運用混合小波封包與離散餘弦轉換及
最佳位元配置之高音質音訊壓縮系統

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姓名

吳宗紘(Tsung-Hung Wu) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

運用混合小波封包與離散餘弦轉換及最佳位元配置之高音質音訊壓縮系統
(Hybrid Wavelet Packet and Discrete Cosine Transform with Optimum Bit Allocation Applied to High-Quality Audio Coding )

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摘要(中)

以小波分頻的訊號壓縮技術已被廣泛地應用在音視訊編碼系統中，其優越的性能充分顯現在靜態影像之壓縮技術上。本論文提出混合小波與離散餘弦轉換之音訊壓縮系統，以小波封包分頻方式，將樂音訊號經由濾波器群組分成26個次頻帶，再根據時域與頻域之平坦程度，決定是否要進一步執行離散餘弦轉換。本系統並採用非理想合成濾波器之最佳位元配置演算法，將人耳聲學模型所得出的頻域最小遮蔽臨界值，轉換成小波域上的遮蔽臨界值，以提供精良的量化準則。其後以均勻量化器配合小波域的遮蔽臨界值，大幅降低資料量並仍保有極高的音質，最後再以算術編碼將量化後的係數做進一步的熵編碼並封裝成位元流。實驗結果顯示，本系統僅需52 kbps即可達到MP3 64 kbps的音質；另外，在同樣64 kbps之位元率下，本系統所提供的音質不但優於MP3、AAC低複雜度規格，更可超越AAC高效率規格。

摘要(英)

The wavelet filter bank analysis-synthesis technique has been widely applied to many areas of digital signal processing, especially in image and video coding. In this thesis, we propose a hybrid Wavelet Packet and DCT audio compression system, which divides the audio signal into 26 subbands via Wavelet Packet analysis and selectively performs DCT in each subband according to the flatness measure of time and frequency of this subband. The proposed coder adopts optimum bit allocation with nonideal reconstruction filters to transform the minimum masking threshold in frequency domain obtained from psychoacoustic model into the masking threshold in Wavelet domain. The WP or DCT coefficients are then quantized with uniform quantizers according to masking threshold, so that we can reduce the data rate but still have high quality. Finally, the quantized coefficients are encoded with arithmetic coding and encapsulated with other side information. The experiments show that, only 52 kbps is needed for proposed audio coder to achieve MP3 64-kbps quality. At the same bit rate of 64 kbps, the proposed audio coding system can provide not only better quality than MP3 and AAC LC profile but also superior to AAC HE profile!

關鍵字(中)

★ 壓縮
★ 小波
★ 離散餘弦轉換
★ 音訊

關鍵字(英)

★ wavelet
★ DCT
★ audio
★ compression

論文目次

目錄
目錄 III
圖目 VI
表目 VIII
第一章緒論 1
1.1 音訊壓縮簡介 1
1.2 研究動機與目的 3
1.3 系統架構 4
1.4 論文架構 5
第二章小波分析技術 7
2.1 小波轉換 ( Wavelet Transform ) 7
2.1.1小波分解與離散小波轉換 8
2.1.2多重解析度分析 9
2.2小波轉換與數位訊號處理 11
2.2.1 小波濾波器 11
2.2.2 Daubechies緊密時間涵蓋小波 17
2.2.3 GBCW雙正交小波 19
2.3小波封包 ( Wavelet Packet ) 20
第三章人耳聲學模型及其應用實例 24
3.1 一般音訊壓縮編解碼器結構 24
3.2 人耳聲學模型 26
3.2.1 基本原理與其應用 26
3.2.2 雜訊對單頻音的遮蔽效應 28
3.2.3頻音對單頻音的遮蔽效應 32
3.2.4 時間軸上的遮蔽效應 33
3.2.5模型公式 34
3.3 MPEG音訊編碼器家族 38
3.3.1 MPEG-1第三層（MP3） 40
3.3.2 先進音訊編碼（AAC） 43
3.4 算術編碼 46
第四章小波音訊壓縮系統 49
4.1 轉換 50
4.1.1 Daubechies緊密時間涵蓋小波 50
4.1.2 GBCW雙正交小波 54
4.1.3小波封包 55
4.1.4離散餘弦轉換 57
4.2 最佳位元配置 58
4.3熵編碼 61
第五章實驗結果與討論 65
5.1 客觀評量工具 – EAQUAL 65
5.2 CDF與GBCW雙正交小波之比較 68
5.3 調適性小波與非調適性小波之比較 69
5.4 正交小波與雙正交小波之比較 .72
5.5 混合小波轉換與離散餘弦轉換 73
5.6 複雜度分析 77
第六章結論與未來展望 81
6.1 結論 81
6.2 未來展望 81
參考文獻 82

參考文獻

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指導教授

張寶基(Pao-Chi Chang)

審核日期

2004-6-20

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