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PRNewswire: OmniVision announces the OV48C, a 48MP image sensor with a large 1.2um pixel size for flagship smartphone cameras. The OV48C is the industry's first image sensor for high resolution mobile cameras with on-chip dual conversion gain HDR, which reduces motion artifacts and produces better SNR. This sensor also offers a staggered HDR option with on-chip combination for the maximum flexibility to select the best HDR method for a given scene.

"The combination of high resolution, large pixel size and high dynamic range is essential to providing the image quality required by flagship mobile phone designers for features such as night mode," said Arun Jayaseelan, staff marketing manager at OmniVision. "The OV48C is the only flagship mobile image sensor in the industry to offer the combination of high 48MP resolution, a large 1.2 micron pixel, high speed, and on-chip high dynamic range, which provides superior SNR, unparalleled low light performance and high quality 4K video."

Built on OmniVision's PureCel Plus stacked die technology, this 1/1.3" format sensor also integrates an on-chip, 4-cell color filter array and hardware remosaic, which provides 48MP Bayer output, or 8K video, in real time. In low light conditions, this sensor can use near-pixel binning to output a 12MP image for 4K2K video with four times the sensitivity, yielding a 2.4 micron-equivalent performance. The OV48C also uses 4C Half Shield phase detection for fast autofocus support.

Output formats include 48MP at 15 fps, 12MP with 4-cell binning at 60 fps, and 4K2K video at 60 fps with the extra pixels needed for EIS. This sensor also offers 1080p video with slow motion support at 240 fps, as well as 720p at 360 fps. OV48C samples are available now.

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Isorg publishes a video promoting its optical fingerprint sensor for smartphones:



Some more info from the company's page:

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PRNewswire: SmartSens releases two 3MP CMOS sensors SC3235 and SC3320 for webcams and security cameras. With the new SmartPixel-2 DSI technology, The SC3320 comes equipped with larger optical format at 1/2.5" and Full HD Pro pixel count. This also guarantees a DR of up to 100dB with 60fps supporting 2-exposure HDR and NIR (850nm-940nm) imaging. SC3235 has 1/2.7" 2304H x 1296V array and leverages SmartSens' mature SmartPixel architecture.

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BusinessWire: Ambarella, Lumentum, and ON Semiconductor announce a joint 3D sensing platform for access control systems and smart video security products such as video doorbells and door locks. The platform is based on Ambarella’s CV25 CVflow AI vision SoC, structured-light powered by Lumentum’s VCSEL technology, and ON Semiconductor’s AR0237IR image sensor.

“ON Semiconductor’s RGB-IR sensor technology enables single sensor solutions to provide both visible and IR images in security and vision IoT applications,” said Gianluca Colli, VP and GM of the Commercial Sensing Division at ON Semiconductor. “Ambarella’s CV25 computer vision SoC, with its next-generation image signal processor (ISP), brings out the best image quality of our RGB-IR sensor, while providing powerful AI processing capability for innovative use cases in security applications.” Ambarella’s CV25 chip includes native support for RGB-IR CFA and HDR processing.

BusinessWire: Ambarella also announces CV22FS and CV2FS automotive camera ADAS SoCs with native support for RGGB, RCCB, RCCC, RGB-IR, and monochrome sensor formats:

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Panasonic publishes an arxiv.org paper "Smart Home Appliances: Chat with Your Fridge" by Denis Gudovskiy, Gyuri Han, Takuya Yamaguchi, and Sotaro Tsukizawa proposing an AI-equipped camera in a fridge:

"Current home appliances are capable to execute a limited number of voice commands such as turning devices on or off, adjusting music volume or light conditions. Recent progress in machine reasoning gives an opportunity to develop new types of conversational user interfaces for home appliances. In this paper, we apply state-of-the-art visual reasoning model and demonstrate that it is feasible to ask a smart fridge about its contents and various properties of the food with close-to-natural conversation experience. Our visual reasoning model answers user questions about existence, count, category and freshness of each product by analyzing photos made by the image sensor inside the smart fridge. Users may chat with their fridge using off-the-shelf phone messenger while being away from home, for example, when shopping in the supermarket. We generate a visually realistic synthetic dataset to train machine learning reasoning model that achieves 95% answer accuracy on test data. We present the results of initial user tests and discuss how we modify distribution of generated questions for model training based on human-in-the-loop guidance. We open source code for the whole system including dataset generation, reasoning model and demonstration scripts."

