Wavelet transforms and their applications
Debnath, Lokenath
2015-01-01
This textbook is an introduction to wavelet transforms and accessible to a larger audience with diverse backgrounds and interests in mathematics, science, and engineering. Emphasis is placed on the logical development of fundamental ideas and systematic treatment of wavelet analysis and its applications to a wide variety of problems as encountered in various interdisciplinary areas. Numerous standard and challenging topics, applications, and exercises are included in this edition, which will stimulate research interest among senior undergraduate and graduate students. The book contains a large number of examples, which are either directly associated with applications or formulated in terms of the mathematical, physical, and engineering context in which wavelet theory arises. Topics and Features of the Second Edition: · Expanded and revised the historical introduction by including many new topics such as the fractional Fourier transform, and the construction of wavelet bases in various spaces ...
APPLICATION OF WAVELET TRANSFORM IN STRUCTURAL OPTIMIZATION
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
It is very common in structural optimization that the optima lie at or in the vicinities of the singular points of feasible domain. Therefore it is very reasonable to introduce wavelet transform that is advantageous in singularity detection. The principle and algorithm of the application of wavelet transform in structural optimization are discussed The feasibility is demonstrated by some typical examples.
Wavelet Transform and its Application to CBIR
Directory of Open Access Journals (Sweden)
Mr. V. K. Magar
2013-07-01
Full Text Available Wavelet filter bank, based on the lifting scheme framework. The lifting scheme there are two linear filters denoted Adapt a multidimensional P (prediction and U (update are defined as Neville filters of order N and Ñ, respectively. We are applying the Haar wavelet transform {&} wavelet decomposition of the image then we enter the Neville filter order {&} optimization the Neville filter. Lifting scheme on quincunx grids perform wavelet decomposition of 2-D signal (image and corresponding reconstruction tools for image as well as a function for computation of moments. The wavelet schemes rely on the lifting scheme use the splitting of rectangular grid into quincunx grid. The proposed methods apply the genetic algorithm wide range of problems, from optimization problem inductive concept learning, scheduling, and layout problem. In this project we did comparison between separable wavelet and nonseparable wavelet. We calculate the retrieval rate of separable and nonseparable.Retrieval rate is more means maximum features can be extracted. This method is applied to content-based image retrieval (CBIR an image signature is derived from this new adaptive non-separable wavelet transform. In CBIR we are used Texture feature for retrieving the image. We used 260 image databases. There are 5 classes. Images are scanned through its particular characteristics now some degree of freedom is given to the algorithm to find the image from its weight so term non-separable lifting is used and through the wavelet transformation Image primal and dual wavelet is taken into consideration for the application
Discrete wavelet transformations an elementary approach with applications
Van Fleet, Patrick
2008-01-01
An "applications first" approach to discrete wavelet transformations. Discrete Wavelet Transformations provides readers with a broad elementary introduction to discrete wavelet transformations and their applications. With extensive graphical displays, this self-contained book integrates concepts from calculus and linear algebra into the construction of wavelet transformations and their various applications, including data compression, edge detection in images, and signal and image denoising. The book begins with a cursory look at wavelet transformation development and illustrates its
Applications of a fast continuous wavelet transform
Dress, William B.
1997-04-01
A fast, continuous, wavelet transform, justified by appealing to Shannon's sampling theorem in frequency space, has been developed for use with continuous mother wavelets and sampled data sets. The method differs from the usual discrete-wavelet approach and from the standard treatment of the continuous-wavelet transform in that, here, the wavelet is sampled in the frequency domain. Since Shannon's sampling theorem lets us view the Fourier transform of the data set as representing the continuous function in frequency space, the continuous nature of the functions is kept up to the point of sampling the scale-translation lattice, so the scale-translation grid used to represent the wavelet transform is independent of the time-domain sampling of the signal under analysis. Although more computationally costly and not represented by an orthogonal basis, the inherent flexibility and shift invariance of the frequency-space wavelets are advantageous for certain applications. The method has been applied to forensic audio reconstruction, speaker recognition/identification, and the detection of micromotions of heavy vehicles associated with ballistocardiac impulses originating from occupants' heart beats. Audio reconstruction is aided by selection of desired regions in the 2D representation of the magnitude of the transformed signals. The inverse transform is applied to ridges and selected regions to reconstruct areas of interest, unencumbered by noise interference lying outside these regions. To separate micromotions imparted to a mass- spring system by an occupant's beating heart from gross mechanical motions due to wind and traffic vibrations, a continuous frequency-space wavelet, modeled on the frequency content of a canonical ballistocardiogram, was used to analyze time series taken from geophone measurements of vehicle micromotions. By using a family of mother wavelets, such as a set of Gaussian derivatives of various orders, different features may be extracted from voice
Application of wavelet transform in runoff sequence analysis
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
A wavelet transform is applied to runoff analysis to obtain the composition of the runoff sequence and to forecast future runoff. An observed runoff sequence is firstly decomposed and reconstructed by wavelet transform and its expanding tendency is derived. Then, the runoff sequence is forecasted by the back propagation artificial neural networks (BPANN) and by a wavelet transform combined with BPANN. The earlier researches seldom involve the problem of how to choose wavelet function, which is important and cannot be ignored when the wavelet transform is used. With application of the developed approach to the analysis of runoff sequence, several kinds of wavelet functions have been tested.
