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Special Issue "CMOS Image Sensors and Related Applications"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 30 November 2020.

Special Issue Editor

Prof. Byung-geun Lee
Website
Guest Editor
Gwangju Institute of Science and Technology, Gwangju, Korea
Interests: CMOS image sensors for industrial/space applications; hardware neural network (Neuromorphic) system development; analog and mixed-signal IC design; digital calibration techniques for analog circuit errors

Special Issue Information

Dear Colleagues,

It is my pleasure to invite you to submit your valuable research outcomes to this Special Issue, titled “CMOS Image Sensors and Related Applications”.

CMOS image sensor (CIS) technology has made dramatic improvements over the past few decades. The enormous contribution of many researchers and the ever-increasing demand for mobile applications such as smartphone, digital camera, and tablet computers have led to the great commercial success of CIS. Ongoing progress in CIS technology, including pixel and readout architectures, device, and circuit, allows its application to expand beyond capturing high-quality images. In addition to traditional, yet still important, CIS and its applications, a new CIS architecture and its implementation for emerging technologies, such as real-time image recognition for self-driving vehicle, imaging systems for artificial neural networks, computational bio-imaging, and so on, have become the focus of recent research.

The aim of this Special Issue is to share and publish high-quality peer-reviewed papers in the area of CIS technology and its applications. The editorial board invites researchers to contribute to the field of high-performance CIS technologies including novel CIS architectures and implementations, high-performance pixel-readout circuits, on-chip image generation and processing, and a new CIS dedicated to task-specific imaging systems. Topics of this issue include but are not limited to:

  • CMOS image sensor architecture and circuit implementation;
  • High-frame rate and/or low-power CMOS image sensors;
  • Wide-dynamic range CMOS image sensors;
  • Imaging systems employing state-of-the-art CMOS image sensors;
  • High-performance pixel readout circuits including analog-to-digital converters.

Prof. Byung-geun Lee
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • CMOS image sensor
  • pixel readout circuit
  • image processing
  • imaging system

Published Papers (3 papers)

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Open AccessArticle
Angular Light, Polarization and Stokes Parameters Information in a Hybrid Image Sensor with Division of Focal Plane
Sensors 2020, 20(12), 3391; https://doi.org/10.3390/s20123391 - 16 Jun 2020
Abstract
Targeting 3D image reconstruction and depth sensing, a desirable feature for complementary metal oxide semiconductor (CMOS) image sensors is the ability to detect local light incident angle and the light polarization. In the last years, advances in the CMOS technologies have enabled dedicated [...] Read more.
Targeting 3D image reconstruction and depth sensing, a desirable feature for complementary metal oxide semiconductor (CMOS) image sensors is the ability to detect local light incident angle and the light polarization. In the last years, advances in the CMOS technologies have enabled dedicated circuits to determine these parameters in an image sensor. However, due to the great number of pixels required in a cluster to enable such functionality, implementing such features in regular CMOS imagers is still not viable. The current state-of-the-art solutions require eight pixels in a cluster to detect local light intensity, incident angle and polarization. The technique to detect local incident angle is widely exploited in the literature, and the authors have shown in previous works that it is possible to perform the job with a cluster of only four pixels. In this work, the authors explore three novelties: a mean to determine three of four Stokes parameters, the new paradigm in polarization cluster-pixel design, and the extended ability to detect both the local light angle and intensity. The features of the proposed pixel cluster are demonstrated through simulation program with integrated circuit emphasis (SPICE) of the regular Quadrature Pixel Cluster and Polarization Pixel Cluster models, the results of which are compliant with experimental results presented in the literature. Full article
(This article belongs to the Special Issue CMOS Image Sensors and Related Applications)
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Open AccessArticle
Assessing the Influence of Temperature Changes on the Geometric Stability of Smartphone- and Raspberry Pi Cameras
Sensors 2020, 20(3), 643; https://doi.org/10.3390/s20030643 - 23 Jan 2020
Abstract
Knowledge about the interior and exterior camera orientation parameters is required to establish the relationship between 2D image content and 3D object data. Camera calibration is used to determine the interior orientation parameters, which are valid as long as the camera remains stable. [...] Read more.
Knowledge about the interior and exterior camera orientation parameters is required to establish the relationship between 2D image content and 3D object data. Camera calibration is used to determine the interior orientation parameters, which are valid as long as the camera remains stable. However, information about the temporal stability of low-cost cameras due to the physical impact of temperature changes, such as those in smartphones, is still missing. This study investigates on the one hand the influence of heat dissipating smartphone components at the geometric integrity of implemented cameras and on the other hand the impact of ambient temperature changes at the geometry of uncoupled low-cost cameras considering a Raspberry Pi camera module that is exposed to controlled thermal radiation changes. If these impacts are neglected, transferring image measurements into object space will lead to wrong measurements due to high correlations between temperature and camera’s geometric stability. Monte-Carlo simulation is used to simulate temperature-related variations of the interior orientation parameters to assess the extent of potential errors in the 3D data ranging from a few millimetres up to five centimetres on a target in X- and Y-direction. The target is positioned at a distance of 10 m to the camera and the Z-axis is aligned with camera’s depth direction. Full article
(This article belongs to the Special Issue CMOS Image Sensors and Related Applications)
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Open AccessLetter
Design of an Edge-Detection CMOS Image Sensor with Built-in Mask Circuits
Sensors 2020, 20(13), 3649; https://doi.org/10.3390/s20133649 - 29 Jun 2020
Abstract
In this paper, we propose a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that has built-in mask circuits to selectively capture either edge-detection images or normal 8-bit images for low-power computer vision applications. To detect the edges of images in the CIS, neighboring column [...] Read more.
In this paper, we propose a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that has built-in mask circuits to selectively capture either edge-detection images or normal 8-bit images for low-power computer vision applications. To detect the edges of images in the CIS, neighboring column data are compared in in-column memories after column-parallel analog-to-digital conversion with the proposed mask. The proposed built-in mask circuits are implemented in the CIS without a complex image signal processer to obtain edge images with high speed and low power consumption. According to the measurement results, edge images were successfully obtained with a maximum frame rate of 60 fps. A prototype sensor with 1920 × 1440 resolution was fabricated with a 90-nm 1-poly 5-metal CIS process. The area of the 4-shared 4T-active pixel sensor was 1.4 × 1.4 µm2, and the chip size was 5.15 × 5.15 mm2. The total power consumption was 9.4 mW at 60 fps with supply voltages of 3.3 V (analog), 2.8 V (pixel), and 1.2 V (digital). Full article
(This article belongs to the Special Issue CMOS Image Sensors and Related Applications)
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