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The 1st International SPAD Sensor Workshop will be held on Feb. 26-28, 2018 in Swiss Alps. The workshop is sponsored by IISS with financial support by SensL, STMicroelectronics, AMS, XFab, TSMC, MPD, Fastree3D, and TowerJazz. The Steering Committee selected over 20 invited speakers from the SPAD community that have been active in one of the big three themes of the workshop: SPAD Technology, Architectures, and Applications.

Online registration will open Wednesday January 10th 2018 at 8:00 am (Swiss time) and will close when maximum attendance is reached.

The Workshop location - village Christophe Racat

SPAD Workshop Agenda

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PRNewswire: OmniVision introduced the 1/2.8-inch 24MP OV24A family, built on the PureCel Plus stacked die architecture. These are OmniVision’s first 0.9um pixel sensors for smartphone applications. The PureCel Plus stacked die 0.9um pixel leverages multiple generations of pixel technologies to match the latest 1.0um pixel QE.

The OV24A sensor family consists of three products: the OV24A1Q, OV24A1B and OV24A10. All three versions of the OV24A sensors can support PDAF. The OV24A1Q, with its unique 4-cell color filter pattern, is ideal for front-facing camera applications. This sensor has an on-chip, in-pixel binning feature that captures four times more light photons than a regular 0.9um pixel for better image quality in low-light conditions. Additionally, an application can recover an image to full 24Mp resolution, when paired with OmniVision’s software.

The OV24A1B (monochrome) and OV24A10 (Bayer) are used for main-camera and/or dual-camera configurations, enabling zoom and Bokeh features, and improved low-light performance.

Additionally, increasing image quality for the rear-facing main smartphone camera remains of the utmost importance to most consumers. When it is paired in a dual-camera configuration, the OV24A10 and/or OV24A1B sensors’ 24Mp resolution provides a higher zoom ratio, portrait mode effect, and higher quality still images and video in low light.

The OV24A1Q and OV24A10 provide HDR for still images, as well as HDR video with full resolution at 30fps.

Recent studies have predicted that millennials will take over 25,000 selfies during their lifetime. Image quality is becoming an increasingly important factor in this demographic’s smartphone buying decisions. “Smartphone image quality is essential to many consumers, and social media has particularly inspired millennials to make good use of high-resolution front-facing cameras,” said James Liu, product marketing manager at OmniVision. “Our OV24A image sensor family was developed to address the needs of these savvy consumers, who expect the highest quality stills and videos from their smartphones.”

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ElectronicsMaker: Hisense Group and its subsidiary Hisense TransTech and Corephotonics unveil TransportEye stereo camera, said to have the longest detection range currently supported by any automotive stereo camera – reaching distances of up to 100m with a camera baseline of just 12cm.

“This strategic collaboration with Hisense Group is an important milestone for Corephotonics. It extends our reach beyond the mobile sector into exciting new vertical markets, such as automotive,” states David Mendlovic, CEO of Corephotonics. “The combination of our unique innovations in camera design and computational imaging, together with Hisense’s technologies and extensive production capabilities has proven essential for the success of this venture.”


The companies Youtube video demos the camera performance:

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JPL image sensing leader Shouleh Nikzad has been elected to the rank of Fellow in the National Academy of Inventors (NAI). The NAI Fellows Selection Committee chose her for induction as she “demonstrated a highly prolific spirit of innovation in creating or facilitating outstanding inventions that made a tangible impact on quality of life, economic development, and the welfare of society.”

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GlobeNewsWire: DSP Group, Emza Visual Sense, and Himax announce the WiseEye IoT, said to be the industry’s first ultra-low power, always-on, intelligent visual sensor adding human presence awareness for consumer appliances and industrial IoT applications.

DSPG’s ULE and SmartVoice solutions, Emza’s machine vision algorithms, and Himax’s low power CMOS Sensor yield a commercially available sensor capable of detecting, localizing, counting and profiling people.

“Machine learning-based sensors enhance the intelligence and functionality of any device, and our trainable WiseEye IoT solution aims at bringing these capabilities to the vast and largely untapped IoT space in both consumer and industrial domains,” said Yoram Zylberberg, CEO of Emza Visual Sense. “In DSP Group, we found a unique combination of offering that fits any IoT supplier – a low power SoC that can serve as a computing platform for our advanced algorithm and ULE modules for easy integration with IoT systems.”