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Sony IEDM paper "High-definition Visible-SWIR InGaAs Image Sensor using Cu-Cu Bonding of III-V to Silicon Wafer" by S. Manda, R. Matsumoto, S. Saito, S. Maruyama, H. Minari, T. Hirano, T. Takachi, N. Fujii, Y. Yamamoto, Y. Zaizen, T. Hirano, and H. Iwamoto describes a process of bonding small InGaAs dies onto a Si wafer:

"We developed a back-illuminated InGaAs image sensor with 1280x1040 pixels at 5-um pitch by using Cu-Cu hybridization connecting different materials, a III-V InGaAs/InP of photodiode array (PDA), and a silicon readout integrated circuit (ROIC). A new process architecture using an InGaAs/InP dies-to-silicon wafer and Cu-Cu bonding was established for high productivity and pixel-pitch scaling. We achieved low dark current and high sensitivity for wavelengths ranging from visible to short-wavelength infrared (SWIR)."

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MDPI paper "Electrical Characterization of the Backside Interface on BSI Global Shutter Pixels with Tungsten-Shield Test Structures on CDTI Process" by Célestin Doyen, Stéphane Ricq, Pierre Magnan, Olivier Marcelot, Marios Barlas, and Sébastien Place from ST Micro and Université de Toulouse is a part of the Special issue on the 2019 International Image Sensor Workshop (IISW2019).

"A new methodology is presented using well known electrical characterization techniques on dedicated single devices in order to investigate backside interface contribution to the measured pixel dark current in BSI CMOS image sensors technologies. Extractions of interface states and charges within the dielectric densities are achieved. The results show that, in our case, the density of state is not directly the source of dark current excursions. The quality of the passivation of the backside interface appears to be the key factor. Thanks to the presented new test structures, it has been demonstrated that the backside interface contribution to dark current can be investigated separately from other sources of dark current, such as the frontside interface, DTI (deep trench isolation), etc."


"With these MOS capacitor and W-shield gate transistor test structures, it is possible to electrically characterize the backside interface of BSI technology at the end of a process using a tungsten shield. By means of two known characterization methods, Dit and NEFF, which are the two important parameters for dark current, can be extracted. It is, therefore, possible to investigate if the dark current mainly comes from the backside interface, and to discriminate the origin of the backside dark current.

In the case presented in this study, the difference in Idark behavior is explained by quality passivation differences of the backside interface between wafers. COCOS measurements are useful to characterize the interface just after a material deposit, however, it cannot be used with a fully processed wafer, unlike the methodology used on the new structures presented in this study. A drawback of this method is the presence of a charging effect that forces some caution on the execution of measurements, but this effect can be recovered and is not present in pixel operating conditions. In addition to these Idark contribution studies, these dedicated devices with associated characterizations can be helpful for process monitoring, TCAD calibration, and reliability works."

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PRNewswire: OmniVision announces the OS12D40, a 1.4um pixel, 11.3MP image sensor with on-chip remosaic (4-cell to Bayer) color converter and on-chip HDR processing. When in full-HD 1080p mode, this sensor's 3-exposure HDR with on-chip combination and tone mapping provides best in class video captures. This is superior to the competing method, known as staggered HDR, which relies on additional passes that introduce motion artifacts, especially in low light. Additionally, OmniVision's PureCel Plus-S stacked architecture enables each pixel to perform optimally to further improve HDR in scenes with widely contrasting bright and dark areas.

