本論文旨在研究深度資訊應用於H.264/AVC視訊標準編碼之影響，以期提高移動向量預測(Motion vector Prediction)的準確度。在傳統移動向量預測演算法中，編碼區塊的預測移動向量是利用鄰近區塊的移動向量取中間值得到。如果鄰近區塊的移動向量不夠可靠，應該避免拿來做移動向量預測。本論文利用深度資訊來協助判斷所參考區塊的移動向量是否可靠，根據變異係數(Coefficient of Variation)來計算鄰近區塊在深度資訊中的變化，當變異係數的值大於臨界值時，則此區塊的移動向量就比較不可靠。採用更可靠的移動向量預測方法，將可以提升編碼的效能。
模擬結果顯示，本文提出的演算法不管是在針對靜態或是動態的影像都有明顯的效能改善。靜態影像平均省了1.25%的編碼位元，中等移動影像平均省了3.47%的編碼位元，動態影像平均省了7.56%的編碼位元。

This thesis proposes a motion vector prediction algorithm in H.264/AVC that uses the depth information to get more accurate motion vector predictor (MVP) for motion estimation. In conventional video coding, the MVP of the current block is obtained by finding the median of the motion vectors in neighboring blocks. When the motion vectors of some neighboring blocks are not reliable, they shouldn’t be used to find the MVP. In this thesis, the reliability of the motion vectors of neighboring blocks is determined by the depth information of those blocks. The coefficient of variation (CV) for the depth values in each neighboring block is calculated. The motion vectors of the neighboring blocks that CV values are larger than threshold are considered as unreliable. Since a more accurate MVP is determined by the proposed algorithm, the coding performance is improved.
Simulation results show that the proposed algorithm greatly improves the coding performances. The bit rate can be saved up to 1.25% for sequences with little motion, 3.47% for sequences with medium motion, and 7.56% for sequences with high motion.

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