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Albert Theuwissen discusses imager's Dynamic Range definition and factors that often make a measured DR be lower than one specified in the datasheet.

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Canon Watch site noticed Egami article on Canon sensor with curved periphery portion, said to improve lens vignetting:


Update: Mirrorless Rumors site posted another patent from Egami , this time applied by Toshiba for a curved sensor:

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Nikkei: Tamron announces successful development of an innovative image sensor technology, with support of Japan Science and Technology Agency (JST) of National Research and Development Agency, that enhances imaging capability far exceeding that of human vision, featuring ultra-high light sensitivity and WDR.

The new technology is said to enhance both sensitivity and DR, which has been considered difficult in the past. The ultra-high sensitivity enables capturing clear color images even under an extreme low brightness of 0.003 lux, which is darker than starlight. The WDR performance is exceeding 140dB.


Three key technologies - Optics, Image Sensor, and Image Processing - have been identified essential, and their effective integration has been studied for the new imaging technology:


This development is supported by Japan Science and Technology Agency (JST), Adaptable and Seamless Technology transfer Program through Target-driven R&D (A-STEP).

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Brigates publishes fairly detailed datasheets of its image sensors with characterization data. It's a brave move as some of the parameters are quite far from the state of the art.

BG0703 is a 1MP 1/2.7-inch rolling shutter image sensor aimed to high-end surveillance and industrial imaging markets:


A newer and improved 1080p 1/3-inch BG0803 targets the same market:

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French-language site Challenges reports that ST has signed a huge contract with Apple for image sensors, which will boost the workload at its Crolles plants, where fifty new machines are being installed. The influx of this and other new orders allows the Crolles 200mm fab to reach utilization rate of 100%, while Crolles 300mm plant utilization exceeds 80%. When questioned, ST group refused to comment.

Possibly, the French site talks about ST AF ToF sensors used in iPhone 7.

Thanks to SL for the link!

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MediaTek announces its plan to bring ADAS vision solutions to the automotive industry beginning Q1 2017:

"Reimagined from the ground up, MediaTek’s ADAS system will feature cutting-edge, decentralized Vision Processing Unit (VPU) solutions to optimally handle large amounts of real-time visual streaming data. MediaTek employs Machine Learning to increase the accuracy and speed of detection, recognition and tracking, making it more comparable to human decision-making performance."

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Reuters, NYT: Intel will provide a SoC for autonomous vehicle systems that Delphi and Mobileye are developing together, Glen De Vos, Delphi's VP Engineering said. Delphi is testing autonomous driving technology in vehicles in Singapore. By the end of this year, Delphi hopes to choose a city in the United States to launch a test fleet of self-driving cars during 2017, De Vos said. The company is also looking for test site in a European city.

Delphi and Mobileye will demo their self-driving vehicle system at the CES in Las Vegas in January. That system will use current, electromechanical laser imaging technology, or LIDAR, that is too expensive for use in consumer vehicles, he said. Delphi is also working with Quanergy Systems, a maker of solid-state LIDAR systems.

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Novus Light discusses Sony proprietary Scalable Low Voltage Signalling with an Embedded Clock (SLVS-EC) interface, which debuts in the company's next generation of image sensors for industrial applications. The interface has been mentioned quite a long time ago in Sony papers such as this one, allowing to output signal independently from 4 corners of the chip:


In SLVS-EC, the clock signal is embedded in the data and recovered by dedicated circuitry on the receive side. Since the signals are then less sensitive to skew, the data can be transmitted at much higher data rates and over much further distances. Each of the SLVDS-EC channels can support speeds of up to 2.304Gbit/sec. The result is that a sensor that supports the new standard will be able to transfer data over eight links at a data rate of 1.84GBytes/sec (80% of full bandwidth due to 8b10b encoding).

I'm not sure what is the difference between MIPI M-PHY and SLVDS-EC, but Sony promotes its high speed:

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ARMdevices interviews Jem Davies, ARM VP of Technology, Imaging and Vision Group. Jem talks about imaging and vision strategy at ARM and says that Huawei will be one of the first licensees of its imaging ad vision technology in smartphones:



Jem Davies ARM Techcon 2016 presentation video posted on Nov. 22 has been updated, so that its end part is not cut anymore.

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LIPS receives 2016 Golden Torch Innovation Award from Outstanding Enterprise Manager Associate in Taiwan for the technologies behind its depth camera innovation.

