最新的多功能視訊編碼(H.266/VVC)國際標準提供比其前一代高效率視訊編碼(H.265/HEVC)國際標準更佳的編碼效率。H.266/VVC中的四元樹/巢狀多類型樹分割結構與編碼工具大量增加編碼時間。本論文提出H.266/VVC快速畫面間編碼演算法，首先計算128×128區塊的每像素平均編碼殘差值，設定臨界值以關閉數個編碼工具。再者，基於條件機率的統計，提前終止出現機率較低的編碼單位深度之四元樹/巢狀多類型樹分割或跳過三元樹分割。另外，利用空間域和時間域編碼樹單位的位元失真成本值計算皮爾森相關係數，找出最相關之編碼樹單位作為參考編碼樹單位，利用參考編碼樹單位之編碼資訊提前終止多類型樹或跳過三元樹分割。實驗結果顯示，所提出的方法在Random Access的架構下，可以有效減少平均37.16%的編碼時間並僅增加平均1.13%的Bjøntegaard Delta Bitrate (BDBR)。

The latest video coding standard, H.266/Versatile Video Coding (VVC), provides improved coding efficiency than its predecessor, H.265/High Efficiency Video Coding (HEVC). The quadtree/nested multi-type tree (QT/MTT) partition structure and coding tools in H.266/VVC greatly increase the encoding time. This thesis proposes a fast algorithm for H.266/VVC inter coding. First, the average residual per pixel of the 128×128 coding unit (CU) is calculated. Several coding tools are conditionally turned off according to the thresholds. Furthermore, based on the statistics of conditional probabilities, the proposed algorithm early terminates the QT/MTT partition or skip the ternary tree (TT) split of the CU depths that occur less frequently. In addition, we calculate the Pearson correlation coefficients, which utilizes the rate-distortion costs of the spatial and temporal coding tree units (CTUs), to choose the most correlated correlation CTU as the reference CTU. The encoded information of the reference CTU can be used to early terminate the MTT partition or skip the TT split. Experimental results show that the proposed approach can effectively achieve 37.16% encoding time reduction on average with an average increase of only 1.13% in Bjøntegaard Delta Bitrate (BDBR) under Random Access configuration.

摘要 1
ABSTRACT 2
目錄 4
表目錄 7
圖目錄 9
第一章 緒論 10
1.1 多功能視訊編碼H.266/VVC簡介 10
1.1.1 QT/MTT分割架構 11
1.1.2 編碼單位 14
1.1.3 預測架構 14
1.1.4 畫面間預測 15
1.1.5 轉換 18
1.2研究動機與目的 20
1.3論文架構 20
第二章 H.266/VVC快速演算法文獻回顧 21
2.1 H.266/VVC編碼工具決策文獻回顧 21
2.2 H.266/VVC畫面間快速演算法文獻回顧 22
第三章 所提出的畫面間編碼快速演算法 27
3.1基於殘差值之編碼工具快速決策演算法 27
3.2 基於條件機率之深度快速決策演算法 32
3.3基於皮爾森相關係數之多類型樹快速決策演算法 34
3.3.1 皮爾森相關係數之計算 34
3.3.2多類型樹分割決策 36
3.3.3 三元樹分割決策 37
3.3.4 三元樹分割方向決策 38
3.4整體畫面間快速編碼演算法 39
第四章 實驗結果 43
4.1 H.266/VVC測試影像序列 43
4.2參數設定 47
4.3結果與討論 49
第五章 結論與未來展望 57
參考文獻 58

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