"With this new image sensor, we're setting the standard for best in class, mass market security camera performance," said David Shin, product marketing manager for the security segment at OmniVision. "This means both commercial and home security systems will now be able to better capture moving objects across all lighting conditions in full-HD 1080p mode, while using artificial intelligence (AI) or human operators to selectively take 4K2K images without HDR. The latter is important when the need for greater detail is identified, such as capturing an intruder's facial features or reading a car's license plate number. Additionally, we achieve 2.8 micron-equivalent pixel performance using 4-cell binning, to provide excellent low light image quality in 1080p mode."

Industry analysts predict that the security and surveillance camera market is growing at a more than 15% CAGR, and will exceed 400M units in 2024.

Other features include a large 1/2.49" optical format, 9 degree CRA, a 10b ADC and a 4-lane MIPI transceiver (2.5 Gbps/lane).

Integrated selective conversion gain technology allows the pixel conversion gain to be dynamically switched between low and high, depending on the scene being captured in combination with the sensor's other features, including PureCel Plus-S stacked pixel technology for reduced crosstalk and maximum QE.

The OS12D40 uses a 4-cell color filter pattern. It has an on-chip 4-cell to Bayer remosaic converter, in order to provide 4K video at 60fps with 20% additional pixels for EIS. In a 4-cell binned mode, it can output an impressive 2.8MP/1080p resolution with 20% additional pixels for EIS video and images at four times the sensitivity. This sensor also supports both CPHY and DPHY interfaces, and can output 11.3MP, 4512x2512 16:9 captures at 60fps, 4K video at 60fps and 1080p video at 240fps.

OS12D40 samples are available now in a fan-out and chip-scale wafer level package.


PRNewswire: OmniVision announces the expansion of its BSI GS sensor family with new VGA imagers that feature the industry's smallest pixel size of 2.2um—the OG0VA image sensor and OC0VA CameraCubeChip™ wafer-level camera module. Additionally, the OC0VA is the first CameraCubeChip with Nyxel technology. They have a high QE of 40% at 940nm and 60% at 850nm.

The OG0VA image sensor provides 640x480 VGA resolution at 240fps and 320x240 QVGA resolution at 480 fps, in the optical format of 1/10 inches. The OC0VA CameraCubeChip combines this sensor with image signal processing and optics into a 2.69 x 3.04 x 3.04mm wafer-level camera module. Additionally, their low light sensitivity is excellent, with significantly lower gain than the industry's typical 3.0um pixel size for an improved SNR.

"There is a growing need for global shutter technology at a variety of resolution levels to accurately capture the images of moving objects, along with excellent NIR performance and small size," said Devang Patel, senior staff marketing manager for the security and emerging segments at OmniVision. "The OG0VA and OC0VA expand our family of the industry's smallest GS imagers by providing VGA resolution options with the best NIR performance in a global shutter device."


Omnivision also continues the series of videos on its 8MP automotive sensor features:

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VentureBeat, EETimes, JerusalemPost: TriEye is partnering with Porsche to us SWIR sensing technology, with the hopes of advancing the performance of ADAS and autonomous vehicles.

“Our collaboration with Porsche has been exceptional from day one, and we look forward to growing this potential,” said TriEye CEO and co-founder Avi Bakal. “The fact that Porsche, a leading car manufacturer, has decided to invest in TriEye and evaluate TriEye’s CMOS-based SWIR camera to help further improve Advanced Driver Assistance Systems is a significant vote of confidence in our technology.”

Porsche executive board and development member Michael Steiner says, “We see great potential in this sensor technology that paves the way for the next generation of driver assistance systems and autonomous driving functions. SWIR can be a key element: It offers enhanced safety at a competitive price.”