“Himax CMOS Image Sensor, HM01B0, is the first to be specially designed to benefit the computer vision algorithm and we are excited to be a part of this sophisticated new joint offering from Emza and DSP Group,” commented Amit Mittra, CTO of Himax Imaging. “Low power and high performance are critical to the success of this application. Using our CMOS Image Sensor gives WiseEye the ability to bring computer vision to new applications that have been hard to reach before due to cost, performance, and power constraints.”

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BusinessWire: Velodyne LiDAR announces a cost reduction for its most popular LiDAR sensor. The VLP-16 is now offered to customers around the world for up to a 50% cost reduction.

“Demand for our VLP-16s grew tremendously in 2017. As a result, we increased capacity and now can pass along savings as cost reduction to our customers,” said David Hall, Founder and CEO, Velodyne LiDAR. “We want to make 2018 a year of optimism for the autonomous vehicle, especially as the first waves of robocabs hit the road. Our goal is the democratization of transportation safety by making it accessible to every man, woman, and child in the world as quickly as possible.”

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Aphesa comes up with a nice list of pixel defects:

• Dead pixels do not respond to light at all and they don't provide any information. Dead pixels can be black, white (or let's say the maximum output value) or any intermediate value (also called stuck pixels).
• Hot pixels respond do light normally but suffer from excessive dark current and can saturate at reasonable exposures even in the dark.
• RTS pixels respond to light and provide once in a while a sequence of correct values but they can randomly jump up and down with a well defined offset. RTS also can be in a dark current where the dark current value randomly jumps between few discrete values.
• Wide variance noise pixels have in average the right response to light but their noise is much larger than for the other pixels.
• Blinking pixels can be either dead blinking if they jump randomly between two dead states or blinking operating if they jump between the right value and a dead state.
• Clipping pixels behave normally up to a certain value (resp. from a certain value) where they will clip. They are only usable below (resp. above) their clipping value.
• The pixels that start at a too high value sometimes only have excessive offset (can be caused by an excessive FD leakage, or memory node leakage in global shutter pixels.)

While the list is quite exhaustive and covers most of the known effects, there are few more that could be added:

• Pixel with excessive image lag - can manifest itself as a non-linearity at low light. Can only appear at low temperatures. Depending on the array timing, can only appear in high frame rate modes.
• Large crosstalk pixels - some pixels can suffer from too much coupling between them
• Defective color response - can come from defects in color filter
• Anomalously high or low photoresponse (too high PRNU) - can be caused by contamination particles masking a part of the light, or defects in metals, light pipes, etc.
• Dark current that non-linearly depends on the integration time (for example, starts from high and getting lower after a couple of ms.)

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Arxiv.org paper "Super-Resolution Quantum Imaging at the Heisenberg Limit" by Manuel Unternährer, Bänz Bessire, Leonardo Gasparini, Matteo Perenzoni, and André Stefanov from FBK, Italy and Institute of Applied Physics, University of Bern, Switzerland combines an entangled photons light source and a single-photon imager to overcome diffraction resolution limit:

"Quantum imaging exploits the spatial correlations between photons to image object features with a higher resolution than a corresponding classical light source could achieve. Using a quantum correlated N-photon state, the method of optical centroid measurement (OCM) was shown to exhibit a resolution enhancement by improving the classical Rayleigh limit by a factor of 1/N. In this work, the theory of OCM is formulated within the framework of an imaging formalism and is implemented in an exemplary experiment by means of a conventional entangled photon pair source. The expected resolution enhancement of a factor of two is demonstrated. The here presented experiment allows for single-shot operation without scanning or iteration to reproduce the object in the image plane. Thereby, photon detection is performed with a newly developed integrated time-resolving detector array. Multi-photon interference effects responsible for the observed resolution enhancement are discussed and possible alternative implementation possibilities for higher photon number are proposed."


"In conclusion, our theoretical and experimental results demonstrate that quantum states of light showing super-resolution at the Heisenberg limit can be engineered. By limiting the Rayleigh resolution in low NA single-lens imaging, different light sources are compared in their ability to transmit spatial information. The OCM biphoton state used in our experiment shows a resolution enhancement close to a factor of two and is comparable to imaging at half the wavelength. For high NA systems, where the classical resolution is mainly limited by the wavelength, or for higher photon number N, theory suggests the possibility to have sub-wavelength image features present in the centroid coordinate. A full vectorial field analysis in contrast to the scalar approximations has yet to show the advantage in the limit of high NA.

