• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.143-144
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• 2020

VVC (Versatile Video Coding)는 HEVC이후 차세대 표준 비디오 코딩으로 JVET(Joint Video Exploration)에 의해 2018년 표준화를 시작하였다. VVC에는 복원픽쳐의 변환-양자화에러에 의해 발생한 블로어, 블로킹, 링잉 아티팩트를 감소시키기 위하여 deblocking filter (DF), sample adaptive offset (SAO), adaptive loop filter(ALF)와 같은 모듈을 사용한다. 한편 CNN (Convolutional Neural Network)은 최근 이미지와 비디오 복원에 높은 성능을 보이고 있다. VVC에서 픽쳐는 CTU (Coding Tree Unit)으로 분할되고 각 CTU는 다시 CU (Coding Unit)으로 분할된다. 그리고 인코딩을 위한 중요한 정보들이 Picture, CTU, CU단위로 디코더에 전송된다. 이 논문에서는 화면 간 예측으로 인코딩 된 픽처에서 블록과 픽처정보를 이용한 딥러닝 기반의 인루프 필터 모델을 제안한다. 제안하는 모델은 화면 간 예측에서 QP, 4×4 블록단위의 모션벡터, 참조블록과의 시간적거리, CU의 깊이를 모델에 추가적인 정보로 이용한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.311-312
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• 2021

최근 VVC(Versatile Video Coding) 표준 완료 이후 JVET(Joint Video Experts Team)은 NNVC(Neural Network-based Video Coding) AhG(Ad-hoc Group)을 구성하고 인공지능을 이용한 비디오 압축 기술들을 탐색하고 있다. 본 논문에서는 VVC 복원 영상의 DCT 계수를 기반으로 복원 영상을 분류하고, 분류된 각 클래스에 따라 적응적으로 CNN(Convolutional Neural Network) 기반의 화질 개선을 수행하는 VVC 후처리 기법을 제안한다. 실험결과, 제안기법은 AI(All Intra) 부호화 모드에서 1.23% BD-rate 이득을 보였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1236-1238
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• 2022

JVET 은 최신 비디오 부호화 표준인 VVC(Versatile Video Coding) 표준화를 완료한 후, VVC 보다 더 높은 압축 성능을 가지는 새로운 표준기술 탐색을 진행하고 있으며, 이를 위하여 참조 소프트웨어 ECM(Enhanced Compression Model)을 개발하고 있다. 현재 ECM4.0 에는 다양한 후보 구성 및 예측 성능 개선 기법을 추가하여 기존 VVC 의 GPM(Geometric Partitioning Mode)을 확장한 GPM-MMVD(GPM with merge MV differences), GPM-TM(GPM with template matching) 등을 채택하고 있다. 본 논문에서는 ECM 에 채택된 확장된 GPM 기술들의 각 기술 별 선택 빈도를 분석하고 이를 바탕으로 보다 효율적인 GPM 확장 모드 시그널링 방식을 제안한다. 또한 후보 탐색 알고리즘을 간소화한 복잡도 감소 기법을 제시한다. 실험결과 제안하는 시그널링 기법은 ECM4.0 대비 Y와 Cb, Cr 에서 각각 0.02%, 0.16%, 0.09% BD-rate 부호화 성능 향상을 보였고 GPM 인덱스 탐색 간소화 기법은 ECM4.0 대비 Y 와 Cr 에서 각각 0.02%, 0.18% BD-rate 부호화 성능 향상을 보였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1239-1240
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• 2022

JVET 은 VVC(Versatile Video Coding) 표준화 완료 이후 보다 높은 압축 성능을 갖는 차세대 비디오 코덱의 표준 기술을 탐색하고 있으며 ECM(Enhanced Compression Model) 참조 소프트웨어를 통해 제안된 알고리즘의 성능을 검증하고 있다. 현재 ECM 에서는 정해진 순서에 의해 병합(Merge) 후보를 구성하고 템플릿 매칭(template matching)을 통하여 후보들의 순서를 재배열하는 ARMC(Adaptive Reordering of Merge Candidate) 기법을 채택하고 있다. 본 논문은 ARMC 의 병합 후보의 선택 빈도 분석을 바탕으로 정규 병합(regular merge) 후보 수를 확장하여 구성하고, 실제 탐색에 사용되는 최종 후보의 수를 제한하는 효율적인 ARMC 후보 구성 기법을 제안한다. 실험결과 ECM 4.0 대비 Cb 와 Cr 에서 0.12%, 0.19% 비디오 부호화 성능을 확인하였다.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.313-324
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• 2020

