Archives for November 2015

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Sharp has presented its quarterly results about a month ago. It appears that the company's imager sales have peaked about half a year ago and slowly go down now:

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Photoneo reports that it is the winner of StartupAwards.sk for 2015 in Science category.

In a separate news, the company CEO Jan Zizka was selected to the group of 100 leaders of change in NEWEUROPE100 initiative. This list showcases people that will be the drivers of change in Central and Eastern Europe in the near future.

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Next week, CMOSIS will introduce the CSI2100 2MP CMOS sensor. Its features include a 1440 x 1440 pixel array with 12 µm B&W GS pixels and a 500 fps frame rate in 10-bit mode. The sensor boasts a a full well capacity of 2 Me-/pixel and is optimized to detect small signal variations in bright images captured at high-speed. This makes it suitable for medical, scientific and industrial applications. The CSI2100 evaluation kit was co-developed with Pleora Technologies.

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Europractice publishes its 2016 MPW prices and schedules. It looks like that other than TowerJazz, UMC becomes one of the biggest CIS MPW providers, including 110nm CIS process:

5 - block size 5mm x 5mm, 6 - block size 4mm x 4mm Discouted prices are available only to Europractice members and only for educational or publicly funded research use

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Yole Developpement "Infrared Detector Technology & Market Trends (2015 edition)" report estimates the total IR detector market at 247M units in 2014 and a global revenue of US$ 209M. Yole’s analysts highlight the rapid growth of +14% between 2015 and 2020 (in units). Five applications among the nine applications will drive the IR detector market revenue growth: spot thermometry in mobiles devices, motion detection, smart building, HVAC and other medium array applications and people counting. “The next growth opportunities will be outside traditional markets, in smart buildings and mobile devices,” comments Yann de Charentenay, Senior, Technology & Market Analyst at Yole.

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Martin Wäny, the founder and CEO of Awaiba, now CMOSIS, gives an interview on endoscopic imaging to News Medical site. Few interesting quotes:

"The miniaturization, and in particular the usage of semiconductor miniaturization technologies, allows us to build smaller, in volume and lower priced endoscopic cameras. This enables the proliferation of disposable endoscopes for a wide range of applications.

Is it possible to introduce 3D visualization using the mini optical modules?

Yes, for that purpose CMOSIS already offers endoscopic stereo camera modules. Multiple camera modules can provide 3D image information as needed for dental applications, or for the absolute measurement of features in laparoscopy or gastroenterology."

CMOSIS-Awaiba Naneye Camera

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German camera maker XIMEA publishes a Vimeo talk about its hyperspectral cameras based on IMEC sensors:

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As promised in comments to the earlier post on sub-electron pixel noise, here is the presentation on the noiseless frame summation in the regular charge-transfer pixel that can allow DR expansion while maintaining the usual 4T pixel noise level:


The above slides complete the description of the noiseless frame summation general idea. There are few practical issues that need to be addressed though:

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The Optical Society of America announces that Eric Fossum has been elected as OSA Fellow, among other 77 OSA members. "Fellows of The Optical Society are elected based on their significant contributions to the advancement of optics and photonics and are selected based on several factors, including specific scientific, engineering, and technological contributions, a record of significant publications or patents related to optics, technical or industry leadership in the field as well as service to OSA and the global optics community."

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Rambus Fellow David Stork was recently elected “Life Fellow” by the Optical Society of America (OSA). Stork is a member of Rambus imaging team and has many image sensor related papers and patents.

“I deeply enjoy the task of identifying technical problems or opportunities, solving hard theoretical problems and translating those results into practical devices and real-world services that make a difference in the world,” he told Rambus Press. “Specific examples include pondering interdisciplinary problems and the intersections of apparently disparate disciplines, e.g. optics and computing, hardware and software, computer vision and art, speech recognition and computer vision, etc.”

