Image denoising method based on bidimensional empirical mode decomposition and mean filtering

2009 ◽  
Vol 28 (11) ◽  
pp. 2884-2886 ◽  
Author(s):  
Xiao-yong RANG ◽  
Jun-yong YE ◽  
Chun-hua GUO
Keyword(s):  
Image Denoising ◽  
Empirical Mode Decomposition ◽  
Denoising Method ◽  
Mode Decomposition ◽  
Bidimensional Empirical Mode Decomposition ◽  
Mean Filtering

scholarly journals Side-scan Sonar Image De-noising Based on Bidimensional Empirical Mode Decomposition and Non-local Means

2020 ◽  
Vol 206 ◽  
pp. 03019
Author(s):  
Kun Zhao ◽  
Jisheng Ding ◽  
YanFei Sun ◽  
ZhiYuan Hu
Keyword(s):  
Empirical Mode Decomposition ◽  
Intrinsic Mode Functions ◽  
Denoising Method ◽  
Side Scan Sonar ◽  
Sonar Image ◽  
Local Means ◽  
Residual Component ◽  
Mode Decomposition ◽  
Non Local ◽  
Bidimensional Empirical Mode Decomposition

In order to suppress the multiplicative specular noise in side-scan sonar images, a denoising method combining bidimensional empirical mode decomposition and non-local means algorithm is proposed. First, the sonar image is decomposed into intrinsic mode functions(IMF) and residual component, then the high frequency IMF is denoised by non-local mean filtering method, and finally the processed intrinsic mode functions and residual component are reconstructed to obtain the de-noised side-scan sonar image. The paper’s method is compared with the conventional filtering algorithm for experimental quantitative analysis. The results show that this method can suppress the sonar image noise and retain the detailed information of the image, which is beneficial to the later image processing.

scholarly journals A Novel Strategy to Image Decomposition for Wireless Capsule Endoscopy Images

2020 ◽  
Vol 9 (4) ◽  
pp. 535-539
Keyword(s):  
Image Denoising ◽  
Capsule Endoscopy ◽  
Image Decomposition ◽  
Wireless Capsule Endoscopy ◽  
Denoising Method ◽  
Research Article ◽  
Mode Decomposition ◽  
Novel Strategy ◽  
Bidimensional Empirical Mode Decomposition ◽  
Wireless Capsule

Now a day wireless capsule endoscopy (WCE) is broadly used for detection of gastro internal organ diseases. WCE is produces quite 55000 images but still there is challenging task of it that captured noisy images. Removing noise from images is difficult aspiration for image denoising technique. Therefore, various redundant blur and amounts of remaining noise ought to be analysis to research the particular results of denoising method. In this research article, different methods are used for image denoising and evaluated performance for wireless capsule endoscopy images. The proposed approach is suggested Bidimensional Empirical Mode Decomposition (BEMD) for WCE images. Here evaluate performance of BEMD method and wavelet. Computer simulation proved that proposed technique offer considerable advantage than other method.

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