The Experts below are selected from a list of 273 Experts worldwide ranked by ideXlab platform

Ohkyong Kwon - One of the best experts on this subject based on the ideXlab platform.

  • simple Pixel circuits for high resolution and high image quality organic light emitting diode on silicon microdisplays with wide data voltage range
    Journal of The Society for Information Display, 2016
    Co-Authors: Sangwoon Hong, Bongchoon Kwak, Seongkwan Hong, Ohkyong Kwon
    Abstract:

    Two simple Pixel circuits are proposed for high resolution and high image quality organic light-emitting diode-on-silicon microdisplays. The proposed Pixel circuits achieve high resolution due to simple Pixel Structure comprising three n-type MOSFETs and one storage capacitor, which are integrated into a unit subPixel area of 3 × 9 µm2 using a 90 nm CMOS process. The proposed Pixel circuits improve image quality by compensating for the threshold voltage variation of the driving transistors and extending the data voltage range. To verify the performance of the proposed Pixel circuits, the emission currents of 24 Pixel circuits are measured. The measured emission current deviation error of the proposed Pixel circuits A and B ranges from −2.59% to +2.78%, and from −1.86% to +1.84%, respectively, which are improved from the emission current deviation error of the conventional current-source type Pixel circuit when the threshold voltage variation is not compensated for, which ranges from −14.87% to +14.67%. In addition, the data voltage ranges of the proposed Pixel circuits A and B are 1.193 V and 1.792 V, respectively, which are 2.38 and 3.57 times wider than the data voltage range of the conventional current-source type Pixel circuit of 0.501 V.

  • 35 1 high resolution amoled Pixel using negative feedback Structure for improving image quality
    Digest of Technical Papers - SID International Symposium, 2013
    Co-Authors: Nack-hyeon Keum, Ohkyong Kwon
    Abstract:

    An active matrix organic light emitting diode (AMOLED) Pixel Structure is proposed to improve image quality of high resolution small sized displays. The proposed Pixel Structure increases luminance uniformity by decreasing the distortion of the voltage in the storage capacitors using negative feedback Structure. The simulation results show that the distortion of the voltage in the storage capacitors with negative feedback Structure decreases to 55.3% compared to that without negative feedback Structure and the emission current error of the proposed Pixel Structure ranges from −0.71 LSB to 0.56 LSB when the threshold voltage of the driving TFT varies from −0.2 V to 0.2 V.

  • A Simple Pixel Structure Using Polycrystalline-Silicon Thin-Film Transistors for High-Resolution Active-Matrix Organic Light-Emitting Diode Displays
    IEEE Electron Device Letters, 2012
    Co-Authors: Hai-jung In, Ohkyong Kwon
    Abstract:

    A simple Pixel Structure comprising two transistors and one capacitor and a novel driving method are proposed for small-sized and high-resolution active-matrix organic light-emitting diode displays on polycrystalline-silicon thin-film transistor (TFT) backplane. The proposed Pixel increases the yield due to small number of TFTs and improves image quality by compensating threshold voltage variations of driving TFTs. The proposed Pixel is designed as test Pixels with 353 Pixels per inch, and the measured emission current error range of -74.2% -60.6% is improved to the range of -2.5% -2.1% when the proposed Pixel is used.

  • a novel voltage programming Pixel with current correction method for large size and high resolution amoleds on poly si backplane
    한국정보디스플레이학회 2005년도 International Meeting on Information Displayvol.II, 2005
    Co-Authors: Joonho Bae, Ohkyong Kwon, Jinsung Kang, Hokyoon Chung
    Abstract:

    A novel active matrix organic light diodes (AMOLEDs) voltage-programming Pixel Structure with current-correction method is proposed for largesize and high-resolution poly-Si AMOLED panel applications. The HSPICE simulation results shows that the maximum error of emission current in proposed Pixel is 1.536%, 2.45%, and 2.97% with the ${\pm}12.5%$ mobility variation and ${\pm}0.3V$ threshold voltage variation for 30-, 40-, and 50-inch HDTV panels, respectively.