Integrated single-photon detector arrays as presented here will certainly give rise to more experiments and applications in the field of quantum imaging. While the device in this work has non-optimal detection efficiency at the used wavelength, a speed up in acquisition time and higher photon number correlation measurement is expected in more optimized settings."

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Japan Times reports that "Facial recognition technology will be used at the Tokyo 2020 Olympics and Paralympics to streamline the entry of athletes, officials and journalists to the games venues.

In light of concerns about terrorism, the games’ organizers aim to bolster security and prevent those involved in the 2020 Games from lending or borrowing ID cards.

The Justice Ministry deployed gates using facial recognition technology to screen passengers at Tokyo’s Haneda airport in October."

DailyMail reports about more cases of Apple Face ID false positive identifications in China.


Not only Apple face recognition system can fail. ZDNet reports that Germany-based SySS was able to trick some versions of Windows Hello on Surface Pro 4 equipped with an IR camera used by face recognition:



BLCV publishes a series of articles "Demystifying Face Recognition", currently 4 articles explaining everything from basics to more advanced computer learning aspects.

EETimes publishes an article about Germany-based FZI Research Center for Information Technology camera based face recognition and analyzing system to monitor driver's attention status:


Forbes: Facebook adds an optional face recognition feature that lets users find out when they appear in someone else's photos.

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Samsung image sensor web page has been updated recently and now shows just two product categories - mobile and automotive:


The mobile category is 21-sensor large:


The automotive offerings are less extensive but include the Mobileye-speced 7.4MP, RCC sensor with 120dB DR (S5K2G1, sampling now):

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Bloomberg quotes Satoshi Yoshihara, GM of Sony image sensors division saying on 3D image sensing: "This has the scale to become the next pillar of our business."

"The most immediate impact from TOF sensors, which will be fabricated at Sony’s factories in Kyushu, will probably be seen in augmented-reality gadgets.

“Sony has everything technology-wise to address the market,” said Pierre Cambou, an imaging analyst at Yole. “They shouldn’t have a problem gaining a large share in 3D.”

When Sony decided to gamble on time-of-flight sensors three years ago, it faced a choice between building or buying the technology. In 2015, Sony decided to acquire Softkinetic Systems, a small developer of TOF sensors.

“When our engineers and their engineers talked about collaborating, we realized we could come up with an amazing sensor,” Yoshihara said of the merger. “In terms of both (chip) performance and size, we can achieve another breakthrough.”

Alexis Breton, a spokesman for STMicro, declined to comment, pointing to recent data showing that it’s shipped more than 300 million TOF chips. STMicro’s revenue from the division that mostly includes the sensors was $295 million last year."


Panasonic too presents a number of 3D ToF cameras:


Basler uses Panasonic ToF sensors in its 3D cameras. The company's ToF products marketing manager Jana Bartels explains the camera features:

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Oslo University, Norway publishes a nice Q&A exercise from its Image Sensor Circuits and Systems course by Soman Cheng and Johannes Sølhusvik. One can also try to pass an exam circa 2014 or 2015.

Lectures on some of the topics are available on-line, such as Characterization, Noise, Offset and Noise Compensation, Optics, MOSFET and Pixel Readout, Color Theory, and more.

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MIT Media Lab publishes a IEEE Access paper "Rethinking Machine Vision Time of Flight
With GHz Heterodyning" by Achuta Kadambi and Ramesh Raskar presenting "time-of-flight imaging that increases its depth resolution 1,000-fold. That’s the type of resolution that could make self-driving cars practical... At distances of 2 meters, the MIT researchers’ system... has a depth resolution of 3 micrometers."

The paper presents an indirect ToF imaging with a GHz modulation frequency:


A Youtube video explains the group's achievement:



Thanks to DS for the pointer!