Higher-density dyadic wavelet transform and its application
Qin, Yi; Tang, Baoping; Wang, Jiaxu
2010-04-01
This paper proposes a higher-density dyadic wavelet transform with two generators, whose corresponding wavelet filters are band-pass and high-pass. The wavelet coefficients at each scale in this case have the same length as the signal. This leads to a new redundant dyadic wavelet transform, which is strictly shift invariant and further increases the sampling in the time dimension. We describe the definition of higher-density dyadic wavelet transform, and discuss the condition of perfect reconstruction of the signal from its wavelet coefficients. The fast implementation algorithm for the proposed transform is given as well. Compared with the higher-density discrete wavelet transform, the proposed transform is shift invariant. Applications into signal denoising indicate that the proposed wavelet transform has better denoising performance than other commonly used wavelet transforms. In the end, various typical wavelet transforms are applied to analyze the vibration signals of two faulty roller bearings, the results show that the proposed wavelet transform can more effectively extract the fault characteristics of the roller bearings than the other wavelet transforms.
Applications of a fast, continuous wavelet transform
Energy Technology Data Exchange (ETDEWEB)
Dress, W.B.
1997-02-01
A fast, continuous, wavelet transform, based on Shannon`s sampling theorem in frequency space, has been developed for use with continuous mother wavelets and sampled data sets. The method differs from the usual discrete-wavelet approach and the continuous-wavelet transform in that, here, the wavelet is sampled in the frequency domain. Since Shannon`s sampling theorem lets us view the Fourier transform of the data set as a continuous function in frequency space, the continuous nature of the functions is kept up to the point of sampling the scale-translation lattice, so the scale-translation grid used to represent the wavelet transform is independent of the time- domain sampling of the signal under analysis. Computational cost and nonorthogonality aside, the inherent flexibility and shift invariance of the frequency-space wavelets has advantages. The method has been applied to forensic audio reconstruction speaker recognition/identification, and the detection of micromotions of heavy vehicles associated with ballistocardiac impulses originating from occupants` heart beats. Audio reconstruction is aided by selection of desired regions in the 2-D representation of the magnitude of the transformed signal. The inverse transform is applied to ridges and selected regions to reconstruct areas of interest, unencumbered by noise interference lying outside these regions. To separate micromotions imparted to a mass-spring system (e.g., a vehicle) by an occupants beating heart from gross mechanical motions due to wind and traffic vibrations, a continuous frequency-space wavelet, modeled on the frequency content of a canonical ballistocardiogram, was used to analyze time series taken from geophone measurements of vehicle micromotions. By using a family of mother wavelets, such as a set of Gaussian derivatives of various orders, features such as the glottal closing rate and word and phrase segmentation may be extracted from voice data.
COMPARISON OF FOURIER AND WAVELET TRANSFORMS IN GEOPHYSICAL APPLICATIONS
Directory of Open Access Journals (Sweden)
Hakan ALP
2008-01-01
Full Text Available In this study, it was compared Fourier Transformation using widely in analysing of geophysics data and image processing and Wavelet Transformation using in image processing, boundary analysis and recently years in use geophysical data analysis. It was applicated and compared two transformations in the both geophysical data and fundamental functions. Then the results obtained were evaluated. In this study it was compared two transformation using earthquake records and Bouger gravity anomalies map of Hatay region geophysical data. At the end of the our study it was clearly seen that wavelet transform can be used by geophysical data analysing.
