中文摘要
　　H.264/AVC壓縮標準採用大量預測機制及熵編碼來達到高壓縮率，可是在網路傳輸時若發生封包遺失，則易造成連續區塊解碼錯誤，而導致之後連續預測畫面品質大幅下降。採用錯誤隱藏法(Error Concealment)於影像發生錯誤時在解碼端加以修復，即可以有效防止錯誤快速擴散以確保視訊之品質。利用時間域(Temporal)作錯誤藏匿之邊界配對法(Boundary Match Algorithm，BMA)是以全搜尋法為基本，修復之區塊可具有較好的品質，但在計算上卻是最費時的。而改良式錯誤隱藏法(Improved Error Concealment，IEC)，加快了錯誤區塊尋找的速度，但找出的配對區快有可能並非最佳解。因此如何在搜尋速度與修補之品質上作取捨，是一個值得深入研究的課題。
　　本論文基於邊界配對法提出一邊界特徵點配對演算法，利用拉普拉斯(Laplacian)二階導數特性求取錯誤區塊外邊界上的特徵點。利用錯誤區塊與候選區塊外邊界上所有特徵點的模式比對(Pattern Match)，來挑選有可能的候選區塊，進而減少需要配對區塊之邊界差異值的計算，以減少整體之搜尋時間。此外，由於特徵點的對齊具有邊緣(Edge)對準之效用，此可改善區塊間不平滑之現象，讓修補畫面可以擁有趨近於全搜尋法的品質，達到加快計算速度與確保視訊品質雙重效果。
　　實驗結果顯示，所提出的特徵點配對錯誤隱藏法，擁有與全搜尋法為基準之邊界配對法等價的影像品質，且有效改善邊界上不平滑現象，而且在時間效能上，亦優於邊界配對法與改良式錯誤隱藏法。

Abstract
　H.264/AVC can achieve high compression ratio by applying for prediction scheme and entropy coding. When the packet transmitting in the internet is lost, the decoder error will happen and lead to the quality of the next P-frame reduced.
　Applying for error concealment scheme at the decoder can prevent the error propagation and keep the quality. The temporal method - boundary match algorithm (BMA) based on full searching have good recovery quality, but the full searching is time-consuming. The improved error concealment algorithm (IEC) can decrease the searching time, but maybe gets the less important match block. For the reason, poising the good recovery quality and the faster computation time is deserved to be mentioned.
　In this paper, we propose the boundary feature point match algorithm (BFPMA) based on boundary match algorithm. Search the boundary feature points of the corrupted block by using Laplacian second derivative. Matching the boundary points of the corrupted blocks and the candidate blocks is useful to find possible candidate blocks. Because of reducing the number of the candidate blocks, the computation time can saved. Otherwise, the boundary points can aim at each others to improve the rough situation between two match blocks. The quality and the computation performance of pictures are improved effectively.
　Performance evaluation shows that the proposed method can achieve better computation performance and better quality of the pictures then the boundary match algorithm and improved error concealment algorithm.

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