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Hamamatsu publishes a nice deck of slides from its LiDAR webinar on Dec 6, 2017 "LiDAR and Other Techniques, Measuring Distance with Light for Automotive Industry" by Slawomir Piatek. The 66-page presentation compares 905nm vs 1550nm bands, mecanical vs MEMS vs OPA scanning, flash, and FMCW approaches, and much more:

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ISH Market presentation "(R)Evolution of Automotive Electronics" by Akhilesh Kona at Semicon Europe mostly talks about LiDAR technology:

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Zurich, Switzerland-based Insightness uses its new event-driven Silicon Eye sensor and of pose estimation tracks from new EIVO tracking pipeline overlayed with APS images to draw Christmas tree.
- APS frame rate and rendering at 10Hz
- Pose estimation based on events

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Optics Express publishes an open-access paper "Spectral sorting of visible light using dielectric gratings" by Ujwol Palanchoke, Salim Boutami, and Serge Gidon, Commissariat à l'Energie Atomique et aux Energies Alternatives, Grenoble, France. From the abstract:

"We show that by using grating structures, the spectral sorter structures are more efficient when the detector size is less than 1µm, enabling the shrinking of the detector size to the wavelength scale. A comprehensive design strategy is derived that could be used as a design guideline to achieve the sorting of visible light. We show that for pixel size as small as 0.5µm, optical efficiency as high as 80% could be achieved using dielectric based sorting structures."

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BusinessWire: UCB keeps promoting its DiffuserCam project first presented in October. An open source paper "DiffuserCam: lensless single-exposure 3D imaging" by Nick Antipa, Grace Kuo, Reinhard Heckel, Ben Mildenhall, Emrah Bostan, Ren Ng, and Laura Waller is published in OSA Optica. The camera open-source code is also available on GitHub.

"...the researchers show that the DiffuserCam can be used to reconstruct 100 million voxels, or 3D pixels, from a 1.3-megapixel (1.3 million pixels) image without any scanning.

...Although the hardware is simple, the software it uses to reconstruct high resolution 3D images is very complex.

The DiffuserCam is a relative of the light field camera, which captures how much light is striking a pixel on the image sensor as well as the angle from which the light hits that pixel.

Until now, light field cameras have been limited in spatial resolution because some spatial information is lost while collecting the directional information. Another drawback of these cameras is that the microlens arrays are expensive and must be customized for a particular camera or optical components used for imaging.

using random bumps in privacy glass stickers, Scotch tape or plastic conference badge holders, allowed the researchers to improve on traditional light field camera capabilities by using compressed sensing to avoid the typical loss of resolution that comes with microlens arrays.

Although other light field cameras use lens arrays that are precisely designed and aligned, the exact size and shape of the bumps in the new camera’s diffuser are unknown. This means that a few images of a moving point of light must be acquired to calibrate the software prior to imaging. The researchers are working on a way to eliminate this calibration step by using the raw data for calibration. They also want to improve the accuracy of the software and make the 3D reconstruction faster."

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Hamamatsu publishes a number of videos on its ToF sensors:

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Reuters publishes an article on Sony image sensor business. Few quotes:

Sony Corp is poised to report its highest-ever profit this year on strong sales of image sensors after years of losing ground in consumer electronics and hopes to develop the technology for use in robotics and self-driving cars as competition heats up.

Executives say a technological breakthrough in image sensors and seachange in the company’s thinking are behind the success. The breakthrough, creating a sensor that captures more light to produce sharper images, coincided with soaring consumer demand for better smartphone cameras for sharing photos on social media.

The breakthrough, which involved reconfiguring the sensor layout and known as backside illumination, allowed Sony to grab nearly half of the market for image sensors.

“We knew we wouldn’t be able to win if we did what our rivals were doing,” said Teruo Hirayama, technology chief of Sony’s chip business, recalling initial scepticism around the technology that is now used widely.

“It was a great help for us to be told that we should operate independently,” Terushi Shimizu, the chief of Sony’s chip division, said, “rather than just belong to Sony.”

But the company is already bracing for intensifying competition in sensors as rivals, such as Samsung and OmniVision Technologies, step up their game, and is developing new sensor technologies for use in robotics and self-driving cars.

Investors say Sony still has a technological advantage that will take time for others to replicate.

“Sony has been trying to be ahead, but could face a turning point in a year or two,” said Kun Soo Lee, senior principal analyst with IHS Markit in Tokyo.

It is developing sensor technologies that can quickly measure distances or detect invisible light that are expected to be used in autonomous driving, factory automation and robotics, they said.