  • p 11 an improved voltage programmed Pixel Structure for large size and high resolution am oled displays
    SID Symposium Digest of Technical Papers, 2004
    Co-Authors: Sangmoo Choi, Ohkyong Kwon, Hokyun Chung
    Abstract:

    We propose an improved Pixel Structure for large size and high resolution AM-OLED(Active matrix-Organic Light Emitting Diode) displays. The proposed Structure is composed of 5 TFT and 1 capacitor. It can compensate not only the threshold voltage variation of LTPS(Low Temperature Poly Silicon) TFTs but also the voltage drop of supply voltage on panel. Moreover, it operates with simple Structure and control signals. In this paper, we describe the operating principle and the characteristics of the proposed Pixel Structure and verify the performance by HSPICE simulation comparing with those of previously reported Structures.

Kinman Lam - One of the best experts on this subject based on the ideXlab platform.

  • face hallucination based on sparse local Pixel Structure
    Pattern Recognition, 2014
    Co-Authors: Cheng Cai, Guoping Qiu, Kinman Lam
    Abstract:

    In this paper, we propose a face-hallucination method, namely face hallucination based on sparse local-Pixel Structure. In our framework, a high resolution (HR) face is estimated from a single frame low resolution (LR) face with the help of the facial dataset. Unlike many existing face-hallucination methods such as the from local-Pixel Structure to global image super-resolution method (LPS-GIS) and the super-resolution through neighbor embedding, where the prior models are learned by employing the least-square methods, our framework aims to shape the prior model using sparse representation. Then this learned prior model is employed to guide the reconstruction process. Experiments show that our framework is very flexible, and achieves a competitive or even superior performance in terms of both reconstruction error and visual quality. Our method still exhibits an impressive ability to generate plausible HR facial images based on their sparse local Structures. Our framework aims to shape the prior model using sparse representation.Global Structure and local-Pixel Structure are incorporated to produce plausible facial details.A method to learn local-Pixel Structures based on sparse representation is proposed.The proposed method is competitive with other, state-of-the-art face-hallucination methods.

  • from local Pixel Structure to global image super resolution a new face hallucination framework
    IEEE Transactions on Image Processing, 2011
    Co-Authors: Kinman Lam, Guoping Qiu, Tingzhi Shen
    Abstract:

    We have developed a new face hallucination framework termed from local Pixel Structure to global image super-resolution (LPS-GIS). Based on the assumption that two similar face images should have similar local Pixel Structures, the new framework first uses the input low-resolution (LR) face image to search a face database for similar example high-resolution (HR) faces in order to learn the local Pixel Structures for the target HR face. It then uses the input LR face and the learned Pixel Structures as priors to estimate the target HR face. We present a three-step implementation procedure for the framework. Step 1 searches the database for example faces that are the most similar to the input, and then warps the example images to the input using optical flow. Step 2 uses the warped HR version of the example faces to learn the local Pixel Structures for the target HR face. An effective method for learning local Pixel Structures from an individual face, and an adaptive procedure for fusing the local Pixel Structures of different example faces to reduce the influence of warping errors, have been developed. Step 3 estimates the target HR face by solving a constrained optimization problem by means of an iterative procedure. Experimental results show that our new method can provide good performances for face hallucination, both in terms of reconstruction error and visual quality; and that it is competitive with existing state-of-the-art methods.

Guoping Qiu - One of the best experts on this subject based on the ideXlab platform.

  • face hallucination based on sparse local Pixel Structure
    Pattern Recognition, 2014
    Co-Authors: Cheng Cai, Guoping Qiu, Kinman Lam
    Abstract:

    In this paper, we propose a face-hallucination method, namely face hallucination based on sparse local-Pixel Structure. In our framework, a high resolution (HR) face is estimated from a single frame low resolution (LR) face with the help of the facial dataset. Unlike many existing face-hallucination methods such as the from local-Pixel Structure to global image super-resolution method (LPS-GIS) and the super-resolution through neighbor embedding, where the prior models are learned by employing the least-square methods, our framework aims to shape the prior model using sparse representation. Then this learned prior model is employed to guide the reconstruction process. Experiments show that our framework is very flexible, and achieves a competitive or even superior performance in terms of both reconstruction error and visual quality. Our method still exhibits an impressive ability to generate plausible HR facial images based on their sparse local Structures. Our framework aims to shape the prior model using sparse representation.Global Structure and local-Pixel Structure are incorporated to produce plausible facial details.A method to learn local-Pixel Structures based on sparse representation is proposed.The proposed method is competitive with other, state-of-the-art face-hallucination methods.

