由於裸眼立體顯示器同時顯示多組虛擬視角給使用者選擇，因此能獲得較佳的立體觀賞品質。目前立體視訊均為雙視角影像，因此如何將現有的雙視角生成多視角影像便成為一門重要的議題。現今的多視角影像生成系統皆是基於深度影像繪圖系統生成虛擬視角影像，但基於深度影像繪圖系統存在兩大難題，一為高精確度的深度圖計算，另一為補洞。另外，基於深度影像繪圖系統於影像中有運動模糊、失焦、透明或反射物體等情況下，難以得到很好的虛擬視角的品質。本論文提出一未使用任何深度資訊，基於相位調整的多視角生成系統。本系統的主要架構是基於由Didyk等人所提出的基於相位的多視角生成技術下進行改進，主要提出利用內插方法預測虛擬視角影像與原視角影像的相位差異，進而產生出多組虛擬視角。在實驗結果上，亦證明本系統能有效改善原始的基於相位的多視角生成技術，並有效地增進虛擬視角影像的品質。

Multi-view autostereoscopic displays provide a comfortable visual experience because multiple views are presented for viewers to offer a desired motion parallax. In general, we could utilize a depth image-based rendering (DIBR) technique to obtain multiple virtual views. However, there are two major challenges of DIBR-based methods, which require high accurate depth map estimation and hole-filling functions. Moreover, the DIBR-based methods cannot perform well for challenging video scenes with defocus blur, motion blur, transparent materials, and specularities. In this thesis, a novel phase-based multi-view generation system is proposed without using any depth information. The main kernel concept of the proposed system is based on the phase-based view expansion technique proposed by Didyk et al. The proposed system presented the phase difference prediction procedure by using simple interpolation methods. Experimental results prove that the proposed system performs better than the phase-based view expansion method and the DIBR-based method.

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