Application of wavelet transform to seismic data; Wavelet henkan no jishin tansa eno tekiyo
Energy Technology Data Exchange (ETDEWEB)
Nakagami, K.; Murayama, R.; Matsuoka, T. [Japan National Oil Corp., Tokyo (Japan)
1996-05-01
Introduced herein is the use of the wavelet transform in the field of seismic exploration. Among applications so far made, there are signal filtering, break point detection, data compression, and the solution of finite differential equations in the wavelet domain. In the field of data compression in particular, some examples of practical application have been introduced already. In seismic exploration, it is expected that the wavelet transform will separate signals and noises in data in a way different from the Fourier transform. The continuous wavelet transform displays time change in frequency easy to read, but is not suitable for the analysis and processing large quantities of data. On the other hand, the discrete wavelet transform, being an orthogonal transform, can handle large quantities of data. As compared with the conventional Fourier transform that handles only the frequency domain, the wavelet transform handles the time domain as well as the frequency domain, and therefore is more convenient in handling unsteady signals. 9 ref., 8 figs.
Application of the wavelet transform for speech processing
Maes, Stephane
1994-01-01
Speaker identification and word spotting will shortly play a key role in space applications. An approach based on the wavelet transform is presented that, in the context of the 'modulation model,' enables extraction of speech features which are used as input for the classification process.
Application of Wavelet Transform Techniques to Spread Spectrum Demodulation and Jamming
1993-02-26
This project has investigated the application of wavelet methods in spread spectrum communications. Use of the wavelet transform as an alternative to...signals has been explored. Direct application of the wavelet transform was found to not offer performance advantages over the Fourier transform in...this application. However, use of the wavelet transform in conjunction with Fourier methods provided an efficient hybrid framework for precise
Indian Academy of Sciences (India)
Mourad Talbi
2014-08-01
In this paper, we propose a new technique of Electrocardiogram (ECG) signal de-noising based on thresholding of the coefficients obtained from the application of the Forward Wavelet Transform Translation Invariant (FWT_TI) to each Bionic Wavelet coefficient. The De-noise De-noised ECG is obtained from the application of the inverse of BWT (BWT−1) to the de-noise de-noised bionic wavelet coefficients. For evaluating this new proposed de-noising technique, we have compared it to a thresholding technique in the FWT_TI domain. Preliminary tests of the application of the two de-noising techniques were constructed on a number of ECG signals taken from MIT-BIH database. The obtained results from Signal to Noise Ratio (SNR) and Mean Square Error (MSE) computations showed that our proposed de-noising technique outperforms the second technique. We have also compared the proposed technique to the thresholding technique in the bionic wavelet domain and this comparison was performed by SNR improvement computing. The obtained results from this evaluation showed that the proposed technique also outperforms the de-noising technique based on bionic wavelet coefficients thresholding.
Application of spline wavelet transform in differential of electroanalytical signal
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Investigating characteristics of spline wavelet, we found that if the two-order spline function, the derivative function of the three-order B spline function, is used as the wavelet base function, the spline wavelet transform has both the property of denoising and that of differential. As a result, the relation between the spline wavelet transform and the differential was studied in theory. Experimental results show that the spline wavelet transform can well be applied to the differential of the electroanalytical signal. Compared with other kinds of wavelet transform, the spline wavelet trans-form has a characteristic of differential. Compared with the digital differential and simulative differential with electronic circuit, the spline wavelet transform not only can carry out denoising and differential for a signal, but also has the ad-vantages of simple operation and small quantity of calcula-tion, because step length, RC constant and other kinds of parameters need not be selected. Compared with Alexander Kai-man Leung's differential method, the differential method with spline wavelet transform has the characteristic that the differential order is not dependent on the number of data points in the original signal.
Institute of Scientific and Technical Information of China (English)
刘希强; 周惠兰; 曹文海; 李红; 李永红; 季爱东
2002-01-01
Based on the characteristics of gradual change style seismic signal onset which has more high frequency signal components but less magnitude, this paper selects Gauss linear frequency modulation wavelet as base function to study the change characteristics of Gauss linear frequency modulation wavelet transform with difference wavelet and signal parameters, analyzes the error origin of seismic phases identification on the basis of Gauss linear frequency modulation wavelet transform, puts forward a kind of new method identifying gradual change style seismic phases with background noise which is called fixed scale wavelet transform ratio, and presents application examples about simulation digital signal and actual seismic phases recording onsets identification.