  • from local Pixel Structure to global image super resolution a new face hallucination framework
    IEEE Transactions on Image Processing, 2011
    Co-Authors: Kinman Lam, Guoping Qiu, Tingzhi Shen
    Abstract:

    We have developed a new face hallucination framework termed from local Pixel Structure to global image super-resolution (LPS-GIS). Based on the assumption that two similar face images should have similar local Pixel Structures, the new framework first uses the input low-resolution (LR) face image to search a face database for similar example high-resolution (HR) faces in order to learn the local Pixel Structures for the target HR face. It then uses the input LR face and the learned Pixel Structures as priors to estimate the target HR face. We present a three-step implementation procedure for the framework. Step 1 searches the database for example faces that are the most similar to the input, and then warps the example images to the input using optical flow. Step 2 uses the warped HR version of the example faces to learn the local Pixel Structures for the target HR face. An effective method for learning local Pixel Structures from an individual face, and an adaptive procedure for fusing the local Pixel Structures of different example faces to reduce the influence of warping errors, have been developed. Step 3 estimates the target HR face by solving a constrained optimization problem by means of an iterative procedure. Experimental results show that our new method can provide good performances for face hallucination, both in terms of reconstruction error and visual quality; and that it is competitive with existing state-of-the-art methods.

Seungwoo Lee - One of the best experts on this subject based on the ideXlab platform.

  • a low power memory in Pixel circuit for liquid crystal displays comprising low temperature poly silicon and oxide thin film transistors
    Electronics, 2020
    Co-Authors: Jongbin Kim, Woorim Lee, Hoonju Chung, Seungwoo Lee
    Abstract:

    In this paper, a new Pixel Structure using low-temperature polycrystalline silicon and oxide (LTPO) thin-film transistors (TFTs) for low-power liquid crystal displays (LCDs) is proposed. The extremely low off-state current of oxide semiconductor TFTs enables the proposed circuit to operate at a very low frame frequency of 1/60 Hz, so that the power consumption can be significantly reduced. In addition, the low-temperature polycrystalline silicon TFTs with high reliability directly drive Pixels, which can achieve stable and flicker-free LCDs. The proposed circuit is fabricated using the LTPO TFT backplane and successfully verified by simulation and measurement results. The measurement results prove that the proposed circuit operates well without further programming for 60 s, and the power consumption in the panel (except backlight power) can be reduced to 0.02% of that of conventional LCD.

Myunghan Bae - One of the best experts on this subject based on the ideXlab platform.

  • a vga indirect time of flight cmos image sensor with 4 tap 7 mu m global shutter Pixel and fixed pattern phase noise self compensation
    IEEE Journal of Solid-state Circuits, 2020
    Co-Authors: Minsun Keel, Young Chan Kim, Myunghan Bae, Younggu Jin, Daeyun Kim, Yeomyung Kim, Bumsik Chung, Sooho Son, Hogyun Kim, Sung-ho Choi
    Abstract:

    A video graphics array (VGA) (640 $\times $ 480) indirect time-of-flight (ToF) CMOS image sensor has been designed with 4-tap 7- $\mu \text{m}$ global-shutter Pixel in 65-nm back-side illumination (BSI) process. With a 4-tap Pixel Structure, we achieved motion artifact-free depth map. Peak current during exposure time has been reduced by current spreading with constant delay chain in the photo-gate driver. Column fixed-pattern phase noise (FPPN) from the constant delay chain is self-compensated by the proposed time-interleaving technique with the two inversely directional clock chains in the photo-gate driver. Quantum efficiency (QE) and demodulation contrast (DC) have been optimized by using appropriate optical engineering techniques with an optimal silicon thickness. As a result, QE of 34% at 940-nm near-infrared and high DC of 86% at 100-MHz modulation frequency have been achieved. In addition, motion artifact and column FPPN are successfully removed in the depth map. The proposed ToF sensor shows depth noise less than 0.57% with 940-nm illuminator over the working distance up to 4 m, and consumes only 160 mW for VGA output at 60 frames/s.

