Locating extremal curves of fringe pattern based on the wavelet transform method

2006 ◽  
Author(s):  
Alexander Belyakov
Keyword(s):  
Wavelet Transform ◽  
Fringe Pattern ◽  
Transform Method

A New Wavelet Transform Method for Optical Carrier-Fringe Pattern Phase Reconstruction

2010 ◽  
Vol 37 (12) ◽  
pp. 3060-3065 ◽  
Author(s):  
李思坤 Li Sikun ◽  
苏显渝 Su Xianyu ◽  
陈文静 Chen Wenjing
Keyword(s):  
Wavelet Transform ◽  
Fringe Pattern ◽  
Phase Reconstruction ◽  
Transform Method ◽  
Optical Carrier

Demodulation of single interferograms using a sliding 2-D continuous wavelet transform method

2015 ◽  
Vol 62 (8) ◽  
pp. 633-637 ◽  
Author(s):  
Jésus Villa ◽  
Ismael de la Rosa ◽  
Rumen Ivanov ◽  
Daniel Alaniz ◽  
Efrén González
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Continuous Wavelet ◽  
Transform Method

Study of Segmentation Threshold Based on Wavelet Transform

2013 ◽  
Vol 756-759 ◽  
pp. 3855-3859
Author(s):  
Jian Yi Li ◽  
Hui Juan Wang
Keyword(s):  
Wavelet Transform ◽  
Digital Image ◽  
Region Growing ◽  
Detection Methods ◽  
Mathematical Tool ◽  
Matlab Simulation ◽  
Segmentation Method ◽  
Transform Method ◽  
Threshold Segmentation ◽  
Digital Image Enhancement

Based on the research of the four kinds of algorithms of digital image segmentation, based on edge detection methods, based on region growing method, threshold segmentation method and digital image threshold segmentation method based on wavelet transform, using MATLAB simulation of all digital image enhancement and segmentation process, the obtained results are analyzed, proving the threshold segmentation wavelet transform method has unparalleled advantages in information extraction in medical image. Wavelet transform is a mathematical tool widely used in recent years, compared with the Fu Liye transform, the window of Fu Liye transform, wavelet transform is the local transform of space and frequency, it can be very effective in extracting information from the signal [[1.

A wavelet transform method to merge Landsat TM and SPOT panchromatic data

1998 ◽  
Vol 19 (4) ◽  
pp. 743-757 ◽  
Author(s):  
J. Zhou ◽  
D. L. Civco ◽  
J. A. Silander
Keyword(s):  
Wavelet Transform ◽  
Landsat Tm ◽  
Transform Method

Computer-aided diagnosis of diabetic subjects by heart rate variability signals using discrete wavelet transform method

2015 ◽  
Vol 81 ◽  
pp. 56-64 ◽  
Author(s):  
U. Rajendra Acharya ◽  
K. Sudarshan Vidya ◽  
Dhanjoo N. Ghista ◽  
Wei Jie Eugene Lim ◽  
Filippo Molinari ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Computer Aided Diagnosis ◽  
Discrete Wavelet ◽  
Transform Method ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals Leakage Detection in Pipeline using Wavelet Transform Method

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mohd Fairusham Ghazali ◽  
Abdul Kadir Samta
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Correlation Analysis ◽  
Pipeline System ◽  
Leakage Detection ◽  
Transient Method ◽  
Research Project ◽  
Transform Method ◽  
Cepstrum Analysis ◽  
Transient Methods

This research project is focusing on the leakage detection in the pipelines using wavelet and cepstrum analysis. To fully complete this research project, experimental and analysis by using signal processing are required. This research project proposed a technique which is a transient method. The basic principle is the fact that water spouting out of a leak in a pressurized pipe generates a signal, and this signal contains information to whether a leak exists and where it is located. The present transient methods for finding leaks are mainly based upon correlation analysis, where one sensing device is installed at each side of a leak. This method is hard to operate because it needs many operators to operate it due to equipment in different place. This research project proposed a wavelet transform method to detect leakage in the pipeline system. The experimental results show appears  to improve the ability of the method to identify features in the signal.

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