本文提出對JPEG2000 裡的嵌入式區塊編碼的詳細分析和高效的優化設計。在JPEG2000系統中,EBCOT需要相當大的運算量,為了增進EBCOT的效率，我們提出結合二個加速演算法,Pass Prediction 和Sample Skipping。Pass Prediction 演算法預測下一個位元平面的pass狀態，再利用相鄰位元以傳播的方式得到下一個位元平面所有pass的狀態。根據EBCOT的編碼原則，同一位元己被某pass編碼後,即無需要再由其它pass編碼,傳統編碼方式.即使己經由某pass編碼，一樣會將全部的pass掃描一遍。Sample Skipping演算法則是標記己被編碼過的位元，區別出需要被編碼的位元，以及不需要被編碼的位元，並跳過不需編碼的位元，減少不必要的掃描過程以加速整個壓縮的過程。根據實驗結果，我們提出的加速演算法在有損壓縮部份，可減少灰階影像6.2%~7.3%的壓縮時間;減彩色影像9.2% ~ 18.6%的壓縮時間，無損壓縮部份，可減少灰階影像14.2%~20%的壓縮時間;彩色影像10.7% ~ 16.8%的壓縮時間。

This paper analyzes JPEG2000 embedded block coding and a design of efficiency optimization in detail. In JPEG2000 systems, the EBCOT requires considerable computation. In order to improve the efficiency of EBCOT, we integrated the two speed-up algorithms - Pass Prediction and Sample Skipping. The Pass Prediction algorithm predicts the pass state in the next bit-plane, and acquires the entire pass states in the next bit-plane through pass propagation of neighboring bit. According to EBCOT coding rule, once a bit has been coded by a certain pass, it will require no more coding by another pass. With the traditional coding algorithm, a bit that has been coded by a certain pass will still have to go through all pass scanning again. To distinguish the bits that require coding and those don’t require so, Sample Skipping marks the bit which has been coded; in this way, the compressing and scanning time that used to be wasted on the coded bits is now saved up. The results of our experiment show that the proposed algorithm reduces 6.2%~7.3% the amount of scanning time for gray-level images and 9.2%~18.6% the amount of scanning time for color images in loosy compression ,and reduces 14.2%~20% the amount of scanning time for gray-level images and 10.7% to 16.8% for color images in lossless compression.

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