Title
Novel wavelet domain Wiener filtering de-noising techniques: Application to bowel sounds captured by means of abdominal surface vibrations.
Abstract
This work focuses on the design and evaluation of efficient and accurate de-noising algorithms that combine robust signal enhancement and minimum signal distortion. The proposed method introduces novel, frequency depended, parametric, Wiener filtering techniques that involve Discrete Wavelet Transform and Wavelet Packets. Implementations of various decomposition schemes, different mother wavelets and various thresholding options were tested, while perceptual criteria were also taken into account. The introduced de-noising approach has been extensively tested on human bowel sounds, captured by means of abdominal surface vibration recordings, in order to be further utilized as a diagnostic tool. Qualitative and quantitative analysis of the method's performance, when applied to various types of recorded and synthetic sounds, revealed that the new approach works excellent with favourable results.
Year
DOI
Venue
2006
10.1016/j.bspc.2006.08.004
Biomedical Signal Processing and Control
Keywords
Field
DocType
Wavelets,Wiener filter,De-noise,Signal enhancement,Bowel sounds,Abdominal vibrations,Gastrointestinal phonography
Wiener filter,Computer vision,Pattern recognition,Continuous wavelet transform,Second-generation wavelet transform,Discrete wavelet transform,Artificial intelligence,Thresholding,Stationary wavelet transform,Wavelet packet decomposition,Mathematics,Wavelet
Journal
Volume
Issue
ISSN
1
3
1746-8094
Citations 
PageRank 
References 
14
0.82
28
Authors
4
Name
Order
Citations
PageRank
Charalampos Dimoulas110412.35
G. Kalliris227714.72
George Papanikolaou3807.07
A. Kalampakas4502.85