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Electronics
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Circuits, Systems, and Signal Processing for Display Applications
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Circuits, Systems, and Signal Processing for Display Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".

Deadline for manuscript submissions: closed (1 March 2022) | Viewed by 8160

Special Issue Editor

Prof. Dr. Seung-Woo Lee

E-Mail Website
Guest Editor
Department of Information Display, Kyung Hee University, Seoul 02447, Republic of Korea
Interests: integrated TFT circuits; low-power technology; display technologies; AR/VR systems; psychophysical studies

Special Issue Information

Dear Colleagues,

The purpose of this Special Issue is to publish high-quality research in advanced circuits, systems, and signal processing for display applications. IT (information technology) devices such as smart watches, mobile phones, laptop computers, flat TVs, and AR/VR headsets employ displays. Liquid crystal displays (LCDs) and organic light emitting diode (OLED) displays are the most widely used in our lives. In addition, many novel display devices for future applications have been proposed. Driving technologies and electronics that complete the implementation of display systems are one of the most important factors for the commercialization of them. We invite the scientific community to provide high-quality contributions with consolidated and evaluated research related to this promising investigation area.

The topics of interest include, but are not limited to:

  • Driving technologies
  • TFT circuits
  • Display driver ICs
  • Image quality enhancement technologies
  • Motion quality enhancement technologies
  • Touch and interactive displays
  • Human-machine interface technologies
  • High speed interface
  • Novel display system technologies
  • AR/VR/MR display systems
  • Human factors for display applications
  • Machine learning for display applications
  • Color technologies for novel displays

Prof. Dr. Seung-Woo 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 submissions that pass pre-check are 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. 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.

Published Papers (4 papers)

