• ETRI Journal
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• v.42 no.2
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• pp.258-271
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• 2020

A correlation exists between luminance samples and chrominance samples of a color image. It is beneficial to exploit such interchannel redundancy for color image compression. We propose an algorithm that predicts chrominance components Cb and Cr from the luminance component Y. The prediction model is trained by supervised learning with Laplacian-regularized least squares to minimize the total prediction error. Kernel principal component analysis mapping, which reduces computational complexity, is implemented on the same point set at both the encoder and decoder to ensure that predictions are identical at both the ends without signaling extra location information. In addition, chrominance subsampling and entropy coding for model parameters are adopted to further reduce the bit rate. Finally, luminance information and model parameters are stored for image reconstruction. Experimental results show the performance superiority of the proposed algorithm over its predecessor and JPEG, and even over JPEG-XR. The compensation version with the chrominance difference of the proposed algorithm performs close to and even better than JPEG2000 in some cases.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.167-170
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• 2002

We have proposed new pixel structures for Active Matrix OELD (AMOELD) to improve the uniformity of luminance and manufactured a full-color 3.6-inch QVGA AMOELD. The proposed pixel structures, composed of four TFTs and one capacitor, can display 64 gray scales by compensating threshold voltage (Vth) variation of driving TFTs. Nonuniformity and peak intensity of measured luminance are under 14% and over $200cd/m^2$, respectively.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.705-708
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• 2000

일반적인 LCD의 색 재현 특성은 입력 디지털 값이 낮을수록 gray scale의 상관색온도가 상승하여 정확한 색 재현이 불가능하다. 본 논문에서는 LCD의 입력 디지털 값의 변화에 따른 특성을 조사하고, luminance, contrast 비 등의 특성에 열화없이 gray scale의 입력 잘 변화에 따른 상관색온도의 변화를 보정하기 위해서 입력 디지털 값을 조정하는 새로운 LUT를 제안하였다.

• 한국정보디스플레이학회:학술대회논문집
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• 2008.10a
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• pp.473-476
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• 2008

A simple voltage compensation pixel circuit for AMOLED is produced using low temperature polycrystalline silicon (LTPS) technology. Its operation is verified by AIM-SPICE. Simulation results show that the pixel circuit has high immunity to variation of LTPS-TFT and reduces the drop in luminance due to the degradation of the OLED.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.54-55
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• 2017

VR영상은 하나의 카메라가 아닌 여러 대의 카메라로 촬영한 영상을 이어 붙여 만든다. 각각의 카메라로 촬영된 영상은 FOV에서 광원이 서로 다르기 때문에 각 영상의 밝기는 서로 일치하지 않는다. 이러한 밝기 차이는 각 영상을 하나의 VR 영상으로 스티칭 하였을 때 더욱 이질적으로 느껴진다. 본 논문에서는 각각의 카메라 영상이 서로 다른 광원에 의하여 밝기 차이가 발생하였을 때 이를 보상하기 위한 알고리즘을 제안한다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.124-130
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• 1996

A compensation method of color error resulting from dynamic range transformation of color image is propsoed. The color error is measured using the CIE L a b uniform color space, and the color image is compensated to minimize it. The color error is significant in the dark region of image, which is caused by the lunimance scaling factor is relatively large in that case. In the proposed method, we weight the luminance scaling factor corresponding to luminnce to minimize the error. Because the weighting factor depends on luminace distribution of image, a decisio method of weighting factor using histogram is also proposed.

• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.133-140
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• 2020

This study proposes a method of blending visible and near infrared images to enhance edge details and local contrast. The proposed method consists of radiance map generation and color compensation. The radiance map is produced by a Laplacian pyramid and a soft mixing method based on principal component analysis. The color compensation method uses the ratio between the composed radiance map and the luminance channel of a visible image to preserve the visible image chrominance. The proposed method has better edge details compared to a conventional visible and NIR image blending method.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.812-815
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• 2022

Images displayed on a digital devices under the sunlight are generally perceived to be darker than the original images, which leads to a decrease in visibility. For better visibility, global luminance compensation or tone mapping adaptive to ambient lighting is required. However, the existing methods have limitations in chrominance compensation and are difficult to use in real world due to their heavy computational cost. To solve these problems, this paper propose a piece-wise linear curves (PLECs)-based image enhancement method to improve both luminance and chrominance. At this time, PLECs are regressed through deep learning and implemented in the form of a lookup table to real-time operation. Experimental results show that the proposed method has better visibility compared to the original image with low computational cost.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.51-60
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• 2024

Aiming at the problem of low contrast and difficult to recognize video images in low-light environment, we propose an adaptive contrast compensation enhancement algorithm based on human visual perception. First of all, the video image characteristic factors in low-light environment are extracted: AL (average luminance), ABWF (average bandwidth factor), and the mathematical model of human visual CRC(contrast resolution compensation) is established according to the difference of the original image's grayscale/chromaticity level, and the proportion of the three primary colors of the true color is compensated by the integral, respectively. Then, when the degree of compensation is lower than the bright vision precisely distinguishable difference, the compensation threshold is set to linearly compensate the bright vision to the full bandwidth. Finally, the automatic optimization model of the compensation ratio coefficient is established by combining the subjective image quality evaluation and the image characteristic factor. The experimental test results show that the video image adaptive enhancement algorithm has good enhancement effect, good real-time performance, can effectively mine the dark vision information, and can be widely used in different scenes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.191-194
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• 2009

본 논문에서는 효율적인 다시점 비디오 부호화를 위해 히스토그램(histogram)을 이용한 다시점 비디오의 휘도(luminance)와 색차(chrominance)성분 보상 기법을 제안한다. 다시점 비디오는 카메라의 기하학적인 위치 차이와 여러 대의 카메라가 동일한 특성을 가지도록 완벽히 조정되지 못함으로 인해 동일한 시간대에 촬영된 인접한 시점 영상 간에 휘도와 색상의 차이가 발생할 수 있다. 이러한 특성은 인접한 카메라로부터 획득된 영상을 참조하여 시점간 움직임 예측 시에 오정합의 원인이 되어 부호화 효율을 떨어뜨리게 된다. 본 논문에서는 효율적인 다시점 비디오 부호화를 위해 시점간의 히스토그램을 비교하여 정합하는 휘도 및 색차 보상 기법을 수행한다. 일정한 시간 대역(time interval)에서 다시점 비디오의 평균 누적 히스토그램을 이용하여 참조 영상을 생성하고 각 시점별로 정합 함수를 통해 다시점 영상 간의 휘도와 색상의 불일치성을 보상한다. 제안하는 조명 보상 기법을 통하여 다시점 비디오 부호화 효율을 높일 수 있었다.