目前以離散小波轉換為基礎的編碼技術中，SPIHT是一套具有很好壓縮效能的演算法。但是他仍然有許多方面可以改善，譬如如何減少記憶體的需求以及改善耗費大量時間這兩個議題。在這篇論文中，為了改善SPIHT本身耗時的這一項缺點，我們從SPIHT延伸出一套快速的編碼系統TSSPIHT，即是在前處理的過程中先針對不同的小波係數的特性對他作以二為底的對數運算，藉由這個動作去縮短編碼中我們所需檢查的位元平面總數。從實驗結果可以看到在低位元率的情況下，我們的編碼時間比傳統的方式快了約4.1~7.7倍；而在其他位元率下我們也快了約1.5~2.7倍，除此之外，我們也提出適合於這套編碼技術的改良式精練演算法，讓我們的方法可以跟SPIHT有相似的壓縮率。此外，由於我們的方式在優先編碼的位元串中保留比傳統SPIHT更多的高頻資訊，因此在低位元率的情況下我們可以得到較好的視覺品質，而在較高位元率的情況下也可以得到較好的影像品質。

SPIHT (Set Partitioning in Hierarchical Trees) is one of the state-of-the-art coders based on DWT (Discrete Wavelet Transform) and has good performance in image compression. However, it can still be improved in some concepts, such as memory requirement and time consumption. In this thesis, a coding method that follows the natural extension of SPIHT coding scheme for a high speed resolution scalable coding called TSSPIHT (Time Saving SPIHT) is proposed. In order to obtain a considerable speed improvement, this algorithm uses the base 2 logarithm of wavelet coefficients to shorten the checking times of the bit-planes shown by experimental results, the coding speed is 4.1~7.7 times faster than the speed of SPIHT at very low bit rates and 1.5~2.7 times faster at higher bit rates. Besides, the proposed method generates a similar amount of bit counts as the uncoded (i.e., no entropy coded) SPIHT because of the run-length coding method we proposed to transform the bit stream produced from refinement pass. Furthermore, the proposed method also gets better visual quality at very low bit-rates because it has more chances to preserve the detail information than traditional SPIHT in those subbands that different from the LL band.

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