In this paper, we propose a motion vector prediction method that increases the coding efficiency at the boundary of an image by utilizing the 360 video characteristic. In the current VVC method, the location of a neighbor block is excluded from the candidate list for inter prediction in case that it is out of boundary. This can reduce coding efficiency as well as subject quality. To solve this problem, we construct new candidates adding the location of the neighbor block at the boundary of the picture from already decoded information based on the projection method for 360 video coding. To evaluate the performance of the proposed method, we compare with VTM6.0 and 360Lib9.1 under Random Access condition of JVET-360 CTC. As a result, the coding performance shows a BD-rate reduction of 0.02% on average in luma component and 0.05%, 0.06% on average in chroma components respectively, without additional computational complexity. The coding performance at the picture boundary shows a BD-rate reduction of 0.29% on average in luma component and 0.45%, 0.43% on average in chroma components, respectively. Furthermore, we perform subjective quality test with the DSCQS method and obtain MOS values. The MOS value is improved by 0.03 value, and we calculate BD-MOS using MOS value and bit-rate. As a result, the proposed method improved performance by up to 8.78% and 5.18% on average.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.136-139
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• 2017

Recently, many companies and consumers has shown a lot of interest toward VR(Virtual Reality), so many VR devices such as HMD(Head mounted Display) and 360 degree VR camera are released on the market. Current encoded 360 degree VR video uses the codec which originally made for the conventional 2D video. Therefore, the compression efficiency isn't optimized because the en/decoder does not consider the characteristics of the 360 degree VR video. In this paper, we propose a method to improve the compression efficiency by using the reference frame which compensates for the distortions caused by characteristics the 360 degree VR video. Applying the proposed method we were able to increase the compression efficiency by providing better prediction.

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.147-158
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• 2021

Versatile Video Coding (VVC) is the latest video coding standard developed by Joint Video Exploration Team (JVET). In VVC, the quadtree plus multi-type tree (QT+MTT) structure of coding unit (CU) partition is adopted, and its computational complexity is considerably high due to the brute-force search for recursive rate-distortion (RD) optimization. In this paper, we aim to reduce the time complexity of inter-picture prediction mode since the inter prediction accounts for a large portion of the total encoding time. The problem can be defined as classifying the split mode of each CU. To classify the split mode effectively, a novel convolutional neural network (CNN) called multi-level tree (MLT-CNN) architecture is introduced. For boosting classification performance, we utilize additional information including inter-picture information while training the CNN. The overall algorithm including the MLT-CNN inference process is implemented on VVC Test Model (VTM) 11.0. The CUs of size 128×128 can be the inputs of the CNN. The sequences are encoded at the random access (RA) configuration with five QP values {22, 27, 32, 37, 42}. The experimental results show that the proposed algorithm can reduce the computational complexity by 11.53% on average, and 26.14% for the maximum with an average 1.01% of the increase in Bjøntegaard delta bit rate (BDBR). Especially, the proposed method shows higher performance on the sequences of the A and B classes, reducing 9.81%~26.14% of encoding time with 0.95%~3.28% of the BDBR increase.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.109-112
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• 2020

VVC uses 67 modes in intra prediction. Most probable mode (MPM) is used to reduce data for the representation of intra prediction mode. If the mode to send exists in the MPM candidate, the index of the MPM list is transmitted. If it does not exist in the MPM candidate, TBC encoding is applied. When TBC is applied in intra prediction, three are selected in order of low number mode and coded into 5 bits. The remaining modes except the mode encoded by 5 bits are encoded by 6 bits. In this paper, we examine the limitations of the TBC used in VVC intra prediction and propose an adaptive method that can encode more efficiently than conventional methods when using TBC in intra prediction. As a result, the coding efficiency of the overall coding performance is 0.01% and 0.04% in AI and RA, respectively, compared with the conventional coding method.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.397-400
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• 2017

Recently, a lot of images containing various global movements have been generated by the activation of the photographic equipment such as the drone and the action cam. In this case, when the motion such as rotation, scaling is generated, it is difficult to expect a high coding efficiency in the conventional inter-picture prediction method using the 2D motion vector. In this paper, we propose a video coding method that reflects global motion through homography reference pictures. As a proposed method, there are 1) a method of generating a new reference picture by grasping a global motion relation between a current picture and a reference picture by homography, and 2) a method of utilizing a homography reference picture for inter-picture prediction. The experiment was applied to the HEVC reference software HM 14.0, and the experimental result showed an increase in encoding efficiency of 6.6% based on RA. Especially, the results using the videos with rotational motion have a maximum coding efficiency of 32.6%, which is expected to show high efficiency in video, which is often represented by complex global motion such as drones.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.41-47
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• 2019

Recently, enhanced methods on the inter merging have been being investigated in Versatile Video Coding (VVC) standardization which will be a next generation video coding standard with capability beyond the High Efficiency Video Coding (HEVC). If there is not enough motion information available in the neighboring blocks in the merge mode, zero motion candidate is inserted into the merge candidate list, which could make the coding efficiency decreased. In this paper, we propose an efficient method of constructing the merge mode candidate list to reduce the case that the zero motion is used as a candidate by generating an alternative merge candidate. Experimental results show that the proposed method gives the average BD-rate gain of 0.2% with the decoding time increase of 3% in the comparison with VTM 1.0.