Lecture notes on wavelet transforms
Debnath, Lokenath
2017-01-01
This book provides a systematic exposition of the basic ideas and results of wavelet analysis suitable for mathematicians, scientists, and engineers alike. The primary goal of this text is to show how different types of wavelets can be constructed, illustrate why they are such powerful tools in mathematical analysis, and demonstrate their use in applications. It also develops the required analytical knowledge and skills on the part of the reader, rather than focus on the importance of more abstract formulation with full mathematical rigor. These notes differs from many textbooks with similar titles in that a major emphasis is placed on the thorough development of the underlying theory before introducing applications and modern topics such as fractional Fourier transforms, windowed canonical transforms, fractional wavelet transforms, fast wavelet transforms, spline wavelets, Daubechies wavelets, harmonic wavelets and non-uniform wavelets. The selection, arrangement, and presentation of the material in these ...
Energy Technology Data Exchange (ETDEWEB)
Bieleck, T.; Song, L.M.; Yau, S.S.T. [Univ. of Illinois, Chicago, IL (United States); Kwong, M.K. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.
1995-07-01
The concepts of random wavelet transforms and discrete random wavelet transforms are introduced. It is shown that these transforms can lead to simultaneous compression and de-noising of signals that have been corrupted with fractional noises. Potential applications of algebraic geometric coding theory to encode the ensuing data are also discussed.
Application of the cross wavelet transform and wavelet coherence to geophysical time series
Directory of Open Access Journals (Sweden)
A. Grinsted
2004-01-01
Full Text Available Many scientists have made use of the wavelet method in analyzing time series, often using popular free software. However, at present there are no similar easy to use wavelet packages for analyzing two time series together. We discuss the cross wavelet transform and wavelet coherence for examining relationships in time frequency space between two time series. We demonstrate how phase angle statistics can be used to gain confidence in causal relationships and test mechanistic models of physical relationships between the time series. As an example of typical data where such analyses have proven useful, we apply the methods to the Arctic Oscillation index and the Baltic maximum sea ice extent record. Monte Carlo methods are used to assess the statistical significance against red noise backgrounds. A software package has been developed that allows users to perform the cross wavelet transform and wavelet coherence (www.pol.ac.uk/home/research/waveletcoherence/.
Wavelet transforms and their applications to MHD and plasma turbulence: a review
Farge, Marie
2015-01-01
Wavelet analysis and compression tools are reviewed and different applications to study MHD and plasma turbulence are presented. We introduce the continuous and the orthogonal wavelet transform and detail several statistical diagnostics based on the wavelet coefficients. We then show how to extract coherent structures out of fully developed turbulent flows using wavelet-based denoising. Finally some multiscale numerical simulation schemes using wavelets are described. Several examples for analyzing, compressing and computing one, two and three dimensional turbulent MHD or plasma flows are presented.
Theory and Application of the Wavelet Transform to Signal Processing
1991-07-31
discontinuity for the function g(t), providing g(t) is of bounded variation . Theorem 2: Let g(t) E L2 (R) and i(t) E L’(R) fL 2(R). Suppose g(t) is of... bounded variation in a neighborhood of to, then the wavelet transform of 9(t) with respect to the wavelet 0(t) has the property (i) 4og(s,to) --+ 0 as s...co. (28) Now consider 12. It is sufficient to consider the case where g(t) and O(t) are real valued. Because g(t) is of bounded variation in a
2001-03-01
A unique ASIC was designed implementing the Haar Wavelet transform for image compression/decompression. ASIC operations include performing the Haar... wavelet transform on a 512 by 512 square pixel image, preparing the image for transmission by quantizing and thresholding the transformed data, and...performing the inverse Haar wavelet transform , returning the original image with only minor degradation. The ASIC is based on an existing four-chip FPGA
Energy Technology Data Exchange (ETDEWEB)
Szu, H.; Hsu, C. [Univ. of Southwestern Louisiana, Lafayette, LA (United States)
1996-12-31
Human sensors systems (HSS) may be approximately described as an adaptive or self-learning version of the Wavelet Transforms (WT) that are capable to learn from several input-output associative pairs of suitable transform mother wavelets. Such an Adaptive WT (AWT) is a redundant combination of mother wavelets to either represent or classify inputs.
Applications of continuous and orthogonal wavelet transforms to MHD and plasma turbulence
Farge, Marie; Schneider, Kai
2016-10-01
Wavelet analysis and compression tools are presented and different applications to study MHD and plasma turbulence are illustrated. We use the continuous and the orthogonal wavelet transform to develop several statistical diagnostics based on the wavelet coefficients. We show how to extract coherent structures out of fully developed turbulent flows using wavelet-based denoising and describe multiscale numerical simulation schemes using wavelets. Several examples for analyzing, compressing and computing one, two and three dimensional turbulent MHD or plasma flows are presented. Details can be found in M. Farge and K. Schneider. Wavelet transforms and their applications to MHD and plasma turbulence: A review. Support by the French Research Federation for Fusion Studies within the framework of the European Fusion Development Agreement (EFDA) is thankfully acknowledged.
