scholarly journals Correction to: Robust and blind image watermarking via circular embedding and bidimensional empirical mode decomposition

2020 ◽  
Author(s):  
Xiaochao Wang ◽  
Kun Hu ◽  
Jianping Hu ◽  
Ling Du ◽  
Anthony T. S. Ho ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Image Watermarking ◽  
Mode Decomposition ◽  
Bidimensional Empirical Mode Decomposition ◽  
Blind Image

Robust and blind image watermarking via circular embedding and bidimensional empirical mode decomposition

2020 ◽  
Vol 36 (10-12) ◽  
pp. 2201-2214
Author(s):  
Xiaochao Wang ◽  
Kun Hu ◽  
Jianping Hu ◽  
Ling Du ◽  
Anthony T. S. Ho ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Image Watermarking ◽  
Mode Decomposition ◽  
Bidimensional Empirical Mode Decomposition ◽  
Blind Image

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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