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IEEE Sensors Council publishes "A 128×1 Pixels, High Dynamic Range SPAD Imager in 0.18 µm CMOS Technology" presentation by Cheng Mao, Xiangshun Kong, Haowen Ma, Limin Zhang, Feng Yan, and Xiaofeng Bu from Nanjing University, China.

"SPAD imager is proposed to achieve high dynamic range image. A SPAD chip with 128×1 pixels in 0.18 µm CMOS process is presented to show the feasibility. The chip design and the image method are detailed illustrated. The experiment results show that the SPAD imager can achieve 89 dB high dynamic range image, which is about 20 dB higher than that using CCD and CMOS image sensors, showing the superiority of the proposed method."

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Thanks to Offline Dreams mentioned another machine learning CFA pattern optimization in the comment to my yesterday's post. "Deep Joint Design of Color Filter Arrays and Demosaicing" paper by Bernardo Henz, Eduardo S. L. Gastal, and Manuel M. Oliveira from Brazilian Instituto de Informática – UFRGS differs from the previous post in a number of ways:

• both noisy and noiseless cases are explored
• CFA pattern is optimized together with demosaicing algorithm
• different CFA colors were a part of optimization too

"We present a convolutional neural network architecture for performing joint design of color filter array (CFA) patterns and demosaicing. Our generic model allows the training of CFAs of arbitrary sizes, optimizing each color filter over the entire RGB color space. The patterns and algorithms produced by our method provide high-quality color reconstructions. We demonstrate the effectiveness of our approach by showing that its results achieve higher PSNR than the ones obtained with state-of-the-art techniques on all standard demosaicing datasets, both for noise-free and noisy scenarios. Our method can also be used to obtain demosaicing strategies for pre-defined CFAs, such as the Bayer pattern, for which our results also surpass even the demosaicing algorithms specifically designed for such a pattern."


The machine learning optimization picked quite different patterns from the Bayer CFA, both in color and in size:

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PRNewswire: Pixon Imaging announces its new Extended Dynamic Range Architecture (ExDRA) - an software technique that improves low-light-level imaging in cell phone and other CMOS/CCD -based cameras. The technique utilizes charge binning, combining a full megapixel image of bright objects with a higher-sensitivity binned image of faint objects, all performed in one frame time. ExDRA delivers a low light performance that is an order of magnitude (or better) than current methods.

For example, Google's new Pixel 3 "Night Sight", employs up to 15 images to improve low-light sensitivity. This mimics the sensitivity of a longer exposure, but requires stationary objects, and cannot approach the sensitivity of the algorithmically simpler ExDRA. Alternative performance improving methods employed by other cell phone manufacturers require the use of multiple cameras, adding hardware costs and software complexity.

"The ExDRA technique captures both the high-resolution and high-sensitivity images simultaneously from a single CMOS/CCD sensor," reports Rick Puetter, Pixon's Chief Scientist. "This makes it possible to produce images and videos of scenes in low light with exceptional clarity and uniformity."

ExDRA is comprised entirely of software and is suited for integration into mobile phone cameras. It can also be implemented as an App, with little lead time, for use with existing devices.

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BusinessWire: CEA-Leti demonstrates its curved sensor technology, called Pixcurve, that requires fewer lens elements in digital cameras, shrinks camera size by half, and lowers costs – while improving image quality.

Pixcurve advantages:

• Form Factor
  Reducing the number of lens elements in digital cameras from 10 to six reduces the size of the final compound lens by 60%. The overall length of the optical system also is shorter.
• Improved Performance
  Curved image sensors reduce—and in some cases completely eliminate—optical aberrations like curvature of field and the vignetting effect. They also deliver increased brightness and a wider field of view.
• Cost
  Reducing the number of lens elements and eliminating aspheric lens elements, which will be unnecessary, will lower the cost of systems integrating Pixcurve technology.
• Assembly
  Fewer components means quicker and easier assembly—a major advantage for manufacturers.

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German 3D laser scanner maker Sick reveals that it's using a custom designed image sensor in its cameras:


Thanks to TL for the pointer!

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Qualcomm announces its 5G-ready 7nm Snapdragon 855 platform featuring an enhanced imaging functionality:

"Snapdragon 855 sets new standards for capturing stunning photos and videos. The new Qualcomm Spectra™ 380 ISP integrates numerous hardware accelerated computer vision (CV) capabilities, enabling the world’s first announced CV-ISP to provide cutting-edge computational photography and video capture features while at the same time offering up to 4x power savings. The CV-ISP includes hardware-based depth sensing which enables video capture, object classification, and object segmentation all in real-time in 4K HDR at 60fps. This means a user can capture a video and accurately replace selected objects or backgrounds in the scene in real-time all with 4K HDR resolution using over 1 billion shades of color. Even further, the new Qualcomm Spectra 380 ISP is the first announced ISP to support video recording using HDR10+, so the more than 1 billion shades of color can be captured with exceptional contrast and visual brilliance. Finally, in order to efficiently store this amazing content, Snapdragon 855 adds hardware acceleration for HEIF file format encoding, reducing file sizes by 50% for efficiently saving and sending user generated content."