Wavelet transform domain communication systems
Orr, Richard S.; Pike, Cameron; Lyall, Michael J.
1995-04-01
In this paper we introduce a new class of communications systems called wavelet transform domain (WTD) systems. WTD systems are transmultiplexer (TMUX) structures in which information to be communicated over a channel is encoded, via an inverse discrete wavelet transform (IDWT), as the wavelet coefficients of the transmitted signal, and extracted at the receiver by a discrete wavelet transform (DWT). WTD constructs can be used for covert, or low probability of intercept/detection (LPI/D) communications, baseband bandwidth efficient communications, or code-division multiple access (CDMA). This paper concentrates on the spread spectrum applications.
Adaptive wavelet transform algorithm for image compression applications
Pogrebnyak, Oleksiy B.; Manrique Ramirez, Pablo
2003-11-01
A new algorithm of locally adaptive wavelet transform is presented. The algorithm implements the integer-to-integer lifting scheme. It performs an adaptation of the wavelet function at the prediction stage to the local image data activity. The proposed algorithm is based on the generalized framework for the lifting scheme that permits to obtain easily different wavelet coefficients in the case of the (N~,N) lifting. It is proposed to perform the hard switching between (2, 4) and (4, 4) lifting filter outputs according to an estimate of the local data activity. When the data activity is high, i.e., in the vicinity of edges, the (4, 4) lifting is performed. Otherwise, in the plain areas, the (2,4) decomposition coefficients are calculated. The calculations are rather simples that permit the implementation of the designed algorithm in fixed point DSP processors. The proposed adaptive transform possesses the perfect restoration of the processed data and possesses good energy compactation. The designed algorithm was tested on different images. The proposed adaptive transform algorithm can be used for image/signal lossless compression.
The Discrete Wavelet Transform
1991-06-01
focuses on bringing together two separately motivated implementations of the wavelet transform , the algorithm a trous and Mallat’s multiresolution...decomposition. These algorithms are special cases of a single filter bank structure, the discrete wavelet transform , the behavior of which is governed by...nonorthogonal multiresolution algorithm for which the discrete wavelet transform is exact. Moreover, we show that the commonly used Lagrange a trous
Goodman, Roe W
2016-01-01
This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.It explains how to use the Fourier matrix to extract frequency information from a digital signal and how to use circulant matrices to emphasize selected frequency ranges. It introduces discrete wavelet transforms for digital signals through the lifting method and illustrates through examples and computer explorations how these transforms are used in signal and image processing. Then the general theory of discrete wavelet transforms is developed via the matrix algebra of two-channel filter banks. Finally, wavelet transforms for analog signals are constructed based on filter bank results already presented, and the mathematical framework of multiresolution analysis is examined.
Energy Technology Data Exchange (ETDEWEB)
Kingsbury, J Ng and N G [Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ (United Kingdom)
2004-02-06
This book provides an overview of the theory and practice of continuous and discrete wavelet transforms. Divided into seven chapters, the first three chapters of the book are introductory, describing the various forms of the wavelet transform and their computation, while the remaining chapters are devoted to applications in fluids, engineering, medicine and miscellaneous areas. Each chapter is well introduced, with suitable examples to demonstrate key concepts. Illustrations are included where appropriate, thus adding a visual dimension to the text. A noteworthy feature is the inclusion, at the end of each chapter, of a list of further resources from the academic literature which the interested reader can consult. The first chapter is purely an introduction to the text. The treatment of wavelet transforms begins in the second chapter, with the definition of what a wavelet is. The chapter continues by defining the continuous wavelet transform and its inverse and a description of how it may be used to interrogate signals. The continuous wavelet transform is then compared to the short-time Fourier transform. Energy and power spectra with respect to scale are also discussed and linked to their frequency counterparts. Towards the end of the chapter, the two-dimensional continuous wavelet transform is introduced. Examples of how the continuous wavelet transform is computed using the Mexican hat and Morlet wavelets are provided throughout. The third chapter introduces the discrete wavelet transform, with its distinction from the discretized continuous wavelet transform having been made clear at the end of the second chapter. In the first half of the chapter, the logarithmic discretization of the wavelet function is described, leading to a discussion of dyadic grid scaling, frames, orthogonal and orthonormal bases, scaling functions and multiresolution representation. The fast wavelet transform is introduced and its computation is illustrated with an example using the Haar
Wavelet Based Hilbert Transform with Digital Design and Application to QCM-SS Watermarking
Directory of Open Access Journals (Sweden)
S. P. Maity
2008-04-01
Full Text Available In recent time, wavelet transforms are used extensively for efficient storage, transmission and representation of multimedia signals. Hilbert transform pairs of wavelets is the basic unit of many wavelet theories such as complex filter banks, complex wavelet and phaselet etc. Moreover, Hilbert transform finds various applications in communications and signal processing such as generation of single sideband (SSB modulation, quadrature carrier multiplexing (QCM and bandpass representation of a signal. Thus wavelet based discrete Hilbert transform design draws much attention of researchers for couple of years. This paper proposes an (i algorithm for generation of low computation cost Hilbert transform pairs of symmetric filter coefficients using biorthogonal wavelets, (ii approximation to its rational coefficients form for its efficient hardware realization and without much loss in signal representation, and finally (iii development of QCM-SS (spread spectrum image watermarking scheme for doubling the payload capacity. Simulation results show novelty of the proposed Hilbert transform design and its application to watermarking compared to existing algorithms.