“It’s clear that we are currently dependent on the smartphone market,” Shimizu, the chip business chief said. “The market’s shift to dual-lens cameras from single-lens is good for us, but how long is this going to last as the market is only growing 1 or 2 percent?”

Terushi Shimizu, the chief of Sony’s chip division

Terushi Shimizu, the chief of Sony’s chip division

Teruo Hirayama, technology chief of Sony’s chip business

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Magic Leap unveils its first AR product - Magic Leap One Creator Edition glasses. There is an impressive camera and vision technology integrated into the glasses:


Rolling Stone was given a chance to see Magic Leap demo and was generally positive about the new glasses performance.

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Albert Theuwissen's IEEE webinar "Noise: You Love It or You Hate It" to be held on January 24, 2018 10:00am EST, will focus on the various noise sources present in a CMOS image sensor. A CMOS image sensor is a great example of a mixed-signal
circuit : the analog pixel array is driven by digital control signals. The analog output signal generated by the pixel array, goes through a denoising step in the analog domain before being converted to the digital domain. So it should not be surprising that a CMOS image sensor is a complex collection of different noise sources.

This webinar will address the most important noise sources in a CMOS image sensor, from temporal noise to spatial noise. The origin of those noise sources will be explained and countermeasures will be suggested. A lot of the countermeasures are already implemented in today's devices. Without the tremendous noise reduction techniques developed in the last decades, it would never ever have been possible to make color images at the extreme low light levels like we have at this moment. The noise floor of today's devices is that low that we can almost detect single electrons with standard consumer devices. Noise : do you love it or do you hate it? As a consumer I hate it, as an imaging engineer I love it! (These are Albert Theuwissen's words. As of me, I hate noise in any capacity.)

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TechInsights image sensor Senior Technical Analyst Ray Fontaine posts "Image Sensor Technology: Noteworthy Developments in 2017." The short article includes a lot of information:

"A noteworthy twist on Bayer RGB is Samsung’s TetraCell and OmniVision’s 4-Cell strategy for high resolution front-facing cameras. This strategy enables in-pixel binning for greater sensitivity (with lower resolution) for low-lit scenes.

...as we end 2017 we are happy to announce we have found 0.9 µm generation pixels in mass production!

...we are tracking new types of associated autofocus (AF) systems, including: laser-assist, lossless phase detection autofocus (PDAF) in 1.0 µm telephoto camera chips, new types of masked PDAF, etc. Samsung is notable for its preference of a dual photodiode (Dual Pixel) AF system that is successful in its own right, and does not currently require laser-assist AF.

...we still primarily see TSV-based chip-to-chip interconnect, although Sony has been using direct bond interconnects (Cu-Cu hybrid bonding, or DBI) since early 2016. We recently saw OmniVision and foundry partner TSMC join the hybrid bonding club and claim the new world record, based on TechInsights’ findings, of 1.8 µm diameter, 3.7 µm pitch DBI pads.

...we’ve tracked in 2017 is the continued emergence of cameras with improved near infrared (NIR) sensitivity... We’re also analyzing the structures from new process flows in use, such as the pyramid surface diffraction structures on the SmartSens SC5035. Sony has previously announced a similar approach, and we expect a comparable structure in use for OmniVision’s announced Nyxel platform."

Samsung 0.9 µm ISOCELL Pixel with Tetracell Color Filters

STM SOI IR Sensor from Apple iPhone X

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XDA Developers quotes Italian-language Notebook Italia info about Huawei "Point Cloud Depth Camera" based on an interview with one of Huawei engineers and the recent company presentation already mentioned in the previous post.




Here are the last few minutes from Huawei presentation in London:

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After announcing development of BSI ToF sensor half a year ago, Sony announces the release of 1/2-inch VGA IMX456QL product, with samples shipments planned for April 2018. The pixel size is about 10um.

"While conventional ToF sensor has difficulty in measuring far distance of approximately 10 meters, the new product comes with a sensitivity raising mode, enabling distance measurement with a high rate of detection at these distances. It is also possible to capture high-precision depth maps in a VGA resolution at close distances of approximately 30 centimeters to 1 meter.

Additionally, because this sensor captures depth maps for each frame, it enables image capture at a higher frame rate than when using a laser to scan the object for distance measurement. This reduces distortion of moving subjects in depth maps."

G