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Qualcomm promotes its low light image processing in this Youtube video:

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IEEE Electron Device Letters publishes an open-access paper "A 0.27e− rms Read Noise 220-μV/e− Conversion Gain Reset-Gate-Less CMOS Image Sensor With 0.11-μm CIS Process" by Min-Woong Seo, Shoji Kawahito, Keiichiro Kagawa, and Keita Yasutomi. "To achieve a high pixel conversion gain without fine or special processes, the proposed pixel has two unique structures: 1) coupling capacitance between the transfer gate and floating diffusion (FD) and 2) coupling capacitance between the reset gate and FD, for removing parasitic capacitances around the FD node:"

Proposed HCG pixel. (a) Cross-section of the proposed pixel for reducing the parasitic capacitance of floating diffusion. (b) Potential diagram as a function of the voltage level of VRTH.

Photoelectron-counting histrograms with a theoretical Poisson distribution of the developed CMOS imager (@ 100,000 points, 230 LSB/e− using internal ADC). (a) Signal level λ = 2.05. (b) Signal level λ = 4.0.

This is close to 0.22e- rms noise reported in an earlier paper.

Thanks to EF for the link!

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ISSCC 2016 Advance program has many innovative image sensor related papers, with Panasonic leading the way with its organic imagers:

6.1 An Over 120dB Simultaneous-Capture Wide-Dynamic-Range 1.6e- Ultra-Low-Reset-Noise Organic-Photoconductive-Film CMOS Image Sensor
K. Nishimura, Y. Sato, J. Hirase, R. Sakaida, M. Yanagida, T. Tamaki, M. Takase, H. Kanehara, M. Murakami, Y. Inoue,
Panasonic, Moriguchi, Japan

6.2 210ke- Saturation Signal 3µm-Pixel Variable-Sensitivity Global-Shutter Organic Photoconductive Image Sensor for Motion Capture
S. Shishido, Y. Miyake, Y. Sato, T. Tamaki, N. Shimasaki, Y. Sato, M. Murakami, Y. Inoue,
Panasonic, Moriguchi, Japan

6.3 105×65mm2 391Mpixel CMOS Image Sensor with >78dB Dynamic Range for Airborne Mapping Applications
J. Bogaerts, R. Lafaille, M. Borremans, J. Guo, B. Ceulemans, G. Meynants, N. Sarhangnejad, G. Arsinte, V. Statescu, S. van der Groen
CMOSIS NV, Antwerp, Belgium

6.4 An APS-H-Size 250Mpixel CMOS Image Sensor Using Column Single-Slope ADCs with Dual-Gain Amplifiers
H. Totsuka, T. Tsuboi, T. Muto, D. Yoshida, Y. Matsuno, M. Ohmura, H. Takahashi, K. Sakurai, T. Ichikawa, H. Yuzurihara, S. Inoue
Canon, Kawasaki, Japan

6.5 A 64×64-Pixel Digital Silicon Photomultiplier Direct ToF Sensor with 100MPhotons/s/pixel Background Rejection and Imaging/Altimeter Mode with 0.14% Precision up to 6km for Spacecraft Navigation and Landing
M. Perenzoni, D. Perenzoni, D. Stoppa
Fondazione Bruno Kessler, Trento, Italy

6.6 A 1280×720 Single-Photon-Detecting Image Sensor with 100dB Dynamic Range Using a Sensitivity-Boosting Technique
M. Mori, Y. Sakata, M. Usuda, S. Yamahira, S. Kasuga, Y. Hirose, Y. Kato, T. Tanaka
Panasonic, Nagaokakyo, Japan

6.7 A 1.2e- Temporal Noise 3D-Stacked CMOS Image Sensor with Comparator-Based Multiple-Sampling PGA
K. Shiraishi, Y. Shinozuka, T. Yamashita, K. Sugiura, N. Watanabe, R. Okamoto, T. Ashitani, M. Furuta, T. Itakura,
Toshiba, Kawasaki, Japan