Discrete wavelet transform core for image processing applications
Savakis, Andreas E.; Carbone, Richard
2005-02-01
This paper presents a flexible hardware architecture for performing the Discrete Wavelet Transform (DWT) on a digital image. The proposed architecture uses a variation of the lifting scheme technique and provides advantages that include small memory requirements, fixed-point arithmetic implementation, and a small number of arithmetic computations. The DWT core may be used for image processing operations, such as denoising and image compression. For example, the JPEG2000 still image compression standard uses the Cohen-Daubechies-Favreau (CDF) 5/3 and CDF 9/7 DWT for lossless and lossy image compression respectively. Simple wavelet image denoising techniques resulted in improved images up to 27 dB PSNR. The DWT core is modeled using MATLAB and VHDL. The VHDL model is synthesized to a Xilinx FPGA to demonstrate hardware functionality. The CDF 5/3 and CDF 9/7 versions of the DWT are both modeled and used as comparisons. The execution time for performing both DWTs is nearly identical at approximately 14 clock cycles per image pixel for one level of DWT decomposition. The hardware area generated for the CDF 5/3 is around 15,000 gates using only 5% of the Xilinx FPGA hardware area, at 2.185 MHz max clock speed and 24 mW power consumption.
Wavelet transform for Fresnel-transformed mother wavelets
Institute of Scientific and Technical Information of China (English)
Liu Shu-Guang; Chen Jun-Hua; Fan Hong-Yi
2011-01-01
In this paper,we propose the so-called continuous Fresnel-wavelet combinatorial transform which means that the mother wavelet undergoes the Fresnel transformation.This motivation can let the mother-wavelet-state itself vary from |ψ〉 to Fr,s(+)｜ψ),except for variation within the family of dilations and translations.The Parseval's equality,admissibility condition and inverse transform of this continuous Fresnel-wavelet combinatorial transform are analysed.By taking certain parameters and using the admissibility condition of this continuous Fresnel-wavelet combinatorial transform,we obtain some mother wavelets.A comparison between the newly found mother wavelets is presented.
Institute of Scientific and Technical Information of China (English)
DUAN Chen-dong; JIANG Hong-kai; HE Zheng-jia
2004-01-01
In order to make trend analysis and prediction to acquisition data in a mechanical equipment condition monitoring system, a new method of trend feature extraction and prediction of acquisition data is proposed which constructs an adaptive wavelet on the acquisition data by means of second generation wavelet transform (SGWT). Firstly, taking the vanishing moment number of the predictor as a constraint, the linear predictor and updater are designed according to the acquisition data by using symmetrical interpolating scheme. Then the trend of the data is obtained through doing SGWT decomposition, threshold processing and SGWT reconstruction. Secondly, under the constraint of the vanishing moment number of the predictor, another predictor based on the acquisition data is devised to predict the future trend of the data using a non-symmetrical interpolating scheme. A one-step prediction algorithm is presented to predict the future evolution trend with historical data. The proposed method obtained a desirable effect in peak-to-peak value trend analysis for a machine set in an oil refinery.
Research on application for integer wavelet transform for lossless compression of medical image
Zhou, Zude; Li, Quan; Long, Quan
2003-09-01
This paper proposes an approach based on using lifting scheme to construct integer wavelet transform whose purpose is to realize the lossless compression of images. Then researches on application of medical image, software simulation of corresponding algorithm and experiment result are presented in this paper. Experiment shows that this method could improve the compression ration and resolution.
