在現今資訊爆炸的時代，能有效的節省儲存空間及傳輸頻寬是重要的議題。而區塊截短編碼(Block Truncation Coding, BTC)是一種簡單且具速度快的一種靜態影像壓縮技術，但此方法相對於JPEG或JPEG2000所需要的位元率(bit rate)還要的高。而至今有許多改良BTC的演算法被提出，但若試著將BTC的壓縮率提高，會導致發生區塊效應與雜點問題。因此，提供一個低複雜度且能在低位元率下得到良好的影像品質的方法是不可或缺的。
　　本論文中，我們基於半色調式區塊截斷編碼的影像壓縮技術演算法作改良，利用四元樹分割(Quadtree Decomposition)來依據影像中的複雜程度來做變動大小區塊切割，並依據不同大小區塊搭配點擴散方法來降低高壓縮率下所產生的問題。
　　依據影像不同平滑區塊所做的處理方式不同，實驗結果不管是在客觀的影像評測標準或是主觀的影像結果，都能有效的在降低位元率下能達到較好的效果。

　　In the age of information explosion, reducing the storage and bandwidth has become an important issue in order to store and transmit images efficiently. Block Truncation Coding (BTC) is a still image compression technique with the feature of simple and fast. However, the bit rate of the BTC algorithm is relatively high compared to modern compression techniques such as JPEG or JPEG2000. At present, modified and improved BTC algorithms are proposed, but these algorithms produce block effect and noise while trying to promote compression ratio. Therefore, a low-complexity BTC technique that can reduce the perceptual artifacts effectively and provide good image quality at low bit rate is essential.
　　In this thesis, the proposed method is improved based on the halftoning-based BTC. Quadtree decomposition method segments the larger non-overlapping blocks of an image into smaller blocks based on the content of the image. To reduce the problem of high compression ratio, dot diffusion technique which diffuses the quantized error into neighboring unprocessed pixels is adopted to maintain the local gray level.
　　According to the smoothness of different blocks processes, the experiment result shows that our proposed method has better performance in reducing the bit rate of either image quality assessment or perceptual observation.

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