在本篇論文中，我們主要的目的是在希望能藉由影像在做向量量化編碼時，由於相鄰區塊的相似特性使得編碼後所得到的索引值表中會有很多的索引值出現局部相同的特性，而經由許多的相關研究也證實，藉由一些適當的方法來對這些索引值做更進一步的壓縮將會大大的提高向量量化編碼的壓縮比，降低位元率。

為了更進一步的能為影像的索引值表進行壓縮以降低位元率。我們將提出兩個直觀且有效的演算法，用以充分利用相鄰區塊間的編碼相似性，來達到在不增加任何失真的情況下有效的降低位元率。在演算法一中，我們建立一個稱之為關聯索引值表的表格於每個編碼字之後，使得接下來在做向量編碼的各個區塊在與先前編碼過的區塊索引值做比對時，若找不到相同的索引值則可經由這個關聯索引值表盡可能找到相同的索引值，而我們也提出了四個有效的方法來建立這個關聯索引值表並且，由於此表的建立皆可以在編碼前先訓練好，所以並不會增加編解碼時過多的負擔。經過實驗證明，我們所提出的四個方法皆明顯的降低了位元率，並且不會增加任何額外的影像失真率。而在演算法二裡，我們依照實際進行向量量化編碼時的情況，提出一個更有效的編碼架構，使得我們能明顯的降低位元率。

In this thesis, our main purpose will appear the partial same characteristic of a lot of index values by image at doing amount of vector quantization coding, because index value form that the alike characteristic of the close area piece gain after making the coding, and also prove through many related researches, by the method of some adequacy are worth to do to these indexes further compression will the huge exaltation amount of vector turn the gain the compression ratio, reducing the bit rate.

For the sake of further carry on reducing the bit rate in compression for the index value form of the image.We will put forward two coding that keep view and valid algorithms, in order to and well make use of close together area a likeness, reach to reduce the bit rate effectively under the condition of not increase any image lose.In algorithm first, we establish a form that call it as index associated list after each codeword, make connect down at the each area piece that do the vector coding at and area coded in times before an index is worth to do ratio to, if can not find the same index value and
then can find out the same index value possibly through the index associated list, and we also put forward four valid methods to establish this index associated list and, because this form of the establishment all can trains first before coding, so also can't increase the excessive burden for plait to solution yard.Through experiment certificate, four methods that we put forward are
all obvious reduced the bit rate, and don't increase any image to lose .And in the algorithm second, we adhere to carry on physically condition for amount of vector to encode, put forward a more
valid coding structure, make us be able to reduce the bit rate obviously.

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