LIPS Founder & CEO Luke Liu receiving award from the  former Taiwan’s vice president Dwen-Yi Wu

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AutoSens 2016 kindly permitted me to post a couple of slides from Softkinetic presentation "3D depth-sensing for automotive: bringing awareness to the next generation of (autonomous) vehicles" by Daniel Van Nieuwenhove. A good part of the presentation compares ToF with active and passive stereo solutions:

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According to BusinessKorea sources, Samsung is contemplating to split its semiconductor business into a fabless and foundry divisions:

"Samsung Electronics’ System LSI business division is largely divided into four segments; system on chip (SoC) team which develops mobile APs, LSI development team, which designs display driver chips and camera sensors, foundry business team and support team. According to many officials in the industry, Samsung Electronics is now considering forming the fabless division by uniting the SoC and LSI development teams and separating from the foundry business."

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NikonRumors quotes Egami talking about Nikon patent application with 2-layered pixel array forming a cross-type PDAF: "Nikon patent application is to use the two imaging elements having different phase difference detection direction in order to achieve a cross-type AF."


Thanks to TG for the link!

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Framos publishes interviews with Framos North America VP Sebastian Dignard and ON Semi Go To Market Manager Michael DeLuca on image sensor innovations:

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Edoardo Charbon and Junichi Nakamura has been elevated to IEEE Fellows. Thanks to AT for the info!

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Nikkei publishes an article with more details on Hitachi lens-less camera:

"In general, the method that Hitachi employed for its lens-less camera uses a "moire stripe" that can be obtained by stacking two concentric-patterned films with a certain interval and transmitting light through them. The numerous light-emitting points constituting the image influence the pitch and orientation of the moire stripe. The location of light, etc can be restored by applying two-dimensional Fourier transformation to the moire stripe.

This time, Hitachi replaced one of the films (one that is closer to the image sensor) with image processing. In other words, one film is placed with an interval of about 1mm, but the other film does not actually exist. And, instead of using the second film, a concentric pattern is superimposed on image data."

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ISSCC publishes its 2017 advance program. Sony is going to present its 3-die stacked sensor, a somewhat expected evolution of the stacking technology:

A 1/2.3in 20Mpixel 3-Layer Stacked CMOS Image Sensor with DRAM
T. Haruta, T. Nakajima, J. Hashizume, T. Umebayashi, H. Takahashi, K. Taniguchi, M. Kuroda, H. Sumihiro, K. Enoki, T. Yamasaki, K. Ikezawa, A. Kitahara, M. Zen, M. Oyama, H. Koga, H. Tsugawa, T. Ogita, T. Nagano, S. Takano, T. Nomoto
Sony Semiconductor Solutions, Atsugi, Japan
Sony Semiconductor Manufacturing, Atsugi, Japan
Sony LSI Design, Atsugi, Japan

Canon presents, apparently, a version of its IEDM global shutter sensor paper with more emphasis on the readout architecture:

A 1.8erms Temporal Noise Over 110dB Dynamic Range 3.4μm Pixel Pitch Global Shutter CMOS Image Sensor with Dual-Gain Amplifiers, SS-ADC and Multiple-Accumulation Shutter
M. Kobayashi, Y. Onuki, K. Kawabata, H. Sekine, T. Tsuboi, Y. Matsuno, H. Takahashi, T. Koizumi, K. Sakurai, H. Yuzurihara, S. Inoue, T. Ichikawa
Canon, Kanagawa, Japan

Other nice papers in the Imager session are listed below:

A 640×480 Dynamic Vision Sensor with a 9μm Pixel and 300Meps Address-Event Representation
B. Son, Y. Suh, S. Kim, H. Jung, J-S. Kim, C. Shin, K. Park, K. Lee, J. Park, J. Woo, Y. Roh, H. Lee, Y. Wang, I. Ovsiannikov, H. Ryu
Samsung Advanced Institute of Technology, Suwon, Korea;
Samsung Electronics, Pasadena, CA

A Fully Integrated CMOS Fluorescence Biochip for Multiplex Polymerase Chain-Reaction (PCR) Processes
A. Hassibi, R. Singh, A. Manickam, R. Sinha, B. Kuimelis, S. Bolouki, P. Naraghi-Arani, K. Johnson, M. McDermott, N. Wood, P. Savalia, N. Gamini
InSilixa, Sunnyvale, CA

