隨著近年來硬體技術及視訊編碼技術之進步，視訊解析度由原本的480P到現在手機都支援播放的4K影片，視訊資料量大幅度的增加，因此視訊壓縮成為相當重要的課題。而自由視角視訊（Free-View Video, FVV）與立體視訊（3-D Video）也越來越受到重視，隨處可見多視角的應用，例如可供3D影像拍攝的手機或是虛擬實境的頭戴式裝置等。針對多視角視訊，若只運用紋理資訊(Texture Information)要達到較佳的自由視角收視體驗，需耗費大量的軟硬體的計算負載。為了降低視訊的傳送成本及提高合成視角之畫面品質，多視角視訊導入了深度影像的資訊(Depth Information)，其具備左右視角之紋理資訊與同步紀錄的深度資訊，藉由運用深度與彩度資訊間的信號關聯性，可大大減少合成中間視角所需要的軟硬體成本。雖然套用現有紋理影像之編碼方式可以編碼深度影像，但由於深度影像之特性與紋理影像略有不同，壓縮效果並沒這麼顯著，故深度影像的壓縮及編碼方式也成為了重要的研究項目。本論文研究運用深度影像之特性，提出一個基於多階層式的深度影像編碼方式，搭配鏈碼與區域分割資訊以達到降低整體編碼運算負擔的效果，實驗結果顯示本論文所提出的方法，相較於系統預設方法，可大幅降低編碼時間，而且可進一步運用深度資訊提升彩度資訊的編碼品質。整體可提昇多視角視訊的編碼效能。

With the advance of the multimedia codec technologies and related application devices, the cost to transmit media data can be reduced while the system can still maintain high quality reconstructed video. In additional to the conventional 2-D multimedia applications, the Free-View Video (FVV) and 3D Video become popular in that better user perception experiences can be provided. The FVV and 3D-Video related applications have been wildly developed and utilized to drive more user interests. The FVV and 3-D Video are acquired by utilizing multi cameras from different view angle of the same scene. To reduce the costs of multi-view data transmission and enhance the quality of the reconstructed virtual views, not only the texture but also the depth information have to be well manipulated, as the latter plays an important role in virtual view synthesis. In this thesis, we propose a new depth map coding scheme to improve the inefficiency of applying conventional texture information based video coding tools on video depth map. Based on the fact that the depth map comprises sharp edges that surround object region boundaries and all depth map values belonging to the same region are nearly constant, the conventional 2D video codec which are designed to well compress video texture information is proved to be inefficient to encode depth map information. By utilizing the high correlation between texture and depth map, we propose a texture segmented region-based depth coding scheme to reserve accurate depth information while saving required bit rates. We proposed to utilize a two-layer depth image coding method, together with chain code and region segmentation results, to reduce the total FVV coding complexity. Experimental results show that the proposed method can largely shorten the encoding time and the decoded depth information can be used to improve the texture image coding performance. It helps to improve the overall FVV encoding performance.

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