結合樣板及區塊動作補償之雙動作向量預測方法

Abstract

本篇論文介紹了一種基於結合樣板比對預測(TMP)和區塊動作補償(BMC)的雙動作向量預測方法。由於本技術採用交疊動作區塊動作補償(OBMC)方法所產生的像素可適性權重係數表來結合兩個分別來自樣板比預測(TMP)和區塊動作補償(BMC)之預測區塊中的每個像素，因此如何設計這些權重係數值以達到最佳的預測效果，便成了本技術的關鍵部份。為了決定這些權重係數，本論文採用了一種參數化的理論模型來推導產生最佳的權重係數，同時也據此修正了原本傳統動作向量的預測方式，在動作向量預測階段即導入這些權重係數以達到更精確的預測效果。為了要驗證本論文所提出來的雙動作向量預測方法的可靠性及壓縮效能，本論文設計了一系列的實驗，企圖在壓縮效能及運算複雜度上面取得平衡。實驗結果顯示在最佳權衡之下，壓縮效能可以達到1.1%到4.1%的範圍內平均2.2％的BD-Rate節省，複雜度方面在合理程度上編碼端上升了46％的壓縮時間，解碼端則是上升了33%.

This thesis introduces a bi-prediction scheme based on a joint application of template and block motion compensations. Since the template motion is decode-side inferable, this scheme needs only a motion overhead as that of uni-directional prediction. Two predictors derived from the template and block matchings are weighted in a pixel-adaptive manner using OBMC. From an analytical aspect, we provide an optimal design of window function in a parametric overlapped block motion compensation (OBMC) framework to further improve the efficiency of inter-frame prediction. In view of the tradeoff between the performance and the complexity, we discussed the impacts on the prediction efficiency of the proposed scheme when the number of template shapes and the number of motion hypotheses are changed. Also, a fast template search is provided, which greatly reduces the complexity at the decoder side. As compared with HM3.0, the proposed scheme achieves an average BD-rate saving of 2.2%, with a minimum of 1.1% and a maximum of 4.1%. The encoding time increases 46% while the decoding time increases moderately in 33%.