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BusinessWire, Thomas-PR: RoboSense solid-state LiDAR RS-LiDAR-M1Simple (Simple Sensor Version) is now ready for customer delivery, priced at $1,898. The new RS-LiDAR-M1Simple is less than half the size of the previous version, with dimensions of 4.3” x 1.9” x 4.7” (110mm x 50mm x 120mm), and its hardware performance is "virtually equal to the serial production version provided to OEMs." The main body design of this automotive-grade solid-state LiDAR is finalized and ready for shipment.

In addition, RoboSense will demonstrate the world’s first smart solid-state LiDAR, the RS-LiDAR-M1Smart (Smart Sensor Version) with an on-vehicle public road test. The RS-LiDAR-M1 family is said to have the performance advantages of traditional mechanical LiDAR, simultaneously also taking into consideration requirements for the mass production of vehicles. The RS-LiDAR-M1 family meets every automotive-grade requirement, including intelligence, low cost, stability, simplified structure and small size, vehicle body design friendliness, and algorithm processed semantic-level perception output results.

“The RS-LiDAR-M1 is an optimal choice for the serial production of self-driving cars, far superior to mechanical LiDAR. The sooner solid-state LiDAR is used, the sooner production will be accelerated to mass-market levels,” said Mark Qiu, RoboSense COO.

RS-LiDAR-M1 Family Features:

• 125 laser beams: the RS-LiDAR-M1 has a field of view of 120°*25°, which is the MEMS solid-state LiDAR’s largest field of view among released products worldwide. RoboSense uses 905nm lasers with low cost, automotive grade and small size instead of expensive 1550nm lasers. RoboSense breaks ranging ability limits to 150m at 10% NIST target, which is also MEMS solid-state LiDAR’s longest detection range. The frame rate of RS-LiDAR-M1 is increased to 15Hz, which can reduce the impact of point cloud distortion caused by target movement.
• World’s smallest MEMS solid-state LiDAR: the size has been reduced by half, one-tenth the size of conventional 64-beam mechanical LiDAR.
• Reduced parts for lower cost, shorter production time, and large-scale production capacity. Parts have reduced from hundreds to dozens in comparison to traditional mechanical LiDARs, greatly reducing the cost and shortening production time -- achieving a breakthrough in manufacturability. The coin-sized module processes the optical-mechanical system results to meet autonomous driving performance and mass production requirements.
• Modular design: the scalability and layout flexibility of the optical module lay the foundation for subsequent MEMS LiDAR products and support the customization of products for different application cases.
• Stable and reliable: the RS-LiDAR-M1 uses VDA6.3 as the basis for project management, and the development of all modules undergoes a complete V model closed loop. RoboSense fully implemented IATF16949 quality management system and ISO26262 functional safety standards, combining ISO16750 test requirement and other automotive-grade reliability specifications to verify the RS-LiDAR-M1 series of products. MEMS mirror is the core component in RS-LiDAR-M1. According to the AEC-Q100 standard, combining the characteristics of MEMS micro-mirror, a total of ten verification test groups are designed covering temperature, humidity, packaging process, electromagnetic compatibility, mechanical vibration and shock, life-time, and others. The cumulative test time for all test samples has now exceeded 100,000 hours. The RS-LiDAR-M1 uses 905nm lasers to achieve long-distance and also meets Class 1 laser safety. The longest-running prototype has been tested for more than 300 days, while the total road test mileage exceeds 150,000 kilometers with no degradation found in various testing scenarios.
• All-weather: In Vienna, Austria, the RS-LiDAR-M1 was tested for rain and fog under different light and wind speed conditions. The test results prove that the RS-LiDAR-M1 has met the standards, and the final mass-produced RS-LiDAR-M1 will adapt to all climatic and working conditions.
• Minimal wear and tear: as a solid-state LiDAR, the RS-LiDAR-M1 has minimal wear and tear vs. movable mechanical structures, eliminating potential optoelectronic device failures due to mechanical rotation. The characteristics of solid-state provide a reasonable internal layout, heat dissipation, and stability -- a leap in quality as compared to mechanical LiDAR.

