• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1998년도 Proceedings of International Workshop on Advanced Image Technology
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• pp.177-182
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• 1998

In this paper, we propose a lossless motion video coding method using motion compensation. For realtime coding and transmission, we developed a lossless video codec based on the proposed method. It was confirmed the codec functions normally in an experiment involving coding and transmitting through an actual ATM network. Furthermore, we proposed a lossless coding method with bit-plane expansion under a constant bitrate. Two approaches, a closed bit-plane approach and a merged bit-plane approach, are considered and characteristics of their compression efficiency are estimated. Simulation results show that the proposed method is suitable for lossless video coding with bitrate control.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2002년도 정기총회 및 학술대회
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• pp.173-176
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• 2002

This paper proposes a new approach for digital watermarking and secure copyright protection of video. the principal aim being to discourage illicit copying and distribution of copyrighted material. The method presented here is based on the three dimensional discrete wavelet transform of video scene. The watermark is a copyright information encoded in the form of a spread spectrum signal to ensure the system security and is embedded in the 3D DWT magnitude of video chunks. The performance of the presented technique is evaluated experimentally.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2011년도 추계학술대회
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• pp.143-146
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• 2011

This paper presents human perception-based video coding method using an online learning framework. In this work, we analyze the relationship between human attention regions and video quality, and also consider human memory. We classify the motion patterns based on the analysis. Then, we devise a motion pattern classification method using Hedge algorithm. Along with the motion patterns, we smooth out the specific regions or sharpen details of the regions using the regional priorities. The preprocessed sequences are applied to the video codec. The performance is excellent on the overall quality as well as the regional quality.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2011년도 추계학술대회
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• pp.288-291
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• 2011

Video stabilization is an important image enhancement widely used in surveillance system in order to improve recognition performance. Most previous methods calculate inter-frame homography to estimate global motion. These methods are relatively slow and suffer from significant depth variations or multiple moving object. In this paper, we propose a fast and practical approach for video stabilization that selects the most reliable key frame as a reference frame to a current frame. We use optical flow to estimate global motion within an adaptively selected region of interest in static camera environment. Optimal global motion is found by probabilistic voting in the space of optical flow. Experiments show that our method can perform real-time video stabilization validated by stabilized images and remarkable reduction of mean color difference between stabilized frames.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2015년도 추계학술대회
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• pp.147-148
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• 2015

This paper proposes a tile level rate control for High Efficiency Video Coding (HEVC). The proposed tile level rate control is designed by considering the multi-core platform of tile in HEVC. The proposed tile level rate control allocates the number of bits for each tile based on the predetermined weight generated from the current picture level rate control. According to the experimental results, the proposed tile level rate control for HEVC on multi-core platform loses negligibly the bitrate accuracy about 0.07% on average over the reference software HM-14.0.

• 방송공학회논문지
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• 제13권1호
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• pp.17-24
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• 2008

물리 계층과 응용 계층 사이의 상호 계층 최적화에 대한 많은 연구들이 진행되고 있다. 그 예로 H.264/AVC의 SVC (Scalable Video Coding)와 같이 다중 스트림 비디오 방식들이 제안되고 있다. 이러한 물리 계층과 응용 계층 사이의 상호 계층 최적화에 대한 노력들에 비해서 그 중간 계층인 세션 계층에서의 노력은 미비한 상태이다. 이에 대해서 본 논문은 다중 스트림 비디오 방식들을 지원하기 위한 IP Multimedia Subsystem 기반 하에서 세션 제어 방법을 제안하고자 한다.

• 방송공학회논문지
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• 제12권6호
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• pp.624-629
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• 2007

While single view video coding uses the temporal prediction scheme, multi-view video coding (MVC) applies both temporal and inter-view prediction schemes. Thus, the key problem of MVC is how to reduce the inter-view redundancy efficiently, because various existing video coding schemes have already provided solutions to reduce the temporal correlation. In this paper, we propose a global disparity compensation scheme which increases the inter-view correlation and a new inter-view prediction structure based on the global disparity compensation. By experiment, we demonstrate that the proposed global disparity compensation scheme is less sensitive to change of the search range. In addition, the new Inter-view prediction structure achieved about $0.1{\sim}0.3dB$ quality improvement compared to the reference software.

• 방송공학회논문지
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• 제24권2호
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• pp.292-298
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• 2019

본 논문에서는 클라우드 서버와 영상 품질 향상 알고리즘을 이용하여 고화질의 영상을 서비스하는 방법을 소개한다. 즉, 논문에서 제안하는 ViVa (Video Value Addition)의 개념을 바탕으로 저화질 영상을 서비스하는데 필요한 전송 비트레이트와 계산량으로 고화질의 영상을 서비스함으로써 기존 스트리밍 서비스 대비 향상된 시스템을 제안한다.

• 방송공학회논문지
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• 제27권7호
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• pp.985-998
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• 2022

Even after the standardization of VVC completed in 2020, continuing efforts for developing even better video coding technology are still under way. In this context, the Joint Video Experts Group (JVET) is developing various video compression technologies under the name of enhanced compression beyond VVC capability which has reported BDBR gain of -6.75%, -14.05%, and -15.25% on its test model, ECM version 5.0, respectively in Y, Cb, and Cr channels by just having a few new or improved intra coding tools. The current activity has so far adopted 11 intra coding tools beyond VVC which can generate more sophisticated predictors, reduce signaling overhead, or combine various predictors. In this tutorial paper, we will review these techniques.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2022년도 추계학술대회
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• pp.8-9
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• 2022

최근 VVC(Versatile Video Coding) 표준 완료 이후 JVET(Joint Video Experts Team)에서는 NNVC(Neural Network-based Video Coding) EE(Exploration Experiment)를 통하여 화면내 예측을 포함한 신경망 기반의 부호화 기술들을 탐색하고 검증하고 있다. 본 논문에서는 VVC 에 채택되어 있는 다중 변환 선택(MTS: Multiple Transform Selection)에 따라서 적절한 예측 블록을 선택할 수 있는 TDIP(Transform-Dependent Intra Prediction) 모델을 제안한다. 실험결과 제안기법은 VVC 의 AI(All Intra) 부호화 환경에서 VTM(VVC Test Model) 대비 Y, U, V 에 각각 0.87%, 0.87%, 0.99%의 BD-rate 절감의 비디오 부호화 성능 향상을 보였다.