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Electronics
Special Issues
Image Sensors and Companion Chips
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Image Sensors and Companion Chips

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microelectronics".

Deadline for manuscript submissions: closed (20 August 2024) | Viewed by 3041

Special Issue Editor

Dr. Kaiming Nie

E-Mail Website
Guest Editor
School of Microelectronics, Tianjin University, Tianjin 300072, China
Interests: CMOS image sensors; mixed-signal integrated circuits

Special Issue Information

Dear Colleagues,

CMOS image sensors are highly integrated optoelectronic chips which convert optical information into digital information that is easy to process and store. Due to the rapid development of CMOS technologies, the performance of CMOS image sensors has been greatly improved, and the functionality of CMOS image sensors has also diversified. Nowadays, CMOS image sensors undergo a widespread application in various field, such as mobile devices, consumer electronics, AR/VR devices, automotive electronics, security monitoring, medical imaging, industrial imaging, spacing imaging, scientific observation, and so on. To form an imaging system, CMOS image sensors are usually companied with some other chips, such as image signal processor, digital signal processor, interface circuit chips, etc. With the development of 3D integration and packaging technology, multiple chips can be integrated into one chip to form more compact imaging systems.

This Special Issue encourages researchers to present their theories, techniques, circuits, and systems of CMOS chips for image sensing and companion chips. The scope of this Special Issue focuses on, but is not limited to:

  • CMOS image sensor modeling;
  • High-performance active pixels;
  • Low-noise readout circuits;
  • High-speed imaging techniques;
  • Dynamic range extension technology;
  • Low-light imaging;
  • High-resolution imaging;
  • 3D imaging;
  • Dynamic vision sensors;
  • Spike-based image sensors;
  • Sensory and computational integration;
  • Image signal processing;
  • Single photon counting technique;
  • Image sensor interfaces.

Dr. Kaiming Nie
Guest Editor

Manuscript Submission Information

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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. Electronics 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 2400 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
  • pixels
  • readout circuits
  • low-light imaging
  • high dynamic range
  • high-speed imaging
  • 3D imaging
  • DVS
  • ISP
  • SPAD

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Published Papers (2 papers)

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12 pages, 7017 KiB  
Article
A Low-Power, High-Resolution Analog Front-End Circuit for Carbon-Based SWIR Photodetector
by Yuyan Zhang, Zhifeng Chen, Wenli Liao, Weirong Xi, Chengying Chen and Jianhua Jiang
Electronics 2024, 13(18), 3708; https://doi.org/10.3390/electronics13183708 - 18 Sep 2024
Viewed by 1267
Abstract
Carbon nanotube field-effect transistors (CNT-FETs) have shown great promise in infrared image detection due to their high mobility, low cost, and compatibility with silicon-based technologies. This paper presents the design and simulation of a column-level analog front-end (AFE) circuit tailored for carbon-based short-wave [...] Read more.
Carbon nanotube field-effect transistors (CNT-FETs) have shown great promise in infrared image detection due to their high mobility, low cost, and compatibility with silicon-based technologies. This paper presents the design and simulation of a column-level analog front-end (AFE) circuit tailored for carbon-based short-wave infrared (SWIR) photodetectors. The AFE integrates a Capacitor Trans-impedance Amplifier (CTIA) for current-to-voltage conversion, coupled with Correlated Double Sampling (CDS) for noise reduction and operational amplifier offset suppression. A 10-bit/125 kHz Successive Approximation analog-to-digital converter (SAR ADC) completes the signal processing chain, achieving rail-to-rail input/output with minimized component count. Fabricated using 0.18 μm CMOS technology, the AFE demonstrates a high signal-to-noise ratio (SNR) of 59.27 dB and an Effective Number of Bits (ENOB) of 9.35, with a detectable current range from 500 pA to 100.5 nA and a total power consumption of 7.5 mW. These results confirm the suitability of the proposed AFE for high-precision, low-power SWIR detection systems, with potential applications in medical imaging, night vision, and autonomous driving systems. Full article
(This article belongs to the Special Issue Image Sensors and Companion Chips)
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18 pages, 6500 KiB  
Article
NSVDNet: Normalized Spatial-Variant Diffusion Network for Robust Image-Guided Depth Completion
by Jin Zeng and Qingpeng Zhu
Electronics 2024, 13(12), 2418; https://doi.org/10.3390/electronics13122418 - 20 Jun 2024
Cited by 1 | Viewed by 1364
Abstract
Depth images captured by low-cost three-dimensional (3D) cameras are subject to low spatial density, requiring depth completion to improve 3D imaging quality. Image-guided depth completion aims at predicting dense depth images from extremely sparse depth measurements captured by depth sensors with the guidance [...] Read more.
Depth images captured by low-cost three-dimensional (3D) cameras are subject to low spatial density, requiring depth completion to improve 3D imaging quality. Image-guided depth completion aims at predicting dense depth images from extremely sparse depth measurements captured by depth sensors with the guidance of aligned Red–Green–Blue (RGB) images. Recent approaches have achieved a remarkable improvement, but the performance will degrade severely due to the corruption in input sparse depth. To enhance robustness to input corruption, we propose a novel depth completion scheme based on a normalized spatial-variant diffusion network incorporating measurement uncertainty, which introduces the following contributions. First, we design a normalized spatial-variant diffusion (NSVD) scheme to apply spatially varying filters iteratively on the sparse depth conditioned on its certainty measure for excluding depth corruption in the diffusion. In addition, we integrate the NSVD module into the network design to enable end-to-end training of filter kernels and depth reliability, which further improves the structural detail preservation via the guidance of RGB semantic features. Furthermore, we apply the NSVD module hierarchically at multiple scales, which ensures global smoothness while preserving visually salient details. The experimental results validate the advantages of the proposed network over existing approaches with enhanced performance and noise robustness for depth completion in real-use scenarios. Full article
(This article belongs to the Special Issue Image Sensors and Companion Chips)
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