Texture analysis based on local analysis of the bidimensional empirical mode decomposition
Texture analysis based on local analysis of the bidimensional empirical mode decomposition
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DOI：
10.1007/s00138-004-0170-5
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发表时间：
2005-05-01
影响因子：
3.3
通讯作者：
Deléchelle, E
中科院分区：
文献类型：
--
作者：
Nunes, J;Guyot, S;Deléchelle, E
我们方法的主要贡献是将Hilbert-huang变换应用于两个部分：（a）经验模式分解（EMD）和（b）希尔伯特光谱分析）对纹理分析。 EMD具有局部适应性，适合分析非线性或非平稳过程。这种一维分解技术直接从数据直接从数据中提取有限数量的振荡组件或“稳固” AM-FM函数，称为固有模式函数（IMF）。首先，我们将EMD扩展到2D-DATA（即图像），即所谓的二维EMD（BEMD），该过程称为2D-减小过程。二维效果过程分为两个步骤：通过相邻的窗口或形态算子进行极端检测，以及通过径向基础函数或多族B-Splines进行表面插值。其次，我们通过研究从每个局部信号中提取的局部特性（相位，各向同性和方向）来分析通过BEMD获得的每个2D-IMF。单基因信号是分析信号的2D将军，其中riesz变换取代了希尔伯特变换。使用BEMD和Riesz变换的这种纹理分析方法的性能通过合成图像和自然图像证明。
The main contribution of our approach is to apply the Hilbert-Huang Transform (which consists of two parts: ( a) Empirical Mode Decomposition (EMD), and (b) the Hilbert spectral analysis) to texture analysis. The EMD is locally adaptive and suitable for analysis of non-linear or non-stationary processes. This one-dimensional decomposition technique extracts a finite number of oscillatory components or "wellbehaved" AM-FM functions, called Intrinsic Mode Function ( IMF), directly from the data. Firstly, we extend the EMD to 2D-data (i.e. images), the so called bidimensional EMD (BEMD), the process being called 2D-sifting process. The 2D-sifting process is performed in two steps: extrema detection by neighboring window or morphological operators and surface interpolation by radial basis functions or multigrid B-splines. Secondly, we analyse each 2D-IMF obtained by BEMD by studying local properties ( amplitude, phase, isotropy and orientation) extracted from the monogenic signal of each one of them. The monogenic signal is a 2D-generalization of the analytic signal, where the Riesz Transform replaces the Hilbert Transform. The performance of this texture analysis method, using the BEMD and Riesz Transform, is demonstrated with both synthetic and natural images.