The hardware-only version of RS-LiDAR-M1 is currently available for customers, with a retail price of $1898. RoboSense will deliver current orders from key customers and upgrade the production line in Q1 2020, completing retail product delivery by Q1 2020.




Reuters: Bosch announces that it has developed LiDAR too: "The new Bosch sensor will cover both long and close ranges – on highways and in the city. By exploiting economies of scale, Bosch wants to reduce the price for the sophisticated technology and render it suitable for the mass market."

BusinessWire: Velodyne is to present its Five Diamonds rating system to clarify and standardize terminology for ADAS features. The system aims to encourage transparency in the marketplace and promote the maximum positive effect of ADAS technologies.

FinancialTimes: Sony joins the race to develop automotive LiDAR.

“Smartphones probably made the biggest impact in the 21st century in terms of changing people’s lives. Mobility is next,” says Kenichiro Yoshida, Sony CEO. The company's new solid-state LiDAR is said to be Si-based, long-range, lower-cost, compact, and insensitive to vibrations, according to FT sources.

In spite of success on image sensor market, Sony penetration to automotive applications has been quite limited. According to TSR, in 2018, Sony was on 5th place in automotive image sensors with a 3% market share, compared with 62% of ON Semi and 20% of OmniVision.

“I kept on asking why we couldn’t reverse our market position despite our sensors obviously being better than others,” says Terushi Shimizu, EVP of Sony Semiconductor group. “But we didn’t want to be drawn into the cost-cutting competition. We want our sensors to be used because our technology is better.”

Update: Zacks Research too publishes an article on Sony automotive LiDAR plans.

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PRNewswire: OmniVision announces the OA805, a video processor that supports HEVC compression with the lowest power consumption in the industry.

The OA805 has a boot-up time that is significantly faster than its nearest competitor. This rapid startup eliminates any delay between motion detection and video recording, potentially allowing the camera to instantly alert users of suspicious activities. Within 0.1 seconds, the OA805 can go from completely powered off to fully functional.

"High-end surveillance cameras need video processors that can cope with high-definition 4K resolution video streams. However, high resolution video translates into high power consumption, and manufacturers have had to either settle for lower resolution video to conserve power in their battery-powered systems, or to rely on hard-wired solutions," said David Ho, product marketing manager at OmniVision. "With the OA805, this power versus resolution trade-off is eliminated. Its support for both HEVC and H.264 video compression, in combination with the industry's lowest power consumption and fastest boot-up time, allows designers to incorporate leading-edge performance into products that their customers can quickly and easily install anywhere, so they never miss a thing."

Its HDR processing capability allows the OA805 to accept input from RBG/IR image sensors, for videos taken during the day or at night, in conditions with widely contrasting bright and dark images.

As an upgrade from OmniVision's OV798, the OA805 adds HEVC capability, consumes less power, boots up faster and offers higher resolution processing. This video processor accepts up to 16-megapixel captures from an image sensor and outputs up to 4K resolution video at 30 fps using HEVC encoding and decoding. It also supports multiple video streams at lower resolution, including H.264 1080p resolution at 60fps, as well as HDR and RGB-IR.

The OA805 video processor is available now.


In an unrelated news, Omnivision Product Manager Celine Baron features in a number of videos about the company's 8MP automotive sensor:

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EPFL and Canon publish Arxiv.org paper "A megapixel time-gated SPAD image sensor for 2D and 3D imaging applications" by Kazuhiro Morimoto, Andrei Ardelean, Ming-Lo Wu, Arin Can Ulku, Ivan Michel Antolovic, Claudio Bruschini, and Edoardo Charbon.

