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Iterative shaping reconstruction algorithm based on the modulus maxima of signals' dyadic wavelet transform

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Progress in Natural Science:Materials International 2000年第8期 68-72页

作者：刘贵忠张志明冯牧张珂 China Department of Information and Communication Engineering School of Electronics and Information Engineering Xi’an 710049 Xi’an Jiaotong University

An iterative shaping reconstruction algorithm based on modulus maxima of signals’ dyadic wavelet transform is proposed. Numerical experiments show that the algorithm is of good convergence and smaller reconstruction ... 详细信息

关键词： signal reconstruction dyadic wavelet transform modulus maximum.

AN APPLIED RESEARCH ON APPROACH OF dyadic wavelet transform FOR REMOTE SENSING IMAGE EDGE DETECTION

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Journal of Electronics(China) 2006年第4期23卷 535-538页

作者： Fu Wei Xing Guangzhong Hou Lantian Qin Qiming Wang Wenjun Department of Communicaton ＆ Electricity Engineering Yanshan University Qinhuangdao 066004 China Remote Sensing Institute Peking University Beijing 100871 China

In the edge detection of Remote Sensing (RS) image, the useful detail losing and the spurious edge often appear. To solve the problem, the authors uses the dyadic wavelet to detect the edge of surface features by combining the edge detecting with the multi-resolution analyzing of the wavelet transform. Via the dyadic wavelet decomposing, the RS image of a certain appropriate scale is obtained, and the edge data of the plane and the upright directions are respectively figured out, then the gradient vector module of the surface features is worked out. By tracing them, the authors get the edge data of the object, therefore build the RS image which obtains the checked edge. This method can depress the effect of noise and examine exactly the edge data of the object by rule and line. With an experiment of an RS image which obtains an airport, the authors certificate the feasibility of the application of dyadic wavelet in the object edge detection.

关键词： dyadic wavelet transform Edge detection and tracking of Remote Sensing (RS) Object recognition

Feature Extraction and Classification of Echo Signal of Ground Penetrating Radar

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Wuhan University Journal of Natural Sciences 2005年第6期10卷 1009-1012页

作者： ZHOU Hui-lin TIAN Mao CHEN Xiao-li School of Electronic Information Wuhan University Wuhan 430072 Hubei China

Automatic feature extraction and classification algorithm of echo signal of ground penetrating radar is presented. dyadic wavelet transform and the average energy of the wavelet coefficients are applied in this paper to decompose and extract feature of the echo signal. Then, the extracted feature vector is fed up to a feed forward muhi layer perceptron classifier. Experimental results based on the measured GPR, echo signals obtained from the Mei shan railway are presented.

关键词： ground penetrating radar nonstationary signal dyadic wavelet transform feed-forward multi-layer perceptron back propagation algorithm

A New Method of CT Medical Images Contrast Enhancement

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Chinese Journal of Biomedical Engineering(English Edition) 2004年第1期13卷 28-38页

作者： SUNFeng-rong LIUWei WANGChang-yu MEILiang-mo SchoolofInformationScienceandEngineering ShandongUniversity.Jinan250100

A new method of contrast enhancement is proposed in the paper using multiscale edge representation of images, and is applied to the field of CT medical image processing. Comparing to the traditional Window technique, our method is adaptive and meets the demand of radiology clinics more better. The clinical experiment results show the practicality and the potential applied value of our method in the field of CT medical images contrast enhancement.

关键词： Contrast enhancement dyadic wavelet transform Multiscale edge representation Computed tomography

A New Pitch Detection Algorithm Based on wavelet transform

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Journal of Shanghai University(English Edition) 2005年第4期9卷 309-313页

作者：宋兵顾传青张建军 Department of Mathematics College of SciencesShanghai UniversityShanghai 200444P.R.China

In this paper, a new event detection pitch detector based on the dyadic wavelet transform was constrcted by selecting an optimal scale. The proposed pitch detector is accurate, robust to noise and computationally simple. Experiments show the superior performance of this event-based pitch detector in comparison with previous event-based pitch detector and classical pitch detectors that use the autocorrelation and the cepsmun methods to estimate the pitch period.

关键词： glottal closure instants dyadic wavelet transform pitch detection optimal scale.