Power System Transients Analysis by Wavelet Transforms
Institute of Scientific and Technical Information of China (English)
陈维荣; 宋永华; 赵蔚
2002-01-01
In contrast to Fourier transform, wavelet transform is especially suitable for transient analysis because of its time-frequency characteristics with automatically-adjusted window lengths. Research shows that wavelet transform is one of the most powerful tools for power system transient analysis. The basic ideas of wavelet transform are presented in the paper together with several power system applications. It is clear that wavelet transform has some clear advantages over other transforms in detecting, analyzing, and identifying various types of power system transients.
Shukla, K K
2013-01-01
Due to its inherent time-scale locality characteristics, the discrete wavelet transform (DWT) has received considerable attention in signal/image processing. Wavelet transforms have excellent energy compaction characteristics and can provide perfect reconstruction. The shifting (translation) and scaling (dilation) are unique to wavelets. Orthogonality of wavelets with respect to dilations leads to multigrid representation. As the computation of DWT involves filtering, an efficient filtering process is essential in DWT hardware implementation. In the multistage DWT, coefficients are calculated
Target recognition by wavelet transform
Li Zheng Dong; He Wu Liang; Pei Chun Lan; Peng Wen; SongChen; Zheng Xiao Dong
2002-01-01
Wavelet transform has an important character of multi-resolution power, which presents pyramid structure, and this character coincides the way by which people distinguish object from coarse to fineness and from large to tiny. In addition to it, wavelet transform benefits to reducing image noise, simplifying calculation, and embodying target image characteristic point. A method of target recognition by wavelet transform is provided
Sarty, Gordon E.; Atkins, M. Stella; Olatunbosun, Femi; Chizen, Donna; Loewy, John; Kendall, Edward J.; Pierson, Roger A.
1999-10-01
A new numerical wavelet transform, the discrete torus wavelet transform, is described and an application is given to the denoising of abdominal magnetic resonance imaging (MRI) data. The discrete tori wavelet transform is an undecimated wavelet transform which is computed using a discrete Fourier transform and multiplication instead of by direct convolution in the image domain. This approach leads to a decomposition of the image onto frames in the space of square summable functions on the discrete torus, l2(T2). The new transform was compared to the traditional decimated wavelet transform in its ability to denoise MRI data. By using denoised images as the basis for the computation of a nuclear magnetic resonance spin-spin relaxation-time map through least squares curve fitting, an error map was generated that was used to assess the performance of the denoising algorithms. The discrete torus wavelet transform outperformed the traditional wavelet transform in 88% of the T2 error map denoising tests with phantoms and gynecologic MRI images.
Application of wavelet transform to recursive prediction of vibration signals
Institute of Scientific and Technical Information of China (English)
SUN Zhen-ming; WANG Ri-xin; JIANG Xing-wei; XU Min-qiang
2005-01-01
This paper investigates the characteristics of a non-stationary time series, which exists in mechanical fault diagnosis. Combining the characteristics with predictive efficiency, the limitation of the ARIMA model prediction method is analyzed. This model often is applied in the prediction of a non-stationary times series in present. Thus, a wavelet prediction method is introduced to solve non-stationary problems. The Mallat method,often used in signal processing, results form the decimation or the retention of one out of every two samples. Its advantage is that just enough information is kept to allow the exact reconstruction of the input series, but the disadvantage is a time-varying series on line cannot be pursued. Therefore, the authors present another method,à Trous method, which can be applied for recursive prediction in real-time sampling procedure.
2009-09-01
5 CR Cognitive Radio . . . . . . . . . . . . . . . . . . . . . . . 5 DWT Discrete Wavelet Transform . . . . . . . . . . . . . . . . . 5 AWGN...in which it is embed- ded [4,7,8,14,15,17–19,44,61]. The common approach to wavelet denoising includes: 1) transforming the input signal with the... Discrete Wavelet Transform (DWT) Figure 1.1: Tiling of Heisenberg uncertainty boxes in the time-frequency plane for STFT and DWT decompositions. The
Application of adaptive wavelet transforms via lifting in image data compression
Ye, Shujiang; Zhang, Ye; Liu, Baisen
2008-10-01
The adaptive wavelet transforms via lifting is proposed. In the transform, update filter is selected by the signal's character. Perfect reconstruction is possible without any overhead cost. To make sure the system's stability, in the lifting scheme of adaptive wavelet, update step is placed before prediction step. The Adaptive wavelet transforms via lifting is benefit for the image compression, because of the high stability, the small coefficients of high frequency parts, and the perfect reconstruction. With the adaptive wavelet transforms via lifting and the SPIHT, the image compression is realized in this paper, and the result is pleasant.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
We introduce the bipartite entangled states to present a quantum mechanical version of complex wavelet transform. Using the technique of integral within an ordered product of operators we show that the complex wavelet transform can be studied in terms of various quantum state vectors in two-mode Fock space. In this way the creterion for mother wavelet can be examined quantum-mechanically and therefore more deeply.
