The application of Hilbert-Huang Transform in two dimensional data analysis

• Main Authors: Kai-Wei Zhang, 張開維
• Other Authors: Chien-Chung Chang
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/03812663972396978689

碩士 === 國立中央大學 === 機械工程研究所 === 99 === This study focused on the application of Hilbert-Huang transform on two dimensional data and image. Fourier analysis is the most widely used data analysis method, but is limited in getting local frequency property. Hilbert Transform could be used to calculate instantaneous frequency, but is limited when applying on compound signals. Empirical mode decomposition, part of the Hilbert-Huang transform, decompose multiple component signals to sum of single component signals, can lead to correct instantaneous frequency with Hilbert transform. The recent advances of multiple dimensional ensemble empirical mode decomposition could be applied on high dimensional data and image. In this study, we first apply one- and two- dimensional empirical mode decomposition on a set of test image with different pattern feature. Then the histogram based entropy is calculated on the amplitude, phase and frequency image for the purpose of feature analysis. The results showed that multiple dimensional ensemble empirical mode decomposition is a well-performed data analysis tool.