A Study of Adaptive Error Concealment Method Selection for Multiview Video Transmission

[[abstract]]在現今的視覺娛樂產業中，影像立體化是極力發展的目標，多視角視訊可增加影像立體化可看性。然而，多視角視訊的編碼複雜高、需要有大量的記憶體空間儲存，增加傳輸負載。因此，Joint Video Team(JVT) 發展多視角視訊編碼技術以解決上述問題。現有的多視角視訊處理技術包含多視角視訊壓縮技術(Multiview Video Coding, MVC)、三維影像壓縮技術(3D video coding, 3DVC) 和高效能視訊壓縮技術（High Efficiency Video Coding, HEVC）皆是以H.264/AVC編碼技術為基本架構。根據單一視角內連續畫面之間的相似性、相鄰視角畫面間的相似性，以及多視角視訊和其對應之深度圖具有極高的相關性，進行資料的編碼壓縮以減少多視角視訊的資料冗餘，因此每一個bit所代表的資訊量增加。編碼後的資料流在傳輸過程中一旦發生遺失會引起解碼畫面的不完整，不僅是目前的解碼畫面品質下降，連帶降低其他解碼畫面的品質，其影響範圍從單一視角到其他視角視訊的畫面皆有可能受損。因此，本論文提出自我適應性錯誤隱藏方法的決策，此分別應用在MVC和3DVC壓縮技術，以避免多視角視訊發生錯誤傳遞的情況。此決策利用相鄰未毀損或是已修補區域的動量和紋理資訊定義毀損區域的時間域和空間域特性，以顯示毀損區域的具有較強的時間域或是空間域，並且根據此兩種特性透過模糊理論選出適合目前毀損區域的錯誤隱藏方法進行錯誤修補。 由模擬結果顯示，在多視角視訊壓縮和立體視訊編碼系統，本論文所提出的演算法在花費較少的時間獲得較高的修補畫面品質。可以解決錯誤傳遞的問題。達到提高畫面品質的目的。[[abstract]]Currently, multiview video has become the major topic in television system that provides the viewer with reality experience. However, the multiview video has the high coding complexity, needs the hung storage to store the data, and increases the transmission load. Therefore, Joint Video Team (JVT) develops the multiveiw video coding techniques to solve these problems. The multiview video coding technologies, such as multiview video coding (MVC), 3D video coding (3DVC), and High Efficiency Video Coding (HEVC), are developed to reduce the data redundantly in the MVV. It includes the similarity between the successive frames in the same view, the similarity between the frames have the same timestamps in the interviews, and the correlation between the MVV and its corresponding depth map. However, that the data stream is lost in the transmission causes the decoded image incomplete. The completeness of other decoded images is also destroyed by the current damaged image. The affected images may be the other frames in the same view or the other frames in the interview. Then, this not only lowers the quality of the current decoded image, but also reduces the quality of the other decoded images. Therefore, this dissertation proposes an adaptive error concealment method selection to avoid the error propagation in the multiview video. The proposed algorithm defines the temporal and spatial correlations for the damaged macro-block (MB) based on the motion vector (MV) of neighboring blocks and their texture information, where is undamaged or concealed MB, respectively. Moreover, the two correlations of the damaged MB determine the suitable error concealment for the damaged MB to improve the quality of the concealed image. To increase the reconstructed quality of the damaged macro-block, the proposed error concealment method selection determines the error concealment, which is suitable to reconstruct the damaged macro-block, is based on these two correlations through fuzzy reasoning.[[note]]博