• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.62-69
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• 2015

In this paper, a new frame rate up conversion (FRUC) algorithm using adaptive motion estimation (AME-FRUC) is proposed. The proposed algorithm performs extended bilateral motion estimation (EBME) conducts motion estimation (ME) processes on the static region, and extract region of interest with the motion vector (MV). In the region of interest block, the proposed AME-FRUC uses the texture block partitioning scheme and the unilateral motion estimation for improving ME accuracy. Finally, motion compensated frame interpolation (MCFI) are adopted to interpolate the intermediate frame in which MCFI is employed adaptively based on ME scheme. Experimental results show that the proposed algorithm improves the PSNR up to 3dB, the SSIM up to 0.07 and 68% lower SAD calculations compared to the EBME and the conventional FRUC algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.2
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• pp.355-363
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• 2011

Recently, as one of several methods to improve the performance of DVC(Distributed Video Coding) system, many research works are focusing on the iterative refinement of side information. Most of the conventional techniques are mainly based on the relationship between the reconstruction level and side information, or the vector median filtering of motion vectors, but, their performance improvements are restricted. In order to overcome the performance limit of the conventional schemes, in this paper, a side information generation scheme is designed by measuring the block-cost estimation. Then, by adaptively selecting the compensation mode using the received bit-plane information, we propose a block-adaptive iterative refinement which is efficient for non-symmetric moving objects. Computer simulations show that, by using the proposed refinement method, the performance can be improved up to 0.2 dB in rate-distortion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1378-1387
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• 2013

Histogram equalization, which stretches the dynamic range of intensity, is the most common method for enhancing the contrast of image. Contrast limited adaptive histogram equalization(CLAHE), proposed by K. Zuierveld, has two key parameters: block size and clip limit. These parameters mainly control image quality, but have been heuristically determined by user. In this paper, we propose a novel method of determining two parameters of CLAHE using entropy of image. The key idea is based on the characteristics of entropy curves: clip limit vs entropy and block size vs entropy. Clip limit and block size are determined at the point with maximum curvature on entropy curve. Experimental results show that the proposed method improves images with very low contrast.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.332-340
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• 2022

Recently, with the development of deep learning and artificial neural network technologies, research on the application of neural network has been actively conducted in the field of video coding. In particular, deep learning-based intra prediction is being studied as a way to overcome the performance limitations of the existing intra prediction techniques. This paper presents a method of context-adaptive neural network-based intra prediction model training and its coding performance analysis. In other words, in this paper, we implement and train a known intra prediction model based on convolutional neural network (CNN) that predicts a current block using contextual information from reference blocks. Then, we integrate the trained model into HM16.19 as an additional intra prediction mode and evaluate the coding performance of the trained model. Experimental results show that the trained model gives 0.28% BD-rate bit saving over HEVC in All Intra (AI) coding mode. In addition, the coding performance change of training considering block partition is also presented.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.347-350
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• 2003

In this paper, a new automated defects detection method for a TFT-LCD panel is presented. An input image is preprocessed to lessen small abnormal noises and non-uniformity of the image. The adaptive multi-thresholds are used to detect Muras, which are the major defects occurred on TFT-LCD panels. Those are determined adaptively depending on the brightness and the brightness distribution of a local block. For the synthetic images and real Mura images, the proposed algorithm can effectively detect Muras in a reasonable time.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.114-115
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• 2019

This paper introduces an adaptive scalar quantization scheme for video coding technology. The method utilizes the property of the coefficient groups (CG) inside each transform block so that the dead-zone interval of the scalar quantizer is adaptively set up for different CGs. Its experimental results show that our proposed quantization scheme can achieve BDBR reduction of 4.75%, 5.93, and 5.16% for Y, Cb, and Cr channel respectively when encoding with HEVC.

• ETRI Journal
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• v.42 no.1
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• pp.26-35
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• 2020

Herein, we consider uplink multiuser massive multiple-input multiple-output systems when multiple users transmit information symbols to a base station (BS) by applying simple space-time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd-indexed symbols and the other for even-indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed-form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance-based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady-state bit error rate than the conventional scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.755-764
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• 1999

In this study, the system level network simulation is considered with adaptive array antenna in CDMA mobile communication system. A network simulation framework is implemented based on IS-95A/B system to consider dynamic handoff, system level network behavior, and deploying strategy into the overall CDMA mobile communication network under adaptive array algorithm. Its simulation model, such as vector channel model, adaptive beam forming antenna model, handoff model, and power control model, are described in detail with simulation block. In order to maximize SINR of received signal at antenna, maximin algorithm is particularly considered, and it is computed at each simulation snap shot with SINR based power control and handoff algorithm. Graphic user interface in this system level network simulator is also implemented to define the simulation environments and to represent simulation results on real mapping system. This paper also shows some features of simulation framework and simulation results.

• Journal of the Korean Institute of Telematics and Electronics
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• v.15 no.3
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• pp.1-6
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• 1978

This paper deals with speech digitization and bandwidth compression techniques, particularly two predictive coding methods-namely, adaptive diferentia1 pulse code modulation(ADPCM) and adaptive delta modulation (ADM). The principle of a typical adoptive quantizer that is used in ADPCM is explained, and two analysis methods for the adaptive predictor coefficents, block and sequential analyses, are discussed. Also, three companding methods (instantaneous, syllabic, and hybrid companding) that are used in ADM are explained in detail, and their performances are compared. In addition, the performances of ADPCM and ADM as speech coders are compared, and the merits of each coder are discussed.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.51-57
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• 2020

For the purpose of development of anti-jamming GPS receiver we have developed an anti-jamming algorithm and its Simulink implementation model. The algorithm used here is a form of Space-Time Adaptive Processing (STAP) filter which is well known as an effective way to remove wideband jamming signals. We have chosen Minimum Variance Distortionless Response (MVDR) block-adaptive beamforming algorithm for our development since it can provide relatively fast convergence speed to reach optimal weights, stable and high suppression capability on various types of jamming signals. We will show modeling results for this MVDR type adaptive beamformer and some simulation results. We also show the integrity of the demodulated satellite signals and the accuracy of resulting navigation solutions after anti-jamming operation.