"We present the first 1Mpixel SPAD camera ever reported. The camera features 3.8ns time gating and 24kfps frame rate; it was fabricated in 180nm CIS technology. Two pixels have been designed with a pitch of 9.4μm in 7T and 5.75T configurations, respectively, achieving a maximum fill factor of 13.4%. The maximum PDP is 27%, median DCR 2.0cps, variation in gating length 120ps, position skew 410ps, and rise/fall time less than 550ps, all FWHM at 3.3V of excess bias. The sensor was used to capture 2D/3D scenes over 2m with an LSB of 5.4mm and a precision better than 7.8mm. Extended dynamic range is demonstrated in dual exposure operation mode. Spatially overlapped multi-object detection is experimentally demonstrated in single-photon time-gated ToF for the first time."

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Japanese automotive lighting solutions manufacturer Koito presents its headlight products with embedded image sensors:

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Fraunhofer and University Ilmenau SPIE paper "Single-frame three-dimensional imaging using spectral-coded patterns and multispectral snapshot cameras" by Chen Zhang, Anika Brahm, Andreas Breitbarth, Maik Rosenberger, and Gunther Notni extends structured light 3D concept to multispectral imaging:

"We present an approach for single-frame three-dimensional (3-D) imaging using multiwavelength array projection and a stereo vision setup of two multispectral snapshot cameras. Thus a sequence of aperiodic fringe patterns at different wavelengths can be projected and detected simultaneously. For the 3-D reconstruction, a computational procedure for pattern extraction from multispectral images, denoising of multispectral image data, and stereo matching is developed. In addition, a proof-of-concept is provided with experimental measurement results, showing the validity and potential of the proposed approach."

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Fraunhofer and University Ilmenau SPIE paper "Single-frame three-dimensional imaging using spectral-coded patterns and multispectral snapshot cameras" by Chen Zhang, Anika Brahm, Andreas Breitbarth, Maik Rosenberger, and Gunther Notni extends structured light 3D concept to multispectral imaging:

"We present an approach for single-frame three-dimensional (3-D) imaging using multiwavelength array projection and a stereo vision setup of two multispectral snapshot cameras. Thus a sequence of aperiodic fringe patterns at different wavelengths can be projected and detected simultaneously. For the 3-D reconstruction, a computational procedure for pattern extraction from multispectral images, denoising of multispectral image data, and stereo matching is developed. In addition, a proof-of-concept is provided with experimental measurement results, showing the validity and potential of the proposed approach."

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Japanese Applied Physics Express Journal publishes a paper "High-exposure-durability, high-quantum-efficiency (>90%) backside-illuminated soft-X-ray CMOS sensor" by Tetsuo Harada, Nobukazu Teranishi, Takeo Watanabe, Quan Zhou, Jan Bogaerts, and Xinyang Wang from University of Hyogo, Shizuoka University, and Gpixel.

"We develop a high-quantum-efficiency, high-exposure-durability backside-illuminated CMOS image sensor for soft-X-ray detection. The backside fabrication process is optimized to reduce the dead-layer thickness, and the Si-layer thickness is increased to 9.5 μm to reduce radiation damage. Our sensor demonstrates a high quantum efficiency of greater than 90% in the photon-energy range of 80–1000 eV. Further, its EUV-regime efficiency is ~100% because the dead-layer thickness is only 5 nm. The readout noise is as low as 2.5 e− rms and the frame rate as high as 48 fps, which makes the device practical for general soft X-ray experiments.

...we developed a new CMOS sensor with further improvements to the backside process to afford a thicker Si layer of 9.5 μm; we called this sensor the SP3 sensor. This soft-X-ray/EUV-regime SP3 image sensor is also based on the Gpixel BSI CMOS image sensor, GSENSE400SQBSI. ...We made two changes to the backside fabrication process for the SP3 relative to the SBSA: the silicon thickness was changed from 3.5 to 9.5 μm to suppress radiation damage, and that the implantation energy was decreased by one digit to reduce the non-sensitive-layer thickness. Our CMOS sensor adopts a rolling shutter and a high dynamic range (HDR) scheme using the double-conversion gain method, and has 2048 (H) × 2048 (V) 11 μm pixels. "


Thanks to NT for the link!

