Archives for December 2021

Image Sensors at ISSCC 2022

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 ISSCC publishes its 2022 Agenda. There are 13 image sensor-related papers:

  1. Charge-Domain Signal Compression in Ultra-High-Speed CMOS Image Sensors
    Keiichiro Kagawa,
    Shizuoka University, Hamamatsu, Japan
  2. A 0.37W 143dB-Dynamic-Range 1Mpixel Backside-Illuminated Charge-Focusing SPAD Image Sensor with Pixel-Wise Exposure Control and Adaptive Clocked Recharging
    Y. Ota, K. Morimoto, T. Sasago, M. Shinohara, Y. Kuroda, W. Endo, Y. Maehashi, S. Maekawa, H. Tsuchiya, A. Abdelghafar, S. Hikosaka, M. Motoyama, K. Tojima, K. Uehira, J. Iwata, F. Inui, Y. Matsuno, K. Sakurai, T. Ichikawa,
    Canon, Kanagawa, Japan
  3. A 64×64-Pixel Flash LiDAR SPAD Imager with Distributed Pixel-to-Pixel Correlation for Background Rejection, Tunable Automatic Pixel Sensitivity and First-Last Event Detection Strategies for Space Applications
    E. Manuzzato, A. Tontini, A. Seljak, M. Perenzoni
    Fondazione Bruno Kessler, Trento, Italy; Jozef Stefan Institute, Ljubljana, Slovenia
  4. An 80×60 Flash LiDAR Sensor with In-Pixel Histogramming TDC Based on Quaternary Search and Time-Gated Δ-Intensity Phase Detection for 45m Detectable Range and Background Light Cancellation
    S. Park, B. Kim, J. Cho, J-H. Chun, J. Choi, S-J. Kim
    Ulsan National Institute of Science and Technology, Ulsan, Korea; SolidVue, Suwon, Korea, Sungkyunkwan University, Suwon, Korea
  5. A 38μm Range Precision Time-of-Flight CMOS Range Line Imager with Gating Driver Jitter Reduction Using Charge-Injection Pseudo Photocurrent Reference
    K. Yasutomi, T. Furuhashi, K. Sagawa, T. Takasawa, K. Kagawa, S. Kawahito
    Shizuoka University, Hamamatsu, Japan
  6. A 1/1.57-inch 50Mpixel CMOS Image Sensor with 1.0μm All-Directional Dual Pixel by 0.5μm-Pitch Full-Depth Deep-Trench Isolation Technology
    T. Jung, M. Fujita, J. Cho, K. Lee, D. Seol, S. An, C. Lee, Y. Jeong, M. Jung, S. Park, S. Baek, S. Jung, S. Lee, J. Yun, E. S. Shim, H. Han, E. Park, H. Sul, S. Kang, K. Lee, J. Ahn, D. Chang
    Samsung Electronics, Hwasung, Korea
  7. A 4.9Mpixel Programmable-Resolution Multi-Purpose CMOS Image Sensor for Computer Vision
    H. Murakami, E. Bohannon, J. Childs, G. Gui, E. Moule, K. Hanzawa, T. Koda, C. Takano, T. Shimizu, Y. Takizawa, A. Basavalingappa, R. Childs, C. Cziesler, R. Jarnot, K. Nishimura, S. Rogerson, Y. Nitta,
    Sony
  8. A Fully Digital Time-Mode CMOS Image Sensor with 22.9pJ/frame∙pixel and 92dB Dynamic Range
    S. Kim, T. Kim, K. Seo, G. Han,
    Yonsei University, Seoul, Korea
  9. A 64Mpixel CMOS Image Sensor with 0.56μm Unit Pixels Separated by Front Deep-Trench Isolation
    S. Park, C. Lee, S. Park, H. Park, T. Lee, D. Park, M. Heo, I. Park, H. Yeo, Y. Lee, J. Lee, B. Lee, D-C. Lee, J. Kim, B. Kim, J. Pyo, S. Quan, S. You, I. Ro, S. Choi, S-I. Kim, I-S. Joe, J. Park, C-H. Koo, J-H. Kim, C. K. Chang, T. Kim, J. Kim, J. Lee, H. Kim, C-R. Moon, H-S. Kim,
    Samsung Electronics, Hwaseong, Korea
  10. A 200 x 256 Image Sensor Heterogeneously Integrating a 2D Nanomaterial-Based Photo-FET Array and CMOS Time-to-Digital Converters
    H. Hinton, H. Jang, W. Wu, M-H. Lee, M. Seol, H-J. Shin, S. Park, D. Ham
    Harvard University, Cambridge, MA; Samsung Advanced Institute of Technology, Suwon, Korea
  11. A 0.8V Intelligent Vision Sensor with Tiny Convolutional Neural Network and Programmable Weights Using Mixed-Mode Processing-in-Sensor Technique for Image Classification
    T-H. Hsu, G-C. Chen, Y-R. Chen, C-C. Lo, R-S. Liu, M-F. Chang, K-T. Tang, C-C. Hsieh
    National Tsing Hua University, Hsinchu, Taiwan
  12. Augmented Reality – The Next Frontier of Image Sensors and Compute Systems
    C. Liu, S. Chen, T-H. Tsai, B. De Salvo, J. Gomez
    Meta Reality Labs, Redmond, WA
  13. Concepts, Architectures and Circuits for Sub-THz Sensing and Imaging
    A. Stelzer,
    Linz University, Linz, Austria

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EDoF-ToF Paper

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Rice University publishes an OSA Optica paper "EDoF-ToF: extended depth of field time-of-flight imaging" by Jasper Tan, Vivek Boominathan, Richard Baraniuk, and Ashok Veeraraghavan.

"Conventional continuous-wave amplitude-modulated time-of-flight (CWAM ToF) cameras suffer from a fundamental trade-off between light throughput and depth of field (DoF): a larger lens aperture allows more light collection but suffers from significantly lower DoF. However, both high light throughput, which increases signal-to-noise ratio, and a wide DoF, which enlarges the system’s applicable depth range, are valuable for CWAM ToF applications. In this work, we propose EDoF-ToF, an algorithmic method to extend the DoF of large-aperture CWAM ToF cameras by using a neural network to deblur objects outside of the lens’s narrow focal region and thus produce an all-in-focus measurement. A key component of our work is the proposed large-aperture ToF training data simulator, which models the depth-dependent blurs and partial occlusions caused by such apertures. Contrary to conventional image deblurring where the blur model is typically linear, ToF depth maps are nonlinear functions of scene intensities, resulting in a nonlinear blur model that we also derive for our simulator. Unlike extended DoF for conventional photography where depth information needs to be encoded (or made depth-invariant) using additional hardware (phase masks, focal sweeping, etc.), ToF sensor measurements naturally encode depth information, allowing a completely software solution to extended DoF. We experimentally demonstrate EDoF-ToF increasing the DoF of a conventional ToF system by 3.6 ×, effectively achieving the DoF of a smaller lens aperture that allows 22.1 × less light. Ultimately, EDoF-ToF enables CWAM ToF cameras to enjoy the benefits of both high light throughput and a wide DoF."

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Sony – Qualcomm Joint Lab to Work on Image Sensor and Processing Optimizations

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During the recent Qualcomm's mobile processor announcements, there was a part on establishing a joint lab with Sony in San Diego working on image sensor and processor co-optimization:

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BAE Presents 12MP 240fps APS-C Sensor

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BAE (Fairchild Imaging) presents 12MP 240fps APS-C sensor LTN4625A with global and rolling shutter modes:

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Advantest Speeds Up its CIS Production Tester

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GlobeNewswire: Advantest has begun shipping the fourth generation of its high-speed image-processing engine that applies heterogeneous computing technology to detect defects in the data output from CMOS image sensors. When integrated on the proven T2000 ISS platform, the new T2000 IP Engine 4 (Image Processing Engine 4) system provides the means of evaluating the latest high-resolution, high-speed CIS devices used in advanced smart phone cameras.

The new T2000 IP Engine 4 features enhanced computing power to handle huge volumes of imaging data while also reducing test times and the cost of test. Used along with Advantest’s 4.8GICAP image capture module, the new tester can perform high-volume, at-speed testing of the most advanced mobile CIS including 3.5-Gsps C-PHY and 4.8-Gbps D-PHY devices. Image-processing accelerators enable fast testing of high-resolution CIS with more than 200MP.

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Qualcomm Snapdragon 8 Gen 1 Camera Features

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Qualcomm announces its next generation mobile processor Snapdragon 8 Gen 1:

"Snapdragon Sight Technology includes the first commercial 18-bit mobile ISP, capturing over 4000x more camera data than its predecessor for extreme dynamic range, color, and sharpness at staggering speeds up to 3.2 gigapixels per second. This is also the first 8K HDR video capture in a mobile platform and it’s capable of capturing in the premium HDR10+ format that’s loaded with over a billion shades of color. Video will look even more stunning thanks to the new Bokeh Engine which adds beautiful soft backgrounds to videos; it’s like Portrait Mode for video capture. Snapdragon 8 also includes a fourth separate ISP, the new Always-On ISP, which allows the camera to run with extremely low power consumption so users can experience always-on face unlocking and locking if your face isn’t present for heightened privacy."


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Canon announces conclusion of toner cartridge patent lawsuit in China

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