Image Feature Extraction and Analysis Based on Empirical Mode Decomposition

被引：0

作者：

Huang, Shiqi ^{[1
]}

Zhang, Yucheng ^{[1
]}

Liu, Zhe ^{[1
]}

机构：

[1] Xijing Univ, Sch Informat Engn, Xian, Peoples R China

来源：

PROCEEDINGS OF 2016 IEEE ADVANCED INFORMATION MANAGEMENT, COMMUNICATES, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IMCEC 2016) | 2016年

关键词：

empirical mode decomposition; image feature; extraction; analysis; intrinsic mode function;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This Empirical mode decomposition (EMD) is a kind of multi-scale transformation theory which is suitable for nonlinear and non-stationary signal processing. It is not necessary to select the basis function in advance, and can adaptively adjust according to the characteristics of the signal itself. Extracting the intrinsic mode function (IMF) is an important process for the applications for empirical mode decomposition in one or two-dimensional image processing. The choice of decomposition scale and the extraction and selection of the intrinsic mode function are the principal and basic content for the right application and understanding. Aiming at these problems, this paper has discussed and studied them in depth, and some actual images are used to verify the feature extraction method, and the corresponding conclusions are obtained from the experimental results.

引用

页码：615 / 619

页数：5

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