6.8 A 1.5V 33Mpixel 3D-Stacked CMOS Image Sensor with Negative Substrate Bias
C. C-M. Liu, M. M. Mhala, C-H. Chang, H. Tu, P-S. Chou, C. Chao, F-L. Hsueh
TSMC, Hsinchu, Taiwan

6.9 A 1.1µm 33Mpixel 240fps 3D-Stacked CMOS Image Sensor with 3-Stage Cyclic-Based Analog-to-Digital Converters
T. Arai, T. Yasue, K. Kitamura, H. Shimamoto, T. Kosugi, S. Jun, S. Aoyama, M-C. Hsu, Y. Yamashita, H. Sumi, S. Kawahito
NHK Science & Technology Research Laboratories, Tokyo, Japan
Brookman Technology, Hamamatsu, Japan
TSMC, Hsinchu, Taiwan
Shizuoka University, Hamamatsu, Japan

F5 forum on Advanced IC Design for Ultra-Low-Noise Sensing has a couple of image sensor presentations:

NOISE: You Love It or You Hate It
Albert Theuwissen
Harvest Imaging, Belgium & Delft University of Technology, Delft,The Netherlands

Low-Noise Image Sensors
Shoji Kawahito
Shizuoka University, Hamamatsu, Japan

Noise in Single-Photon-Counting Image Sensors
Neale A.W. Dutton
STMicroelectronics, Edinburgh, United Kingdom

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Caeleste publishes its presentation "UV-White-Yellow Bayer-like pattern imager" by P.Gao, B.Dierickx, Q.Yao, J.Zhu, P.Coppejans, R.Zhang, G.Cai, B.Luyssaert, B.Spinnewyn, A.Kalgi, and D.Van Aken at CNES Image sensor workshop held on Nov. 19, 2015, Toulouse, France. The company proposes to implement the color separation with no usual organic filters on top:

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Point Grey releases the measurements of its 5MP cameras based on CCD and CMOS sensors:

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BusinessWire: ams, an Austrian maker of sensor and analog solutions, is to acquire 100% of the shares in CMOSIS in an all-cash transaction.

Founded in 2007, CMOSIS operates as a fabless image sensor supplier from locations in Belgium, Germany, Portugal, and the U.S. and has more than 110 employees. CMOSIS expects to generate full year 2015 revenues of approx. EUR 60m with strong operating profitability above ams’ current group operating profitability. Based on available information, CMOSIS expects to continue year-on-year revenue growth in 2016.

Under the terms of the agreement, ams will acquire 100% of the shares in CMOSIS from TA Associates, a leading global growth private equity firm, and management shareholders for an equity value of approx. EUR 220m. The transaction is expected to close within the next six weeks subject to regulatory approvals and the occurrence of certain conditions defined in the agreements with the sellers of the CMOSIS shares.

“Acquiring CMOSIS is a highly complementary expansion of our sensor portfolio and another major step in executing our sensor solutions growth strategy. This transaction extends our market leadership in optical sensors and will strengthen our position as the leading pure-play sensor solutions provider for growth markets including Industry 4.0, IoT (Internet of Things) and medical diagnostics. Integrating cameras with advanced optical sensors will drive new sensor solutions across vertical markets and accelerate our growth plans as we combine CMOSIS’ leading edge IP and design capabilities with our manufacturing competence and optical sensor strengths”, emphasizes Kirk Laney, CEO of ams.

“CMOSIS has built a leading position in some of the most challenging imaging applications based on our deep technology expertise in CMOS area and line scan image sensors. Our team is at the forefront of global shutter technology for high-end imaging having up to more than 15 years of experience in this field. We are excited to join ams creating a leader in advanced imaging solutions. We will leverage ams’ technical and operational expertise and profit from the global access to potential new customers to realize our full growth potential”, adds Luc de Mey, CEO of CMOSIS.

Update: Knack.be reports that CMOSIS turnover this year is expected to be about 60m Euros, compared with 54.9m in 2014. The profit after tax in 2014 was 9.5m.

