Weak Time-frequent Feature Enhancement Method Using Improved Ensemble Noise-reconstructed Empirical Mode Decomposition and Its Application

2016 ◽  
Vol 52 (19) ◽  
pp. 88 ◽  
Author(s):  
Jing YUAN
Keyword(s):  
Empirical Mode Decomposition ◽  
Feature Enhancement ◽  
Mode Decomposition ◽  
Enhancement Method

scholarly journals Weak Signal Enhance Based on the Neural Network Assisted Empirical Mode Decomposition

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3373
Author(s):  
Kai Chen ◽  
Kai Xie ◽  
Chang Wen ◽  
Xin-Gong Tang
Keyword(s):  
Neural Network ◽  
Empirical Mode Decomposition ◽  
Short Term Memory ◽  
Ensemble Empirical Mode Decomposition ◽  
Generative Adversarial Networks ◽  
Natural Mode ◽  
Weak Signal ◽  
Weak Signals ◽  
Mode Decomposition ◽  
Enhancement Method

In order to enhance weak signals in strong noise background, a weak signal enhancement method based on EMDNN (neural network-assisted empirical mode decomposition) is proposed. This method combines CEEMD (complementary ensemble empirical mode decomposition), GAN (generative adversarial networks) and LSTM (long short-term memory), it enhances the efficiency of selecting effective natural mode components in empirical mode decomposition, thus the SNR (signal-noise ratio) is improved. It can also reconstruct and enhance weak signals. The experimental results show that the SNR of this method is improved from 4.1 to 6.2, and the weak signal is clearly recovered.

Medical Image Enhancement Method Based on Wavelet Transform and Mode Decomposition

2013 ◽  
Vol 389 ◽  
pp. 930-935 ◽  
Author(s):  
Ao Shuang Dong ◽  
Bin Bin Lou ◽  
Hui Yan Jiang ◽  
Qiang Tong ◽  
Guang Ming Yang ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Image Enhancement ◽  
Empirical Mode Decomposition ◽  
Medical Image ◽  
Enhancement Effect ◽  
Mode Decomposition ◽  
Enhancement Method ◽  
Image Edge ◽  
Bidimensional Empirical Mode Decomposition ◽  
Medical Image Enhancement

Traditional medical image enhancement method has some disadvantages. They can not significantly improve the medical image edge, texture and detailed information. Besides the enhancement effect is susceptible to interference noise information. This paper proposed enhancement algorithms combining bidimensional empirical mode decomposition and the wavelet edge enhancement method. The first step is using the method of bidimensional empirical mode decomposition to process medical image, achieve image information with different frequency. And then our method using wavelet transform to enhance different frequency image edge, texture information. Through the comparison of proposed method with the existing method, it has been verified the proposed method has a better effect in the detail enhancement of medical images.

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