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Sony IEDM 2019 paper "Three-layer Stacked Color Image Sensor With 2.0-μm Pixel Size Using Organic Photoconductive Film" by H. Togashi, T. Watanabe, M. Joei, T. Hayashi, S. Hirata, S. Fukuoka, Y. Ando, Y. Sato, J. Yamamoto, I. Yagi, M. Murata, M. Kuribayashi, F. Koga, T. Yamaguchi, Y. Oike, T. Ezaki, and T. Hirayama combines 3T organic PD pixel with 4T Si-based pixel ideas:

"A three-layer stacked color image sensor was formed using an organic film. The sensor decreases the false color problem as it does not require demosaicing. Furthermore, with the 2.0-μm pixel image sensor, improved spectral characteristics owing to green adsorption by the organic film above the red/blue photodiode, were successfully demonstrated."

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Digitimes: Two major Taiwan-based CMOS sensor packaging companies Tong Hsing and Kingpark have agreed to merge to turn them into one of the world's largest CIS packaging houses.

Taipei Times: Tong Hsing plans to acquire all of the shares in Kingpak after its board of directors approved a share-swap deal. The companies hope to complete the deal by June 30, 2020 and expect to pursue emerging opportunities in the smartphone, ADAS, IoT, the Internet of Vehicles, VR, and AR markets, the filing said.

“The two companies have little overlap in customers and products, but they are highly complementary,” Tong Hsing president Heinz Ru said at a press conference at the Taiwan Stock Exchange. Kingpak is to become a wholly owned unit of Tong Hsing and be delisted from the Taipei Exchange when the merger is completed.

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Sony paper at IEDM 2019 presents "A 1/2inch 48M All PDAF CMOS Image Sensor Using 0.8µm Quad Bayer Coding 2×2OCL with 1.0lux Minimum AF Illuminance Level" by T. Okawa, S. Ooki, H. Yamajo, M. Kawada, M. Tachi, K. Goi, T. Yamasaki, H. Iwashita, M. Nakamizo, T. Ogasahara, Y. Kitano, and K. Tatani.

"Currently, there are two coding trends in mobile image sensors: Quad Bayer coding (QBC) and dual photodiode (DPD). QBC realizes high resolution and high dynamic range (HDR), whereas DPD achieves high phase detection auto focus (PDAF) performance. We propose a QBC with 2×2 on-chip lens (2×2OCL) architecture as a potential next-generation high-performance CMOS image sensor. This combines high resolution, HDR, and high PDAF performance in one sensor. The critical issues of 2×2OCL are degradation of the resolution due to the sensitivity difference between 4 pixels under the same color filter and increasing the crosstalk among different colors. To overcome these issues, the OCL and pixel isolation shapes were optimized respectively. The world`s first image sensor using 2×2OCL architecture we prepared in this paper, has 1/2 inch 48M pixels with 0.8µm QBC for high resolution, and all pixel PDAF achieved a minimum AF illuminance level of 1 lux."

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OSA Optics Express publishes an open access paper "Joint electromagnetic and ray-tracing simulations for quad-pixel sensor and computational imaging" by Guillaume Chataignier, Benoit Vandame, and Jérôme Vaillant from InterDigital and University Grenoble Alpes, France.

"Since Canon released the first dual-pixel autofocus in 2013, this technique has been used in many cameras and smartphones. Quad-pixel sensors, where a microlens covers 2x2 sub-pixels, will be the next development. In this paper we describe the design for such sensors; related wave optics simulations; and results, especially in terms of angular response. Then we propose a new method for mixing wave optics simulations with ray tracing simulations in order to generate physically accurate synthetic images. Those images are useful in a co-design approach by linking the pixel architecture, the main lens design and the computer vision algorithms."

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Instructables publish a Sean Hodgins' project on DIY 32 x 32 image sensor and a camera based on it:

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