Bloovi.be reports that yesterday, CMOSIS won Deloitte-Belgium 2015 Technology Fast 50 Award for 615% annual turnover growth, possibly based on 2013 and 2014 data.

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Nikkei: Seiichi Gohshi, professor of the Department of Information Design, the Faculty of Informatics, Kogakuin University, and Fujitsu jointly develop a new technology employed for the "Xevic" image processing engine of Fujitsu's Arrows NX F-02H smartphone, to be released in late November 2015. Unlike commonly-used "reconstructed super resolution" and "learning super resolution," the super-resolution technology being researched by Gohshi uses an original method called "nonlinear signal processing method." A nonlinear function is used to supplement high-frequency components and reproduce high-resolution components that surpass the "Nyquist frequency (half of a sampling frequency)," Gohshi said.


The 2014 University research report gives a list of recent publications by Seiichi Gohshi:

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PRNewswire: Panasonic leverages its high speed sensor to introduce a Post Focus feature that captures multiple photos with multiple in focus points through a single release of the shutter. Post Focus uses 49-area DFD (Depth From Defocus) autofocus to capture 4K images at 30 fps. The operation of Post Focus function is quite simple and easy – set the camera to Post Focus mode, and press the shutter button. The camera automatically "racks" the focus while capturing photos with varied in focus points. During the playback, one uses the touch screen to select the in focus area desired, and save as a separate 8MP file:

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IC Insights publishes its new ranking of semiconductor companies. Sony rises to #14:

"One of the real “star performers” on the list is Sony. As shown, even with the tremendous weakness of the yen versus U.S. dollar, the company is forecast to register an 11% increase in semiconductor sales when expressed in U.S. dollars and a 27% surge in sales in its local currency, the Japanese yen. Sony is having tremendous success in sales of image sensors and is expected to more than triple its semiconductor capital spending this year to put in additional capacity for image sensor production."

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Sony announces 1/2.9-inch IMX323LQN sensor with 2.8um pixels in a "compact and thin package while maintaining low illumination performance equal to that of the existing Sony product (IMX222LQJ) that improved sensitivity in the near infrared region for industrial applications."

Existing IMX222LQJ vs new IMX323LQN

Sony publishes 0.6MP comparison pictures of the older IMX222 and the new IMX323 at 0.1 lx, F1.4 (ADC 12 bit mode, 30 frame/s):

IMX222, Gain 42dB

IMX323, Gain 45dB

Sharp's new image sensor catalog presents a new 2MP 2/3-inch video sensor, RJ52N1BA0LT, available in color and B/W versions:

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Pixart reports Q3 2015 results. The sales are 10.3% down YoY, but gross margin rises to 51.2%.

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Samsung Investors Forum held on Nov. 16, 2015 gives interesting details on its image sensor business from Kyushik Hong, VP of Marketing, Samsung System LSI:

"But for some other product like image sensor, we have a number one market share in China market, for example. So, we sell a lot of our image sensor in all the Chinese OEMs."

Q: [ph] Jason (58:35) from [indiscernible] (58:34). "Can you please comment on [indiscernible] (58:38) how your image sensor technology compares to one of your Japanese competitors, and for the image sensor, besides mobile, what areas are you focusing on and how do you see your business penetrating into the mobile side?"

A: "Okay. So, I think for image sensor technology innovation. It has to come from, I mean – in large probably has to come from the process technology. So, having you around fab and you around process – I mean, the pixel process technology this is very important. So, I think that's not some fables, the base, the image sensor company can do. But particular company that you mentioned, a Japanese company, they also have their own process technology to develop the pixel quality. So, in that sense, I think we are pretty much on par.

But the one we have in addition to that is we also have very advanced logic technology as well. And probably you know that all the advanced image sensor is now all this [ph] packed (59:56) sensor. So, meaning that [indiscernible] (59:58) part of the sensor is surely the pixel and you put all this kind of logics that can handle all the immediate processing, stuff like that, into the separate dedicated logic chip and you just stack them together and these are too part of the sensor can work in perfect harmony as well.

