaluation in July 2020.

Go to the original article...

Image Sensors World        Go to the original article...

PRNewswire: SmartSens announces the launch of SC200AI sensor, the first of its Advanced Imaging (AI) series product lineup—high-performance, low-light-capable image sensor with advanced HDR capabilities and reliability in harsh environments. It features the latest BSI SmartClarity pixel as well as full-color night vision technology, employing a proprietary SFC (Source Follower Centric) enhanced design architecture to increase signal sensitivity and reduce noise levels, resulting in higher SNR and HDR performance.

Compared to previous generations of SmartSens image sensors, the SC200AI improves both sensitivity (27%) and SNRmax (250%). SC200AI also improves color reproduction by lowering Red-to-Green Channel Crosstalk by 36%. The SC200AI also has a 56% reduced dark current compared to previous generations of SmartSens image sensors.

“SC200AI marks a new chapter in our Smart Sensor offerings by dramatically enhancing the image quality across the board and lowering image noise levels in high-temperature environments,” said Chris Yiu, CMO of SmartSens. “As the latest member of our 1/2.8” 1080P product family, the SC200AI is fully Pin2Pin compatible with previous generation products. SmartSens continues to expand our supply chain and capacity support while delivering new technology that elevates the performance of our solutions in the security camera sector.”

The SC200AI Image Sensor line is available for sampling immediately, with mass production expected in late-June.

Go to the original article...

Image Sensors World        Go to the original article...

ResearchGate publishes SPIE presentation "Color imaging sensors with perovskite alloys" by Mohammad Ismail Hossain, Wayesh Qarony, Haris Ahmad Khan, Masayuki Kozawa, Alberto Salleo, Jon Yngve Hardeberg, Hiroyuki Fujiwara, Yuen Hong Tsang, and Dietmar Knipp from Hong Kong Polytechnic University, Norwegian University of Science and Technology, Gifu University (Japan), and Stanford University:

"The conventional optical color sensors consist of side by side arranged optical filters for three basic colors (blue, green, and red). Hence, the efficiency of such optical color sensors is limited by only 33%. In this study, vertically stacked color sensor is investigated with perovskite alloys, which has a potential to provide the efficiency approaching 100%. The proposed optical sensor will not be limited by color Moire error or color aliasing. Perovskite materials with suitable bandgaps are determined by applying energy shifting model and the optical constants are used for the further investigations. Quantum efficiencies and spectral responsivities of the described color sensors are investigated by three-dimensional electromagnetic simulations. Investigated spectral sensitivities are further analysed for the colorimetric characterization. Finally, the performance of the investigated sensor is compared with conventional filter based optical color sensors. Details on the used materials, the device design, and the colorimetric analysis are provided."

Go to the original article...

Image Sensors World        Go to the original article...

CEA-Leti publishes PhD Thesis "Test and characterization of 3D high-density interconnects" by Imed Jani.

"Compared to μ-bumps, Cu-Cu hybrid bonding provides an alternative for future scaling below 10μm pitch with improved physical properties but that generates new challenges for test and characterization; the smaller the Cu pad size, the more the fabrication and bonding defects have an important impact on yield and performance. Defects such as bonding misalignment, micro-voids and contact defects at the copper surface, can affect the electrical characteristics and the life time of 3D-IC considerably.

Moreover, test infrastructure insertion for HD 3D-ICs presents new challenges because of the high interconnects density and the area cost for test features. Hence, in this thesis work, an innovative misalignment test structure has been developed and implemented in short-loop way. The proposed approach allows to measure accurately bonding misalignment, know the misalignment direction and estimate the contact resistance. Afterwards, a theoretical study has been performed to define the most optimized DFT infrastructure depending on the minimum acceptable pitch value for a given technology node to ensure the testability of high-density 3D-ICs."

Go to the original article...

Image Sensors World        Go to the original article...

Android Authority talks about a trend of increasing the sensor size in smartphone cameras:


"Previously, it seemed impossible to stuff a sensor this large in a phone. Phones were just too small, and focus was put on making devices thinner and thinner. It was hard to make a lens system that didn’t bulge out of the device to an extreme degree. But, as phones have gotten bigger and cameras have gotten more important to users, big camera bumps have started to become both justified and normalized. Instead of looking clunky and out of place, large camera bumps have started to become a sign of a phone’s optical capabilities."

Counterpoint Research sees this trend too:

Go to the original article...

Image Sensors World        Go to the original article...

EPIC Online Technology Meeting on Structured Light and Computer Vision features Prophesee presentation on use of its event-driven sensor for 3D structured-light camera:

Go to the original article...

Image Sensors World        Go to the original article...

Agricultural University of Georgia, country of Georgia, publishes MSc Thesis "Characterization of Silicon Photomultipliers for Detector Developments" by Davit Kordzaia.

"The SiPM has been given several denominations by different institutes and manufacturers, such as:

• MPGM APD (multi-pixel Geiger-mode avalanche photodiode)
• AMPD (avalanche micro-pixel photodiode)
• SSPM (solid state photomultiplier)
• G-APD or GM-APD (Geiger-mode avalanche photodiode)
• DPPD (digital pixel photodiode)
• MPPC (multi-pixel photon counter)
• MAD (multi-cell avalanche diode)

This thesis is focused on investigating the processes of charge release and the photon detection efficiency (PDE) recovery of the SiPM, vital for understanding the linearity and the saturation phenomenon of the sensor. The experiment has been conducted on a single SPAD (Single Photon Avalanche Diode) level, instead of the entire sensitive area of the SiPM. This work offers a complete overview of investigation of the surface cover, for achieving the single SPAD illumination, development of the readout electronics and implementation of different apparatus and measurement methods used to perform the experiment."

Go to the original article...