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Research

14 pages, 3971 KiB  
Article
DCT Domain Detail Image Enhancement for More Resolved Images
by Seongbae Bang and Wonha Kim
Electronics 2021, 10(20), 2461; https://doi.org/10.3390/electronics10202461 - 11 Oct 2021
Cited by 1 | Viewed by 1343
Abstract
This paper develops a detail image signal enhancement that makes images perceived as being clearer and more resolved and so more effective for higher resolution displays. We observe that the local variant signal enhancement makes images more vivid, and the more revealed granular [...] Read more.
This paper develops a detail image signal enhancement that makes images perceived as being clearer and more resolved and so more effective for higher resolution displays. We observe that the local variant signal enhancement makes images more vivid, and the more revealed granular signals harmonically embedded on the local variant signals make images more resolved. Based on this observation, we develop a method that not only emphasizes the local variant signals by scaling up the frequency energy in accordance with human visual perception, but also strengthens the granular signals by embedding the alpha-rooting enhanced frequency components. The proposed energy scaling method emphasizes the detail signals in texture images and rarely boosts noisy signals in plain images. In addition, to avoid the local ringing artifact, the proposed method adjusts the enhancement direction to be parallel to the underlying image signal direction. It was verified through subjective and objective quality evaluations that the developed method makes images perceived as clearer and highly resolved. Full article
(This article belongs to the Special Issue Circuits, Systems, and Signal Processing for Display Applications)
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9 pages, 1912 KiB  
Article
Body-Effect-Free OLED-on-Silicon Pixel Circuit Based on Capacitive Division to Extend Data Voltage Range
by Jina Bae and Hyoungsik Nam
Electronics 2021, 10(19), 2351; https://doi.org/10.3390/electronics10192351 - 26 Sep 2021
Cited by 2 | Viewed by 2473
Abstract
This paper proposes an OLED pixel compensation circuit that copes with threshold voltage variation, narrow data voltage range, and body effect on a backplane of silicon-based transistors. It consists of six PMOS transistors and two capacitors. The data voltage range is extended by [...] Read more.
This paper proposes an OLED pixel compensation circuit that copes with threshold voltage variation, narrow data voltage range, and body effect on a backplane of silicon-based transistors. It consists of six PMOS transistors and two capacitors. The data voltage range is extended by the capacitor division with two capacitors, and the connection of both source and gate nodes to the supply voltage makes the driving transistor free from the body effect. In addition, the reference voltage is used to initialize the gate node voltage of the driving transistor as well as to adjust the data voltage region. By the SPICE simulation, it is verified that the current error over the threshold voltage variations of ±10 mV is reduced to be −1.200% to 0.964% at the maximum current range of around 8 nA, and the data voltage range is extended to 3.4 V, compared to the large current error range from −21.46% to 27.36% and the data voltage range of 0.41 V in the basic 2T1C circuit. In addition, the body-effect-free circuit outperforms the latest 4T1C circuit of the current error range from −3.279% to 3.388%. Full article
(This article belongs to the Special Issue Circuits, Systems, and Signal Processing for Display Applications)
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13 pages, 5085 KiB  
Article
Study on the Effect of Gaze Position and Image Brightness on Peripheral Dimming Technique
by Jeong-Sik Kim, Won-Been Jeong, Byeong Hun An and Seung-Woo Lee
Electronics 2021, 10(16), 1896; https://doi.org/10.3390/electronics10161896 - 07 Aug 2021
Viewed by 1810
Abstract
Here, we study a low-power technique for displays based on gaze tracking, called peripheral dimming. In this work, the threshold levels of the lightness reduction ratio (LRR), where people notice differences in brightness, depending on gaze positions and image brightness, are investigated. A [...] Read more.
Here, we study a low-power technique for displays based on gaze tracking, called peripheral dimming. In this work, the threshold levels of the lightness reduction ratio (LRR), where people notice differences in brightness, depending on gaze positions and image brightness, are investigated. A psychophysical experiment with five gaze positions and three image brightness conditions is performed, and the estimated threshold levels are obtained. To investigate the significance of the differences between the threshold levels, the overlap method and the Bayesian estimation (BEST) analysis are performed. The analysis results show that the difference of the threshold levels depending on the conditions is insignificant. Thus, the proposed technique can operate with a constant LRR level, regardless of the gaze position or image brightness, while maintaining the perceptual image quality. In addition, the proposed technique reduces the power consumption of virtual reality (VR) displays by 12–14% on average. We believe that the peripheral dimming technique would contribute to reducing the power of the self-luminous displays used for VR headsets with an integrated eye tracker. Full article
(This article belongs to the Special Issue Circuits, Systems, and Signal Processing for Display Applications)
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19 pages, 14061 KiB  
Article
Deep Gradient Prior Regularized Robust Video Super-Resolution
by Qiang Song and Hangfan Liu
Electronics 2021, 10(14), 1641; https://doi.org/10.3390/electronics10141641 - 09 Jul 2021
Cited by 6 | Viewed by 1749
Abstract
This paper proposes a robust multi-frame video super-resolution (SR) scheme to obtain high SR performance under large upscaling factors. Although the reference low-resolution frames can provide complementary information for the high-resolution frame, an effective regularizer is required to rectify the unreliable information from [...] Read more.
This paper proposes a robust multi-frame video super-resolution (SR) scheme to obtain high SR performance under large upscaling factors. Although the reference low-resolution frames can provide complementary information for the high-resolution frame, an effective regularizer is required to rectify the unreliable information from the reference frames. As the high-frequency information is mostly contained in the image gradient field, we propose to learn the gradient-mapping function between the high-resolution (HR) and the low-resolution (LR) image to regularize the fusion of multiple frames. In contrast to the existing spatial-domain networks, we train a deep gradient-mapping network to learn the horizontal and vertical gradients. We found that adding the low-frequency information (mainly from the LR image) to the gradient-learning network can boost the performance of the network. A forward and backward motion field prior is used to regularize the estimation of the motion flow between frames. For robust SR reconstruction, a weighting scheme is proposed to exclude the outlier data. Visual and quantitative evaluations on benchmark datasets demonstrate that our method is superior to many state-of-the-art methods and can recover better details with less artifacts. Full article
(This article belongs to the Special Issue Circuits, Systems, and Signal Processing for Display Applications)
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