隨著近年來3D電影的風行，如前些年的阿凡達(Avatar)，以及今年火紅的少年Pi的奇幻漂流(Life of Pi) 等電影推出，讓3D影像形成影視娛樂中不可或缺的一員。然而除了電影產業，3DTV也將逐步進入家庭的影音娛樂。
對於3D影像的壓縮，目前廣為使用的技術稱為 ”Advanced Three-Dimensional Television System Technologies (ATTEST).” 它將彩色影像及對應到的深度影像壓縮編碼，經由傳輸以及解碼，再透過 Depth-Image-Based Rendering (DIBR) 的技術，合成出不同視角的影像。
然而，ATTEST系統中前端壓縮的資料量仍舊龐大，因此在本篇論文中提出一個新的3D影像壓縮的演算法。在H.264/AVC架構下，利用分享移動向量以及深度搜尋來降低深度影像壓縮的計算複雜度，並且提出一個快速移動估算演算法，提升3D影像的壓縮效率，同時保持影像品質。

With the popularity of 3D movies in recent years, such as Avatar few years ago, and the most popular Life of Pi this year, 3D images becomes an integral part in the entertainment. Moreover, in addition to the movie industry, 3DTV will gradually enter the home audio and video entertainment.
For 3D image compression, there is one of the most famous techniques called “Advanced Three-Dimensional Television System Technologies (ATTEST).” It use a monoscopic video (color image) and per pixel depth information (depth image) to compress and encode. Through transmission and decoding, it used the technique of Depth-Image-Based Rendering (DIBR) to synthesize free view-points views.
However, there still has a huge amount of data in the encoder of the ATTEST system. Therefore, this thesis proposed a new 3D image compression algorithm. In H.264/AVC, we use sharing motion vector and depth search to reduce the computational complexity in the depth image compression, and also propose a fast motion estimation algorithm to increase the compression efficiency in the 3D image while maintaining image quality.

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