A Programmable Sub-Nanosecond Time-Gated 4-Tap Lock-In Pixel CMOS Image Sensor for Real-Time Fluorescence Lifetime Imaging Microscopy
M-W. Seo, Y. Shirakawa, Y. Masuda, Y. Kawata, K. Kagawa, K. Yasutomi, S. Kawahito
Shizuoka University, Hamamatsu, Japan

A Sub-nW 80mlx-to-1.26Mlx Self-Referencing Light-to-Digital Converter with AlGaAs Photodiode
W. Lim, D. Sylvester, D. Blaauw
University of Michigan, Ann Arbor, MI

A 2.1Mpixel Organic-Film Stacked RGB-IR Image Sensor with Electrically Controllable IR Sensitivity
S. Machida, S. Shishido, T. Tokuhara, M. Yanagida, T. Yamada, M. Izuchi, Y. Sato, Y. Miyake, M. Nakata, M. Murakami, M. Harada, Y. Inoue
Panasonic, Osaka, Japan

A 0.44erms Read-Noise 32fps 0.5Mpixel High-Sensitivity RG-Less-Pixel CMOS Image Sensor Using Bootstrapping Reset
M-W. Seo, T. Wang, S-W. Jun, T. Akahori, S. Kawahito
Shizuoka University, Hamamatsu, Japan;
Brookman Technology, Hamamatsu, Japan

A 1ms High-Speed Vision Chip with 3D-Stacked 140GOPS ColumnParallel PEs for Spatio-Temporal Image Processing
T. Yamazaki, H. Katayama, S. Uehara, A. Nose, M. Kobayashi, S. Shida, M. Odahara, K. Takamiya, Y. Hisamatsu, S. Matsumoto, L. Miyashita, Y. Watanabe, T. Izawa, Y. Muramatsu, M. Ishikawa;
Sony Semiconductor Solutions, Atsugi, Japan;
Sony LSI Design, Atsugi, Japan
University of Tokyo, Bunkyo, Japan

The tutorials day includes one on deep learning processors:

Energy-Efficient Processors for Deep Learning
Marian Verhelst
KU Leuven, Heverlee, Belgium

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Basler: After a successful conclusion of the evaluation phase and extremely positive customer feedback, Basler first ToF camera is now entering series production. The VGA ToF camera is said to stand out for its combination of high resolution and powerful features at a very attractive price. This outstanding price/performance ratio puts the Basler ToF camera in a unique position on the market and distinguishes it significantly from competitors' cameras.

The Basler ToF camera operates on the pulsed time-of-flight principle. It is outfitted with eight high-power LEDs working in the NIR range, and generates 2D and 3D data in one shot with a multipart image, comprised of range, intensity and confidence maps. It delivers distance values in a working range from 0 to 13.3 meters at 20fps. The measurement accuracy of the Basler ToF camera is +/-1 cm at a range from 0.5 to 5.8 meters, while consuming 15W of power.

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ARMDevices interviews Movidius VP Marketing, Gary Brown, on the company low power advantages of their vision processor in different applications:

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IEEE Electron Devices Society publishes a list of this year's awards. Jaroslav Hynecek receives 2016 EDS J.J. Ebers Award for "For the pioneering work and advancement of CCD and CMOS image sensor technologies." The Award is to be presented at IEDM in December.

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Open-access Sensors journal publishes Purdue University paper "Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors" by Stanley H. Chan, Omar A. Elgendy, and Xiran Wang. From the abstract:

"Because of the stochastic nature of the photon arrivals, data acquired by QIS is a massive stream of random binary bits. The goal of image reconstruction is to recover the underlying image from these bits. In this paper, we present a non-iterative image reconstruction algorithm for QIS. Unlike existing reconstruction methods that formulate the problem from an optimization perspective, the new algorithm directly recovers the images through a pair of nonlinear transformations and an off-the-shelf image denoising algorithm. By skipping the usual optimization procedure, we achieve orders of magnitude improvement in speed and even better image reconstruction quality. We validate the new algorithm on synthetic datasets, as well as real videos collected by one-bit single-photon avalanche diode (SPAD) cameras."


Thanks to EF for the link!

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ARM fellow Jem Davies describes the company approach to imaging opportunities:

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Xilinx publishes a demo of its neural learning network. Alexnet, although somewhat dated by modern standards, seems to remain the most popular for such capability statements:

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