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研究生:陳宏彥
研究生(外文):Hung-yen Chen
論文名稱:Bispectrum分析用於訊號與影像之特徵量化
論文名稱(外文):Application of the Bispectral Analysis to Feature Quantification for Signals and Images
指導教授:羅佩禎羅佩禎引用關係
指導教授(外文):Pei-Chen Lo
學位類別:碩士
校院名稱:國立交通大學
系所名稱:電機與控制工程系
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:2002
畢業學年度:90
語文別:中文
論文頁數:62
中文關鍵詞:高階頻譜
外文關鍵詞:high order spectrum
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  • 點閱點閱:290
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  • 收藏至我的研究室書目清單書目收藏:1
本篇論文主要研究Chandran 與 Elgar 提出的Bispectral Invariant演算法對於特徵萃取的效能,並將它應用於一維序列與二維影像的特徵萃取。這個演算法所取得的特徵值是來自於一維序列的Bispectrum,而且對於雜訊有良好的免疫能力。而對二維影像而言,這個演算法的利用Radon transform與傅立葉切片定理(Fourier slice theorem)的理論,把影像的二維傅立葉轉換簡化為許多一維投影序列,再運用一維序列的方式處理。得到的特徵值具有對於影像的平移、旋轉、縮放皆有良好的抑制能力,即不受空間幾何變化之影響。
本論文將這個演算法應用於一維訊號與二維影像圖樣並與傳統的方法Moment Invariants比較,實驗結果顯示這個演算法不但能夠得到較好的群落特性,而且具有更佳的雜訊免疫能力。

This thesis aims to investigate the feasibility of the Bispectral Invariant algorithm, presented by Chandran and Elgar, for feature extraction and quantification. This method is to be applied to the one-dimensional(1-D) signals as well as the two-dimensional(2-D) images. The features extracted by the algorithm, providing good noise immunity, are the quantitative results of the bispectrum of a 1-D sequence. For a 2-D image, it can be reduced to a set of projected 1-D sequences via the Radon transform, or alternatively, the Fourier transform of each 1-D projection can be obtained from a radial slice of the 2-D Fourier transform of the image according to the Fourier slice theorem. The features are shown to be translation-invariant, scale-invariant, and rotation-invariant. In other words, the quantitative result are not affected by the spatial geometrical variations.
In this thesis, we also compare performance of the algorithm and that of the well-known method “moment invariants”. The results show that the bispectral invariants not only achieve better clustering characteristics but also provide superior noise immunity.

中文摘要------------------------------------------------I
英文摘要-----------------------------------------------II
目錄--------------------------------------------------III
表目錄-------------------------------------------------V
圖目錄-------------------------------------------------VI
第一章 簡介------------------------------------------ 1
1.1 背景---------------------------------------------- 1
1.2 動機---------------------------------------------- 1
1.3 章節的安排-----------------------------------------2
第二章 Bispectrum與Bispectral Invariant基本理論-------3
2.1 Bispectrum的介紹----------------------------------3
2.2 Bispectrum的性質----------------------------------3
2.3 一維序列的Bispectral Invariants------------------ 8
2.3.1 定義-----------------------------------------8
2.3.2 Bispectral Invariants的性質與說明------------9
2.4 二維序列的Bispectral Invariant--------------------13
2.4.1 二維影像的Radon Transform--------------------13
2.4.2 二維影像的傅立葉切片定理---------------------18
第三章 一維序列的處理與結果---------------------------20
3.1 直接作法------------------------------------------20
3.2 間接作法------------------------------------------22
3.3 結果與分析----------------------------------------24
第四章 二維影像的處理與結果---------------------------36
4.1 間接作法------------------------------------------36
4.2 結果與分析------------------------------------39
第五章 結論與未來展望---------------------------------58
5.1 結論----------------------------------------------58
5.2 未來展望------------------------------------------58
參考文獻----------------------------------------------60

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