在這篇論文，提出了二種嵌入機密資料的方法，其中一種是在壓縮影像中嵌入資料，另一種是在多元影像中嵌入資料。許多資訊隱藏的技術被應用在向量量化編碼所需的索引表中。然而將機密資料嵌入到索引表中會嚴重影響到原始影像在向量編碼時所造成嚴重的失真。在現今機密分享的技術中，都只擁有認證的能力，卻沒有容錯的能力，這種情況會導致如果在分享的影像中有資料被破壞及損毀，將會造成回復時機密影像的呈現不可辨識或是過度失真。

在第一個方法，我們試著在嵌入機密訊息於索引表時，增加可以藏入的資料量，維持索引表是零失真的狀態和減少壓縮率。在這個方法有效運用了循序搜尋分辨法(SOC)去找到向量索引表與其鄰居之間的關聯性。因為適當的索引值之間擁有很高的相似性，所以在索引表中隱藏資訊以及在對已經嵌入資料的索引表做編碼可以運用較少的位元數。

在第二個方法，我們提出了一個有效的機密分享技術而且它不只包含了認證的能力而且還有補救及容錯的能力。當分享出去的其中一張機密影像在收到時，已經有部份資料遺失或損毀，可以運用這個方法提出來的機制去補救它，而使它在合成原來機密資料的結果更加精準，擁有較高的視覺效果。

In this thesis, two types of embedding techniques are proposed. One is that of embedding secret data into condensed images while and the other applies to multiple images. Many steganographic techniques are currently exploited for the VQ index table. However, the embedding strategies require longer compression codes and decrease visual quality. Secret-sharing is a technique first invented by Shamir. It is used to split a secret into n shares and then distribute them to n users. Later, t shares can cooperate to reconstruct the secret, called the (t,n)-threshold. Recently, many meaningful secret sharing schemes have yielded authentication mechanisms, yet none included a remedy ability, which may mean that the secret image will not be obtained completely, while some information about stego images is lost.
In the first method, we tried to satisfy the essentials of increasing the secret payload, preserve the VQ index table without loss, and reduce the compression rate. The proposed scheme utilizes search order coding to determine the correlation between the VQ indices and neighboring indices. Because of the similarity among adjacent indices, the new method can embed the secret bits into the index table and encode the embedded index table using fewer bits.
In the second method, we proposed a meaningful secret sharing scheme to include the authentication and remedy abilities that allow for some data loss in the secret image. This approach has the ability to repair the secret image with reasonable visual quality.

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