• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.246-249
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• 2016

본 논문에서는 화면 내 블록 카피 (IntraBC: Intra Block Copy) 예측 기술의 압축 성능 분석과 향상된 해쉬 기법을 통한 HEVC (High Efficiency Video Coding) 스크린 콘텐츠 코딩 성능 기법을 제안한다. 현재 SCM (Screen Content Coding Test Model) 에 채택 된 화면 내 블록 카피 기술에서는 $16{\times}16$ 블록에는 1차원 탐색을 수행하고 $8{\times}8$블록에서는 해쉬기반 전역 탐색을 수행하여 해쉬가 일치하는 블록들과 RD-Cost를 수행한다. 현재의 해쉬기반 전역탐색에는 기울기 (Gradient) 위주의 해쉬 구성으로 인해 해쉬가 고르게 분포하지 않아, RD-Cost 수행횟수가 과도하게 많아지는 문제가 있다. 제안하는 방법은 전역적 화면 내 블록 카피의 해쉬 구성 방법을 개선함으로써, 기존 SCM-6.1 대비 0.46%의 BDBR 향상을 확인하였다.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.140-148
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• 2016

HEVC(High Efficient Video Coding) has twice times better compression ratio than H.264/AVC, but since the computational complexity has significantly increased in the encoder side, it may cause difficulty in real-time SW implementation in the encoder side. This paper proposes two methods about fast intra prediction. First, fast mode and prediction unit decision method using transform coefficients of the original block is proposed. and second, fast prediction unit decision method using coded block flag(cbf) is proposed. The proposed method achieves 42% encoder speed up with 0.8% bitrate increase compared with HM16.0.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1134-1142
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• 2019

Detection of double compression is one of the most efficient ways of remarking the validity of videos. Many methods have been introduced to detect HEVC double compression with different coding parameters. However, HEVC double compression detection under the same coding environments is still a challenging task in video forensic. In this paper, we introduce a novel method based on the frame partitioning information in intra prediction mode for detecting double compression in with the same coding environments. We propose to extract statistical feature and Deep Convolution Neural Network (DCNN) feature from the difference of partitioning picture including Coding Unit (CU) and Transform Unit (TU) information. Finally, a softmax layer is integrated to perform the classification of the videos into single and double compression by combing the statistical and the DCNN features. Experimental results show the effectiveness of the statistical and the DCNN features with an average accuracy of 87.5% for WVGA and 84.1% for HD dataset.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.340-347
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• 2015

HEVC (High Efficiency Video Coding) achieves high coding efficiency by employing a quadtree-based coding unit (CU) block partitioning structure and various prediction units (PUs), and the determination of the best CU partition structure and the best PU mode based on rate-distortion (R-D) cost. However, the computation complexity of encoding also dramatically increases. In this paper, to reduce such encoding computational complexity, we propose three fast PU mode decision methods based on encoding information of upper depth as follows. In the first method, the search of PU mode of the current CU is early terminated based on the sub-CBF (Coded Block Flag) of upper depth. In the second method, the search of intra prediction modes of PU in the current CU is skipped based on the sub-Intra R-D cost of upper depth. In the last method, the search of intra prediction modes of PU in the lower depth's CUs is skipped based on the sub-CBF of the current depth's CU. Experimental results show that the three proposed methods reduce the computational complexity of HM 14.0 to 31.4%, 2.5%, and 23.4% with BD-rate increase of 1.2%, 0.11%, and 0.9%, respectively. The three methods can be applied in a combined way to be applied to both of inter prediction and intra prediction, which results in the complexity reduction of 34.2% with 1.9% BD-rate increase.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.159-160
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• 2013

동영상 압축 표준 기술인 HEVC(High Efficiency Video Coding) 는 ITU-T와 ISO/IEC 의 VCEG과 MPEG 의 공동으로 표준화를 진행중이다. 최근 표준의 확장기술에 해당하는 방법으로 Range Extension을 표준화 중에 있으며, 기존에 존재하는 RDPCM에서 재차 잔차신호를 줄이는 방법으로 CRDPCM 방법을 제안한다. 제안하는 방법은 손실 압축에 해당하며 실험 결과에 따르면 약 0.7%의 성능 향상을 가진다.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.353-361
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• 2020

