本論文提出一種投射式視角預測搜尋演算法，是利用相機之內部參數和外部參數產生極線以及更精確的視角向量預測子以縮小搜尋視窗，並在不影響影像品質的前提下，節省H.264/MVC中視角間預測之運算複雜度，進而增進H.264/MVC的執行效能。另外，本論文亦參考影像之紋理分布提出新的移動向量預測子，此預測子不僅能在框間預測時增強物件的凝聚性，更能藉由物件內像素的群聚性減少移動估測的搜尋範圍，節省移動估測所需時間，並且重建出品質優良的影像。
本論文將所提出之投射式視角預測搜尋演算法實現於JMVC2.5中，根據模擬結果，在不同的量化參數以及不同的測試樣本中，本演算法皆可節省約70%至80%的運算量。在影像品質方面，PSNR僅下降0.01dB，位元率僅增加0.3%，此幅度在人眼所能接受的範圍之內；換言之，本論文所提出之投射式視角預測搜尋演算法能在影像效果幾乎沒有變差的前提之下，有效提升MVC的編碼效率。

H.264/MVC is the newest standard for digital video compression. Similar with H.264/AVC, H.264/MVC carries out the compression for multi-view image system to get the more compression efficiency. This thesis focuses on the computational complexity reduction in inter prediction and inter-view prediction. The main research point is to narrow the search window, and derived a more accurate disparity vector predictor and motion vector predictor for inter prediction and inter-view prediction.
Multi-view video system can apply different image for user’s eyes and allow users to have a more realistic visual experience. However, with the increasing of view, the amount of data to be processed can be also doubled. Multi-view images have not only temporal redundancies in the single view image, but also have a huge correlation between views. In order to reduce computational complexity, this thesis proposed a fast algorithm to find the redundancy between views.
According to the camera geometry, this thesis produces a more accuracy disparity vector predictor and narrows the search region of disparity estimation. For motion estimation, a new motion vector predictor can be found. Finally, this thesis implements the algorithm in JMVC. Experimental results show that the proposed algorithm can reduce 70~80% of the computational time, while maintaining high RD performance.

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