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      KCI등재 SCOPUS

      SHVC All Intra 공간 스케일러빌리티를 위한 효율적인 모드 결정 알고리즘

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      https://www.riss.kr/link?id=A106638641

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      다국어 초록 (Multilingual Abstract)

      This paper proposes an efficient mode decision method for All Intra (AI) spatial scalability in SHVC. The proposed method can significantly reduce the encoding time by effectively reducing the number of candidate modes in the rough mode decision (RMD) step as well as the number of candidate modes in the rate-distortion optimization (RDO) step. In the RMD step, a new absolute difference of average (ADA) measure is proposed that can dramatically reduce the number of intra-modes to be examined. The proposed method uses different threshold values depending both on the direction and the CU sizes for the best tradeoff between the performance and the encoding complexity. In the RDO step, the proposed method makes use of three kinds of candidate modes, which are base-layer (BL) correlated modes, spatially correlated modes, and the candidate modes from the RMD step. By efficiently combining different kinds of candidate modes to be examined, the proposed method not only reduces the encoding complexity significantly but also shows better performance compared to other mode decision methods.
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      This paper proposes an efficient mode decision method for All Intra (AI) spatial scalability in SHVC. The proposed method can significantly reduce the encoding time by effectively reducing the number of candidate modes in the rough mode decision (RMD)...

      This paper proposes an efficient mode decision method for All Intra (AI) spatial scalability in SHVC. The proposed method can significantly reduce the encoding time by effectively reducing the number of candidate modes in the rough mode decision (RMD) step as well as the number of candidate modes in the rate-distortion optimization (RDO) step. In the RMD step, a new absolute difference of average (ADA) measure is proposed that can dramatically reduce the number of intra-modes to be examined. The proposed method uses different threshold values depending both on the direction and the CU sizes for the best tradeoff between the performance and the encoding complexity. In the RDO step, the proposed method makes use of three kinds of candidate modes, which are base-layer (BL) correlated modes, spatially correlated modes, and the candidate modes from the RMD step. By efficiently combining different kinds of candidate modes to be examined, the proposed method not only reduces the encoding complexity significantly but also shows better performance compared to other mode decision methods.

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      목차 (Table of Contents)

      • Abstract
      • 1. 서론
      • 2. Proposed Methods
      • 3. Simulation Results
      • 4. 결론
      • Abstract
      • 1. 서론
      • 2. Proposed Methods
      • 3. Simulation Results
      • 4. 결론
      • References
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      참고문헌 (Reference)

      1 G. J. Sullivan, "Standardized Extensions of High Efficiency Video Coding(HEVC)" 7 (7): 1001-1016, 2013

      2 J. Chen, "Scalable High Efficiency Video Coding Draft 3" 2013

      3 "SHVC reference software"

      4 L. Shen, "SHVC CU Processing Aided by a Feedforward Neural Network" 15 (15): 5803-5815, 2019

      5 C. C. Wang, "Recent Advances in Image and Video Coding" InTech 2016

      6 H. Schwarz, "Overview of the scalable video coding extension of the H. 264/AVC standard" 17 (17): 1103-1120, 2007

      7 G. Sullivan, "Overview of the High Efficiency Video Coding(HEVC)standard" 22 (22): 1649-1668, 2012

      8 J. Boyce, "Overview of SHVC : Scalable Extensions of the High Efficiency Video Coding Standard" 26 (26): 20-34, 2015

      9 T. Katayama, "Low-Complexity Intra Coding Algorithm in Enhancement Layer for SHVC" 2016

      10 X. Zuo, "Fast mode decision method for all intra spatial scalability in SHV" 394-397, 2014

      1 G. J. Sullivan, "Standardized Extensions of High Efficiency Video Coding(HEVC)" 7 (7): 1001-1016, 2013

      2 J. Chen, "Scalable High Efficiency Video Coding Draft 3" 2013

      3 "SHVC reference software"

      4 L. Shen, "SHVC CU Processing Aided by a Feedforward Neural Network" 15 (15): 5803-5815, 2019

      5 C. C. Wang, "Recent Advances in Image and Video Coding" InTech 2016

      6 H. Schwarz, "Overview of the scalable video coding extension of the H. 264/AVC standard" 17 (17): 1103-1120, 2007

      7 G. Sullivan, "Overview of the High Efficiency Video Coding(HEVC)standard" 22 (22): 1649-1668, 2012

      8 J. Boyce, "Overview of SHVC : Scalable Extensions of the High Efficiency Video Coding Standard" 26 (26): 20-34, 2015

      9 T. Katayama, "Low-Complexity Intra Coding Algorithm in Enhancement Layer for SHVC" 2016

      10 X. Zuo, "Fast mode decision method for all intra spatial scalability in SHV" 394-397, 2014

      11 G. Zhu, "Fast enhancement layer intra coding based on inter-channel correlations and TU depth correlation in SHVC" 50-53, 2016

      12 D. Wang, "Fast Mode and Depth Decision Algorithm for Intra Prediction of Quality SHVC" 2014

      13 Q. Li, "Fast CU Size Decision and PU Mode Decision Algorithm for Quality SHVC Inter Coding" 78 (78): 7819-7839, 2019

      14 H. R. Tohidypour, "Content adaptive complexity reduction scheme for quality/fidelity scalable HEVC" 2013

      15 V. Seregin, "Common SHM test conditions and software reference configurations" 2014

      16 G. Bjøntegaard, "Calculation of average PSNR differences between RD-curves" 2001

      17 X. Li, "An effective CU size decision method for quality scalability in SHVC" 76 (76): 8011-8030, 2017

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2007-01-01 평가 학술지 통합 (기타) KCI등재
      2001-01-01 평가 등재학술지 유지 (등재유지) KCI등재
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.27 0.27 0.24
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.21 0.19 0.366 0.08
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