VVC (Versatile Video Coding) is a new video compression technique that is being standardized, and it supports HD / UHD / 8K video, and High Dynamic Range (HDR) video with a goal of approximately 2 times higher coding efficiency than the conventional HEVC. It also aims to support a variety of functionalities such as screen content coding, adaptive resolution changes, and independent sub-pictures. In this paper, we investigate the signaling process of intra prediction mode first, and develop an effective coding method of the chroma intra prediction mode. In case of the DM mode, the proposed method simplifies the prediction mode of the chorma intra prediction mode when referring to the angular mode of the luminance block. It can improve coding efficiency of the chroma intra prediction mode, and the proposed process can also consider the size of the block in order to further improve its coding efficiency.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.278-279
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• 2013

최근에 완료된 HEVC(High Efficiency Video Coding) 비디오 압축 표준은 H.264/AVC에 비해 2배 이상 향상된 압축 효율을 제공한다. 현재 진행 중인 HEVC 확장 (extension) 작업에서는 손실 및 무손실 부호화에서 4:2:2 및 4:4:4 색차 포맷과 최대 12비트 깊이를 지원하는 고급 프로파일을 개발하고 있다. 현재까지 개발된 HEVC의 CABAC(Context-based Adaptive Binary Arithmetic Coding)은 손실 부호화 환경에 적합하게 설계되었기 때문에 무손실 부호화 환경에서 최적의 부호화 성능을 제공하지 못한다. 본 논문에서는 4:4:4 색차 포맷 영상의 무손실 화면내 부호화 환경에서 잔여 신호의 통계적 특성을 고려한 향상된 CABAC 잔여 데이터 부호화 방법을 제안한다. 실험 결과를 통해, 본 논문에서 제안하는 향상된 CABAC 방법이 무손실 화면내 부호화에서 기존의 CABAC 방법에 비해 평균 약 2.41% 의 비트 수를 감소시키는 것을 확인했다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.71-74
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• 2013

차세대 동영상 표준 코덱인 High Efficiency Video Coding(HEVC)은 기존의 AVC/H.264 보다 동일 화질 대비 최대 약 2배의 압축 성능을 보여준다. 이러한 HEVC의 성능을 얻기 위하여 복잡한 연산이 많은 기법이 도입되었고 이로 인하여 HEVC의 시간 복잡도는 AVC/H.264보다 더욱 증가하였다. HEVC의 시간 복잡도를 줄이기 위해서 다양한 고속 알고리즘이 논의되고 있고 인트라 예측 모드에서의 고속 알고리즘 연구 또한 많은 연구가 이루어지고 있다. 본 논문에서는 인트라 예측 모드 결정과정에서 HEVC에 구현된 Rough mode decision(RMD)와 Most probable mode(MPM)의 결과를 활용하여 고속화된 최종예측 모드 결정 방법을 제안한다. 실험 결과, HM 10.0의 All Intra 환경을 기준으로 BD-rate에서 약 0.9%의 손실과 함께 평균 24%의 속도 향상을 얻을 수 있었다.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.422-433
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• 2015

In this paper, we demonstrate inter-layer prediction tools for scalable video coders. The proposed scalable coder is designed to support not only spatial, quality and temporal scalabilities, but also view scalability. In addition, we propose quad-tree inter-layer prediction tools to improve coding efficiency at enhancement layers. The proposed inter-layer prediction tools generate texture prediction signal with exploiting texture, syntaxes, and residual information from a reference layer. Furthermore, the tools can be used with inter and intra prediction blocks within a large coding unit. The proposed framework guarantees the rate distortion performance for a base layer because it does not have any compulsion such as constraint intra prediction. According to experiments, the framework supports the spatial scalable functionality with about 18.6%, 18.5% and 25.2% overhead bits against to the single layer coding. The proposed inter-layer prediction tool in multi-loop decoding design framework enables to achieve coding gains of 14.0%, 5.1%, and 12.1% in BD-Bitrate at the enhancement layer, compared to a single layer HEVC for all-intra, low-delay, and random access cases, respectively. For the single-loop decoding design, the proposed quad-tree inter-layer prediction can achieve 14.0%, 3.7%, and 9.8% bit saving.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.115-125
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• 2018

This paper presents a fast partition decision framework for High Efficiency Video Coding (HEVC) Screen Content Coding (SCC) based on machine learning. Currently, the HEVC performs quad-tree block partitioning process to achieve optimal coding efficiency. Since this process requires a high computational complexity of the encoding device, the fast encoding process has been studied as determining the block structure early. However, in the case of the screen content video coding, it is difficult to apply the conventional early partition decision method because it shows different partition characteristics from natural content. The proposed method solves the problem by classifying the screen content blocks after partition decision, and it shows an increase of 3.11% BD-BR and 42% time reduction compared to the SCC common test condition.