Snap-shot fringe pattern enhancement using period-guided bidimensional empirical mode decomposition

2020 ◽  
Author(s):  
Paweł Gocłowski ◽  
Maciej Trusiak
Keyword(s):  
Empirical Mode Decomposition ◽  
Fringe Pattern ◽  
Mode Decomposition ◽  
Bidimensional Empirical Mode Decomposition

scholarly journals Automatic fringe pattern enhancement using truly adaptive period-guided bidimensional empirical mode decomposition

2020 ◽  
Vol 28 (5) ◽  
pp. 6277
Author(s):  
Paweł Gocłowski ◽  
Maciej Trusiak ◽  
Azeem Ahmad ◽  
Adam Styk ◽  
Vicente Mico ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Fringe Pattern ◽  
Mode Decomposition ◽  
Bidimensional Empirical Mode Decomposition

scholarly journals Texture Feature Extraction Method for Ground Nephogram Based on Hilbert Spectrum of Bidimensional Empirical Mode Decomposition

2014 ◽  
Vol 31 (9) ◽  
pp. 1982-1994 ◽  
Author(s):  
Xiaoying Chen ◽  
Aiguo Song ◽  
Jianqing Li ◽  
Yimin Zhu ◽  
Xuejin Sun ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Recognition Rate ◽  
Texture Feature ◽  
Intrinsic Mode Functions ◽  
Hilbert Spectrum ◽  
Feature Extraction Method ◽  
Hilbert Huang Transform ◽  
Mode Decomposition ◽  
Marginal Spectrum ◽  
Bidimensional Empirical Mode Decomposition

Abstract It is important to recognize the type of cloud for automatic observation by ground nephoscope. Although cloud shapes are protean, cloud textures are relatively stable and contain rich information. In this paper, a novel method is presented to extract the nephogram feature from the Hilbert spectrum of cloud images using bidimensional empirical mode decomposition (BEMD). Cloud images are first decomposed into several intrinsic mode functions (IMFs) of textural features through BEMD. The IMFs are converted from two- to one-dimensional format, and then the Hilbert–Huang transform is performed to obtain the Hilbert spectrum and the Hilbert marginal spectrum. It is shown that the Hilbert spectrum and the Hilbert marginal spectrum of different types of cloud textural images can be divided into three different frequency bands. A recognition rate of 87.5%–96.97% is achieved through random cloud image testing using this algorithm, indicating the efficiency of the proposed method for cloud nephogram.

An improved bidimensional empirical mode decomposition: A mean approach for fast decomposition

2014 ◽  
Vol 98 ◽  
pp. 344-358 ◽  
Author(s):  
Chin-Yu Chen ◽  
Shu-Mei Guo ◽  
Wei-sheng Chang ◽  
Jason Sheng-Hong Tsai ◽  
Kuo-Sheng Cheng
Keyword(s):  
Empirical Mode Decomposition ◽  
Mode Decomposition ◽  
Bidimensional Empirical Mode Decomposition ◽  
Fast Decomposition
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