So, Samsung, I think, one of the advantage we do have is that we do have both pixel [ph] in-house (01:00:27) pixel technology, as well as advanced logic technology as well. So that we can stack them together by taking advantage of the synergy between this technology.

And I think the second question is about the application outside the mobile, right? So, that's definitely another very exciting subject. Today's subject is about mobile, so I'm pretty much focused on mobile application. But we do have – we do see a lot of opportunity in other applications as well. And automotive is one clear example and, again, combining some of the processing power that we can provide.

So, for example, like automotive, like – there could be like 16 images sensors that has to be working at the same time, and you can't – you have to handle all of this kind of – the video images at the same time for very sophisticated [indiscernible] (01:01:33) type of automotive application. So, definitely automotive is one area. And there could be a lot of even consumer electronics area. Like in this case, even this robot [indiscernible] (01:01:49) they have some imaging sensors inside. So, we're constantly looking at some other opportunity. And we believe all the technology that we built upon the mobile device will greatly help to – for us to expand our area outside the mobile."

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ON Semiconductor announces a new 16.2MP CCD for astrophotography and scientific imaging application. The KAF-16200 APS-H (34.6 mm diagonal) CCD is said to provide best in class image uniformity and dark current, and uses 6.0µm pixels with a transparent gate electrode for high sensitivity, high DR, and integrated overexposure protection.

“This new image sensor targets opportunities directly identified by our camera manufacturing customers,” said Herb Erhardt, VP and GM, Industrial and Security Division, Image Sensor Group at ON Semiconductor, “The KAF-16200 provides a 2x increase in resolution compared to our current device addressing this segment, without sacrificing the CCD-level image quality required for these applications. This is another example of ON Semiconductor’s ability to leverage a broad technology base to provide the highest quality image sensor devices regardless of the underlying technology.”

The KAF-16200 is available in both monochrome and color configurations.

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IEEE Spectrum: The SwissFEL laser team led by Christoph Hauri at the Paul Scherrer Institute near Zurich shows that one can use a commercial megapixel CCD to capture THz-band images. "It was previously known that low frequency radiation, when intense enough, could lead to dramatic changes in the semiconductor band structure. (For the intense light source they turned to a new and uniquely powerful source the SwissFEL team developed.) Long terahertz wavelengths force electrons to tunnel through the bandgap and the charge carriers start multiplying, leading to huge sensitivity."

The open access paper "High-performing nonlinear visualization of terahertz radiation on a silicon charge-coupled device" by Mostafa Shalaby, Carlo Vicario, and Christoph Hauri with the experimental results has been published in Nature Communications:

(a) Time-dependent electric field of the THz pulse retrieved using air-biased-coherent-detection technique. (b) The corresponding broadband amplitude spectrum. A narrowband portion centered around 10 THz is obtained by application of a band pass filter (BPF). (c) The detected images (normalized) on the (4.65-μm pixel size) CCD obtained with the 10 THz BPF in different slices around the focus with z being the propagation direction. The corresponding real images reconstructed taking the natural logarithm (as discussed later). The beam consists of several smaller beams that focus in different planes. The images obtained with a (23.5-μm pixel size) bolometric imager are shown. All images are plotted at the same scale on dimension of 200 × 200 μm. In the focal plane (z=0 μm), two spots are visible with a separation of 51 μm. While the pixel size is smaller than 51 μm in both cameras and so the two spots were obvious in both images, the high-resolving image from the CCD provides a significantly more detailed and accurate beam profile.

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Sony publishes a flyer of 13MP, 1.12um RGB pixel IMX258 used in a number of recent phones, including Xiaomi Mi 4C.

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Albert Theuwissen publishes what might be the most extensive research on PDAF pixels so far. The research is based on Aptina MT9J007C1HS sensor as an example. "Harvest Imaging performed measurements on the PDAF pixels present in an existing, commercially available camera. The results of these measurements, including explanations for the PDAF performance/behaviour are written down in an extensive report."

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