Qualcomm Spectra 380 Image Signal Processor:

• Dual 14-bit CV-ISPs; 22MP @30 fps concurrent dual cameras; 48MP @ 30 fps single camera
• Hardware CV functions including object detection & tracking (Histogram of Oriented Gradients, Harris Corner Detection, Normalized Cross Correlation, Linear classification and optical flow) and stereo depth processing
• Advanced HDR solution including improved zzHDR and 3-exposure Quad Color Filter Array (QCFA) HDR
• 4K60 HDR video capture (HDR10, HDR10+ and HLG) with Portrait Mode (bokeh), 10-bit color depth and Rec. 2020 color gamut
• Hardware-based Multi-Frame Noise Reduction (MFNR) for snapshot and Motion Compensated Temporal noise Filtering (MCTF) for video
• Hardware-based Electronic Image Stabilization (EIS) solution within camera subsystem
• A new modular ISP design with more flexibility to tap in and out of the imaging pipeline both in the RAW and YUV pixel domains
• High frame rate capture for slow motion video (720p @ 480fps)
• HEIF photo capture, HEVC (H.265) video capture

Update: Qualcomm publishes its SD855 camera presentation. Few additional slides from it:

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Occipital HW Leader Evan Fletcher did an interesting work on searching for an optimal CFA pattern among arbitrary large sized patterns in an unconstrained machine learning search. The result might surprise the companies proposing better CFA mosaics, such as Fujifilm:

"After training for ~24 hours, the learned color filter array looks quite familiar:


The network seems to have learned something very similar to a RGGB Bayer pattern, complete with 2×2 repetition and the pentile arrangement of the green pixels! This was quite surprising, especially given that there is no spatial constraint on arrangement or repetition in this network design whatsoever.

This optimization appears to have independently confirmed the venerable Bayer pattern as a good choice for a mosaic function – it was fascinating to see a familiar pattern arise from an unconstrained optimization."

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PhoneArena quotes WSJ and Korean media claiming that next year Samsung Galaxy 5G S10 smartphone is expected to have a rear ToF camera. Later in the year, Samsung A-series smartphones will feature ToF cameras too. Samsung ToF module suppliers are said to be SEMCO and Patron.

Next year's Apple iPhone is to feature a rear ToF camera as well, said to be sourced from LG.

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Bloomberg reports that an oncoming Huawei smartphone possibly incorporate Sony ToF sensor:

"The phone, code-named Princeton internally, will be announced this month and go on sale within a few weeks, according to one of the people who requested anonymity discussing private plans. The technology uses sensors developed by Sony Corp. that can accurately measure distances by bouncing light off surfaces.

Besides generating pictures that can be viewed from numerous angles, Huawei’s new camera can create 3-D models of people and objects that can be used by augmented-reality apps, according to one of the people. The new camera will also let developers control apps and games in new ways, such as hand gestures, the person said, who added that some of the details may change as developers work with the technology."

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Gpixel announces a 51MP, 8424 x 6032 resolution, 35 mm full-frame global shutter image sensor. The GMAX4651 is capable of capturing full resolution images at frame rates of up to 80 fps in standard 12-bit read out mode and 40 fps in dual gain HDR mode.

With more than 83dB DR, 1/50,000 shutter efficiency and wide angular response, the GMAX4651 is aimed to advanced optical inspection and machine vision applications (Automated Optical Inspection (AOI) and Flat Panel Display (FPD) inspection) as well as high-end 8k/4k video broadcast and aerial imaging applications.

“The GMAX4651 is a really unique addition to our GMAX series, outperforming existing CCD solutions on all performance levels,” commented Wim Wuyts, Chief Commercial Officer of Gpixel. “It combines the dual gain HDR used in our successful GSENSE sensors, with excellent global shutter pixel technology and unprecedented frame rates. All together this will set a new industry standard for high-end industrial inspection and the video industry.”

Based on a 4.6 µm charge domain global shutter technology with true CDS, the GMAX4651 delivers more than 25 ke- linear FWC and up to 50 ke- when using 1x2 binning and ultra-low noise read out down to 1.5 e-RMS. Under dual gain HDR mode, where the sensor reads out the same exposure with two different gain settings for off-chip HDR reconstruction, DR can reach 83dB.

GMAX4651 mono sensor sample and evaluation kit will be commercially available in March 2019. Color samples will be made available in Q2 2019 and volume production is targeted for Q3 2019.

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Toronto, Canada-based startup Sheba Microsystems promises MEMS-based AF, zoom, and OIS:





Some demo videos are published in the company's Youtube channel.