  • optimization of linear logarithmic cmos image sensor using a photogate and a cascode mosfet for reducing Pixel response variation
    Proceedings of SPIE, 2017
    Co-Authors: Myunghan Bae, Byoungsoo Choi, Sang-hwan Kim, Jimin Lee, Jangkyoo Shin
    Abstract:

    Recently, CMOS image sensors (CISs) have become more and more complex because they require high-performances such as wide dynamic range, low-noise, high-speed operation, high-resolution and so on. First of all, wide dynamic range (WDR) is the first requirement for high-performance CIS. Several techniques have been proposed to improve the dynamic range. Although logarithmic Pixel can achieve wide dynamic range, it leads to a poor signal-to-noise ratio due to small output swings. Furthermore, the fixed pattern noise of logarithmic Pixel is significantly greater compared with other CISs. In this paper, we propose an optimized linear-logarithmic Pixel. Compared to a conventional 3-transistor active Pixel sensor Structure, the proposed linear-logarithmic Pixel is using a photogate and a cascode MOSFET in addition. The photogate which is surrounding a photodiode carries out change of sensitivity in the linear response and thus increases the dynamic range. The logarithmic response is caused by a cascode MOSFET. Although the dynamic range of the Pixel has been improved, output curves of each Pixel were not uniform. In general, as the number of devices increases in the Pixel, Pixel response variation is more pronounced. Hence, we optimized the linear-logarithmic Pixel Structure to minimize the Pixel response variation. We applied a hard reset method and an optimized cascode MOSFET to the proposed Pixel for reducing Pixel response variation. Unlike the conventional reset operation, a hard reset using a p-type MOSFET fixes the voltage of each Pixel to the same voltage. This reduces non-uniformity of the response in the linear response. The optimized cascode MOSFET achieves less variation in the logarithmic response. We have verified that the optimized Pixel shows more uniform response than the conventional Pixel, by both simulation and experiment.

  • Linear-Logarithmic CMOS Image Sensor with Reduced FPN Using Photogate and Cascode MOSFET
    'MDPI AG', 2017
    Co-Authors: Myunghan Bae, Pyung Choi, Byung-soo Choi, Sang-hwan Kim, Jimin Lee, Jangkyoo Shin
    Abstract:

    We propose a linear-logarithmic CMOS image sensor with reduced fixed pattern noise (FPN). The proposed linear-logarithmic Pixel based on a conventional 3-transistor active Pixel sensor (APS) Structure has additional circuits in which a photogate and a cascade MOSFET are integrated with the Pixel Structure in conjunction with the photodiode. To improve FPN, we applied the PMOSFET hard reset method as a reset transistor instead of NMOSFET reset normally used in APS. The proposed Pixel has been designed and fabricated using 0.18-μm 1-poly 6-metal standard CMOS process. A 120 × 240 Pixel array of test chip was divided into 2 different subsections with 60 × 240 sub-arrays, so that the proposed linear-logarithmic Pixel with reduced FPN could be compared with the conventional linear-logarithmic Pixel. We confirmed a reduction of Pixel response variation which affected image quality

  • a linear logarithmic cmos image sensor with adjustable dynamic range
    IEEE Sensors Journal, 2016
    Co-Authors: Myunghan Bae, Byoungsoo Choi, Heeho Lee, Pyung Choi, Jangkyoo Shin
    Abstract:

    A new Pixel Structure is proposed for wide dynamic range CMOS image sensors. A Pixel based on a three-transistor active Pixel sensor has two linear responses and a logarithmic response using additional circuits. The photogate surrounding the n+/p-sub photodiode exists for the second linear response. The logarithmic response is due to the biased MOS cascode. The proposed Pixel was designed and fabricated using a 0.35- $\mu \text{m}$ 2-poly 4-metal standard CMOS process. The dynamic range of the Pixel is higher than 106 dB. A test chip with a Pixel pitch of $10 \times 10~\mu \text{m}^{2}$ and a $160 \times 120$ Pixel array is evaluated.