在網路及多媒體資訊的帶動下，將資訊隱藏在數位資料中的技術漸漸普遍，其重要性也逐步升高。尤其在軍事、緊急醫療、監視系統上，這些技術更是目光的焦點。使用在這幾個領域上的數位影像，都有著空間或時間上的限制，以致於某一時間點所產生的影像，無法重製，也無法重新傳送。更重要的是，這些領域對影像品質的要求相當高，其內容的準確性須達到一定的水準才有法律上或實用上的參考價值。因此，已有許多針對這些領域來開發的基於資料隱藏與不經壓縮的通訊頻道的錯誤修復演算法，來面對數位影像封包掉落或是遭受攻擊的情況，其在修復畫質的表現上令人驚豔，但普遍來說，它們都有運算複雜度過高，難以實際應用的問題。 本篇論文將會提出一個高效能的錯誤修復演算法，其核心是將影像區塊以其與鄰近區塊之相關性及本身複雜度作分類，並分別施與不同的修復策略，同時針對區塊特性的不同，將可嵌入資訊的空間重新分配，以期達到實際應用上可接受的運算複雜度，並同時保持高水準的影像修復品質。

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