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Arxiv.org paper "Event-Based Structured Light for Depth Reconstruction using Frequency Tagged Light Patterns" by T. Leroux, S.-H. Ieng, and R. Benosman from University of Pittsburgh, Carnegie Mellon University, and Sorbonne University proposes to use (apparently) Prophesee sensor for a structured light 3D camera. Although the paper appears a bit rushed to publication and needs some proofreading, the presented ideas look nice:

"This paper presents a new method for 3D depth estimation using the output of an asynchronous time driven image sensor. In association with a high speed Digital Light Processing projection system, our method achieves real-time reconstruction of 3D points cloud, up to several hundreds of hertz. Unlike state of the art methodology, we introduce a method that relies on the use of frequency tagged light pattern that make use of the high temporal resolution of event based sensors. This approach eases matching as each pattern unique frequency allow for any easy matching between displayed patterns and the event based sensor. Results are shown on the real scenes."

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SystemPlus publishes a teardown report of Orbbec face recognition solution in Oppo Find X smartphone:

"Located in the Find X’s front side, around the speaker, the 3D system is packaged in one metal enclosure. The system features a dot projector, a flood illuminator, a red/green/blue camera and a NIR camera sensor. An additional SoC component is soldered on the main board to process the signal from the latter devices.

The system uses standard components found on the market. That includes a GS image sensor featuring 3µm size pixels and standard resolution of 1 megapixel and a vertical cavity surface emitting laser (VCSEL). The system is therefore very cost efficient compared to other solutions. The camera and dot projector module assembly uses standard wire bonding to connect the sensor or the VCSEL dies, along with an optical module comprising four lenses for both modules."

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After few months of presentations at different conferences and exhibitions, STMicroelectronics has officially unveiled two new automotive global shutter image sensors, the VG5661 and VG5761, aimed to driver monitoring.

ST’s VG5661 and VG5761 are 1.6MP and 2.3MP automotive global shutter sensors. ST has created a unique automotive global shutter pixel with two memory cells while keeping a small pixel size of 3.2μm. The two memory zones allow double-image storage, enabling linear HDR up to 98dB or background removal without lag effects and with no need for additional processing by the host system. This offloads the host processor and reduces instances of correction artefacts. In addition, HDR and high MTF in NIR further minimizes interference from natural light sources.

The VG5661 and VG5761 are supplied in standard BGA packages, or as bare die for direct integration in automotive OEM systems produced in high volumes. They are qualified to AEC-Q100 grade 2 and include complex safety-integrity features as required for an ASIL-B camera system in accordance with the automotive safety standard ISO 26262.

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Lucid Vision Labs presentation has some data on Sony polarization sensors:

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Photoneo presentation at Vision Show in Stuttgart, Germany, on Nov. 6-8, 2018 shows its Parallel Structured Light 3D camera concepts:

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DIY Photography quotes EOSHD that Sony is working on IMX435 stacked full-frame sensor that is able to shoot 8K 60fps video with 12b ADC resolution:

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Lucid Vision Labs presents the results of its ToF camera based on Sony-Softkinetic IMX556 BSI sensor:

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SWIR Vision System presentation at Vision Show 2018 details on its lower than InGaAs cost sensor mentioned in my previous post:


Thanks to TL for the pointer!

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Woodside Capital Partners release November 2018 update of its "Autonomous Vehicles Technology Report." A few interesting slides with somewhat pessimistic view on the automotive LiDAR short term prospects:

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Yole Developpement analyst Alexis Debray publishes an interview with Filip Geuens, CEO of LiDAR maker XenomatiX. Some interesting quotes:

"We see 2 main categories in the market: global illumination LiDARs (also called flash LiDAR) and scanning-beam LiDAR. The scanning can come from an optical phase array or from a rotating mirror, oscillating mirror or other mechanical device.
Our XenoLidar does not fit in any of these 2 categories. XenoLidar uses multi-beam. Just like global illumination, we measure the scene in one shot and with high resolution, but in a much more efficient way as we only need a fraction of the energy a flash system needs. This actually translates into the fact that we can cover a much larger range for the same energy.

In the end it is a balancing exercise. We believe we have the best mix of what is critical for automotive in terms of cost, reliability, resolution, efficiency and size (in order of importance).

Today, an important bottleneck is the lack of decision taking. Many people get confused by the diversity of make-believe solutions and by initiatives that failed to deliver on their promises. That is slowing down adoption. Too many parties are sitting on the fence and waiting for a leader to pick a solution.

We deal with this by putting evidence on the table. Being able to back-up performance statements with functional products is our response. However, early adopters are still needed to help the technology to mature further, moving from technology level to application level."

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Fraunhofer presentation at the Vision Show held in Stuttgart, Germany, on Nov 6-8, 2018 offers a different approach to the data minimization in machine vision applications. To simplify the use, Fraunhofer embedded vision sensor even offers Python language-like scripting interface:


Prophesee too presented its Event-Driven Sensor at the Vision Show:


Thanks to TL for the pointers!

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ST presentation "Automotive In-cabin Sensing Solutions" by Nicolas Roux details the company's GS HDR sensor technology, including the dual ADCs and dual pixel memory:

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ST presentation "Automotive In-cabin Sensing Solutions" by Nicolas Roux details the company's GS HDR sensor technology, including the dual ADCs and dual pixel memory: