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研究生:吳倉志
研究生(外文):Tsang-Chih Wu
論文名稱:以二維轉換以及連續近似值編碼進行失真到無失真的多導程心電圖壓縮
論文名稱(外文):Lossy-to-Lossless Compression for Multichannel ECG Using Two Dimensional Transform and Successive Approximation Coding
指導教授:繆紹綱繆紹綱引用關係
指導教授(外文):Shaou-Gang Miaou
學位類別:碩士
校院名稱:中原大學
系所名稱:電子工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:中文
論文頁數:79
中文關鍵詞:多導程心電圖小波轉換心電圖壓縮SPIHT
外文關鍵詞:wavelet transformmultichannel ECGECG compressionSPIHT
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  • 被引用被引用:1
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  • 下載下載:38
  • 收藏至我的研究室書目清單書目收藏:2
傳統的心電圖(Electrocardiography, ECG)共有十二個導程,包括心電訊號的額平面(frontal plane)六個導程的投影和在橫平面(horizontal plane)六個導程的投影。而在橫平面的六個導程(V1到V6)中,彼此的相關性相當的高。以往大都是對於單一導程ECG訊號提出各式各樣的失真與無失真的壓縮方法,而針對多導程直接處理的方法則相當的少。
對於多導程ECG訊號,以單一導程的編碼基礎去處理相當沒效率,因為此方法並沒好好運用到導程與導程間的相關性,因此我們提出一個新的方法,利用2D整數小波轉換(IWT)與集合分割階層樹狀法(SPIHT),搭配連續近似值編碼(SAC),以達到對多導程ECG訊號的壓縮。此2D轉換將可以利用到各導程間的相關性,經過轉換會產生小波係數方塊,此方塊的傳送與否更會經由方塊重要性辨識器去決定是否傳送。IWT確保真正的無失真壓縮,而SPIHT使我們可以有效率的運用於失真到無失真的壓縮。
本論文以CSE 多導程資料中的八個導程為實驗資料,實驗結果顯示,與單導程壓縮法做比較,本研究方法不管對於失真或無失真壓縮都優於單導程壓縮方法。在失真壓縮方面,當壓縮倍率在12.34時,以單導程方法所得的平均PRD為7.56%,以本研究所提方法則為3.21%,故明顯優於單導程壓縮法;在無失真壓縮方面,使用單導程方法由原本的6000 bits/s降為平均3007.8 bits/s,使用本研究所提方法則降為2876 bits/s。
The traditional Electrocardiogram (ECG) has twelve leads, including six frontal plane leads and six horizontal plane leads, and the six frontal plane leads (from V1 to V6) correlate closely with each other. In the past, lossy and lossless compression methods are often proposed for single channel ECG signals, and compression methods that are directly applied to multichannel ECG signals are rarely seen.
For multichannel ECG signals, encoding ECG signals on a channel by channel basis is not efficient because the correlation across channels is not exploited. We propose a new ECG compression approach using a two-dimensional (2D) integer wavelet transform (IWT) and the set partitioning in hierarchical trees (SPIHT) along with successive approximation coding (SAC). The 2D-transform exploits both the in-channel and the inter-channel correlations. The transform results in wavelet coefficient blocks. Whether a block will be sent is determined by a block significance classifier. The IWT guarantees a true lossless compression, and the SPIHT allows efficient coding and progressive transition from lossy to lossless compression.
The ECG data of 8 leads in the CSE Database are tested. The experimental results show that the proposed approach performs better than its single-channel version in both lossy and lossless cases. For lossy compression, when compression ratio is 12.34, the average PRD is 7.56% using the single channel and 3.21% using the proposed approach. The performance of the proposed approach is significantly better than that of the single channel version. For lossless compression, the average compressed data rate per channel is reduced from 6000 bits/s to 3007.8 bits/s using the single channel approach and to 2876 bits/s using the proposed approach.
目錄

摘要…….…………………………………………………………………..….I
Abstract..………………………………………………………...……………II
誌謝…..………………………………………………………...……………III
目錄…………………………………………………………………..……...IV
圖索引……………………………………………………...………….….…VI
表索引………………………………………………...…………….…..…VIII

第一章 緒論………………………………………………..……….....……..1
1-1研究背景………………………………………..……….....…….....1
1-2研究動機與目的………………………………………………..…..2
1-3研究方法與步驟………………………………………………..…..4
1-4論文架構………………………………………………..…………..5

第二章 基本原理……………………………………………………….……6
2-1資料壓縮…………………...……………………………………………6
2-2標準12導程心電圖…...……………………………………………7
2-3傳統式離散小波轉換………………………………………………11
2-4Lifting Scheme…………………………………………………….15
2-5整數小波轉換………………………………………..……………18
2-6SPIHT原理介紹…………………………..……………………….20
2-6-1空間方向樹………………………………..………………..20
2-6-2集合分割……………………………..……………………..22
2-6-3演算法說明…………………………..……………………..23

第三章 小波轉換的探討……………….…………………………......……25
3-1 矩形小波轉換…………………….……...……………………………..25
3-2 樹狀方塊抽取……………………….…………...……………………..27
3-3 小波轉換濾波器…..…………………….……………….....…………..28
3-3-1 心電圖濾波器選擇…………………………..……………….…29
3-3-2 MIT/BIH Arrhythmia資料庫實驗結果………...…………….…31
3-3-3 CSE心電圖資料庫實驗結果…………………..………….….…32

第四章 失真與無失真心電圖壓縮演算法…....………………….……......35
4-1 壓縮演算法整體架構…………………….……...…………….……….35
4-2 小波轉換濾波器組的選擇………………….……………………….....37
4-3 樹狀方塊與二維小波係數的關係…………….………..……….……..38
4-4 失真壓縮…………………………...…………….………..…................41
4-4-1 方塊辨識器………………………………..…………………….43
4-4-1-1 線性迴歸…………….………………….……………..44
4-4-1-2 非線性迴歸…………………….……….…………..…..46
4-4-2 方塊辨識器與SPIHT編碼…..……………..………………..….48
4-4-3 整體失真壓縮演算法流程……..……….……………………....49
4-5 無失真壓縮…………………………………………….……………...51
4-5-1 整體無失真壓縮演算法流程……...……………….…………...51

第五章 實驗模擬與結果….………………………...……………...………53
5-1 實驗環境設置……………..………………….………………...………53
5-1-1 導程的重建………………………………..…………………….53
5-1-2 實驗數據設定……………………………..…………………….55
5-2 心電圖失真壓縮效能之實驗結果………...………………….…..……59
5-3 心電圖無失真壓縮效能之實驗結果…..………………………....……63

第六章 結論與未來展望……………..…………………….…….…...……64
6-1 結論………...………………………………………………….…..……64
6-2 未來展望………………………………..………………………....……64

參考文獻………………………………………………………….………....66

圖索引

圖2.1 標準肢導程量測位置………………………..….…………………….8
圖2.2 AVL導程量測位置…………....……..….…………………..…...……9
圖2.3 AVR導程量測位置…………....……..….…………………..…...……9
圖2.4 AVF導程量測位置…………....……..….…………………..…...……9
圖2.5 六個胸導程(unipolar precordial leads)量測位置.......…...…..……10
圖2.6 一維信號做一層小波分解與合成....…….…………...………..…....12
圖2.7 二維影像做一層二維小波轉換.…..……….………...…………..…13
圖2.8 二維信號的一層小波分解堆…….…...………...……...……………13
圖2.9 二維信號的二層小波分解堆…….…...……….………...…………..13
圖2.10 影像分解後之示意圖…………………………...………………….14
圖2.11 上提式架構的小波轉換…………...……..……..….………………16
圖2.12 上提式架構的小波反轉換…..………………..…….……………...17
圖2.13 5/3濾波器之上提式小波轉換…………..……………..…………...18
圖2.14 9/7濾波器之上提式小波轉換…..….………………...…..…...……18
圖2.15 上提式架構的整數至整數小波轉換……………….…...........……19
圖2.16 1-D SPIHT頻帶間空間方向樹的關係…....…………………..…....21
圖2.16 2-D SPIHT的parent-offspring關係….…....…………………..…....21
圖3.1 二維矩形小波轉換……………………………...………………..….26
圖3.2 階層式的樹狀方塊架構…...…...….…………………..…...………..28
圖3.3 心電圖壓縮演算法.……..…….…………………..…...…………….30
圖3.4 無失真壓縮5/3與9/7小波轉換之壓縮效能比較曲線..……..….....31
圖3.5 失真壓縮5/3與9/7小波轉換之壓縮率與失真度曲線..……..….....32
圖3.6 無失真壓縮5/3與9/7小波轉換之壓縮效能比較曲線..……..….....33
圖3.7 失真壓縮5/3與9/7小波轉換之壓縮率與失真度曲線..……..….....34
圖4.1 本論文所提出之心電圖壓縮演算法的方塊圖…...………..….........36
圖4.2 9/7 tap濾波器的脈衝響應……..…………………………..…...........37
圖4.3 二維小波係數與SPIHT編碼之效能理想圖….………....................38
圖4.4 一維小波轉換係數與頻帶分布圖….……...……...………...............39
圖4.5 各導程一維小波轉換係數與頻帶分布圖…………..….…...............39
圖4.6 二維小波轉換係數與二維頻帶分布圖…...…………………….…..40
圖4.7 二維矩形小波階層式的樹狀方塊…………………………………..42
圖4.8 片段D_00001樹狀方塊能量分部圖…..…………………...…….....43
圖4.9 失真度與能量統計關係圖…...……...………………………...….....44
圖4.10 線性擬合之曲線…………………………………………...……….46
圖4.11 非線性擬合之曲線………………………………..…………...…...47
圖4.12 失真壓縮演算法流程圖…………..…………………………...…...50
圖4.13 無失真壓縮演算法流程圖………………………..…………...…...52
圖5.1 原始訊號和推導訊號的波形………...………………...…………....54
圖5.2 心電圖訊號經小波轉換後各頻帶的分佈……………..…………....56
圖5.3 以各個頻帶的關係經二維矩形小波轉換的分佈……..…………....58
圖5.4 不同壓縮方法之效能比較…...…………….....…………………......61
圖5.5 原始訊號和重建訊號的典型波形.........................….……………....62

表索引

表2-1 編碼所需的座標集合…………...……………………………..……22
表3-1 MIT/BIH Arrhythmia無失真壓縮結果………………………..……31
表3-2 MIT/BIH Arrhythmia失真壓縮結果…………………………..……32
表3-3 CSE資料庫無失真壓縮結果…………………………………..……33
表3-4 CSE資料庫失真壓縮結果……………………………………..……33
表4-1 9-7 tap濾波器的脈衝響應……………………………………..……37
表4-2 低頻帶所抽取的樹狀方塊…………...………………………..……41
表4-3 高頻帶所抽取的樹狀方塊…………...………………………..……41
表5-1 利用推導式子得到的四個導程平均失真度…………………….…53
表5-2 小波轉換層數n與樹狀向量維度之關係..……......………..…..….55
表5-3 不同的方法所需的額外標頭(位元數)..….……......………..…..….59
表5-4 在不同 下,要進行SPIHT編碼的樹狀方塊(8×8)總個數………60
表5-5 1D和2D方法效能的比較…………….…………..………………....61
表5-6 無失真之效能比較….…………..……………………………..……63
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