Wavelets theory, algorithms, and applications
Montefusco, Laura
2014-01-01
Wavelets: Theory, Algorithms, and Applications is the fifth volume in the highly respected series, WAVELET ANALYSIS AND ITS APPLICATIONS. This volume shows why wavelet analysis has become a tool of choice infields ranging from image compression, to signal detection and analysis in electrical engineering and geophysics, to analysis of turbulent or intermittent processes. The 28 papers comprising this volume are organized into seven subject areas: multiresolution analysis, wavelet transforms, tools for time-frequency analysis, wavelets and fractals, numerical methods and algorithms, and applicat
Ng, J.; Kingsbury, N. G.
2004-02-01
This book provides an overview of the theory and practice of continuous and discrete wavelet transforms. Divided into seven chapters, the first three chapters of the book are introductory, describing the various forms of the wavelet transform and their computation, while the remaining chapters are devoted to applications in fluids, engineering, medicine and miscellaneous areas. Each chapter is well introduced, with suitable examples to demonstrate key concepts. Illustrations are included where appropriate, thus adding a visual dimension to the text. A noteworthy feature is the inclusion, at the end of each chapter, of a list of further resources from the academic literature which the interested reader can consult. The first chapter is purely an introduction to the text. The treatment of wavelet transforms begins in the second chapter, with the definition of what a wavelet is. The chapter continues by defining the continuous wavelet transform and its inverse and a description of how it may be used to interrogate signals. The continuous wavelet transform is then compared to the short-time Fourier transform. Energy and power spectra with respect to scale are also discussed and linked to their frequency counterparts. Towards the end of the chapter, the two-dimensional continuous wavelet transform is introduced. Examples of how the continuous wavelet transform is computed using the Mexican hat and Morlet wavelets are provided throughout. The third chapter introduces the discrete wavelet transform, with its distinction from the discretized continuous wavelet transform having been made clear at the end of the second chapter. In the first half of the chapter, the logarithmic discretization of the wavelet function is described, leading to a discussion of dyadic grid scaling, frames, orthogonal and orthonormal bases, scaling functions and multiresolution representation. The fast wavelet transform is introduced and its computation is illustrated with an example using the Haar
Polygiannakis, J; Moussas, X
2003-01-01
We show that the continuous wavelet transform can provide a unique decomposition of a timeseries in to 'signal-like' and 'noise-like' components: From the overall wavelet spectrum two mutually independent skeleton spectra can be extracted, allowing the separate detection and monitoring in even non-stationary timeseries of the evolution of (a) both stable but also transient, evolving periodicities, such as the output of low dimensional dynamical systems and (b) scale-invariant structures, such as discontinuities, self-similar structures or noise. An indicative application to the monthly-averaged sunspot index reveals, apart from the well-known 11-year periodicity, 3 of its harmonics, the 2-year periodicity (quasi-biennial oscillation, QBO) and several more (some of which detected previously in various solar, earth-solar connection and climate indices), here proposed being just harmonics of the QBO, in all supporting the double-cycle solar magnetic dynamo model (Benevolenskaya, 1998, 2000). The scale maximal sp...
Application of the wavelet transforms on axial strain calculation in ultrasound elastography
Institute of Scientific and Technical Information of China (English)
LUO Jianwen; BAI Jing; SHAO Jinhua
2006-01-01
In ultrasound elastography, the axial strain distribution within biological tissues is calculated as the numerical derivative (differentiation) of the estimated axial displacement field. Unfortunately, the numerical derivative is unstable because it can greatly amplify the noises, especially at high frequencies. This work focuses on the axial strain calculation from the estimated axial displacements using wavelet transforms (WTs), including continuous wavelet transforms (CWTs) and discrete wavelet transforms (DWTs). The feasibility of the WT-based method using the quadratic spline function is verified by computer simulations and some phantom data. Results indicate that the WT-based method can effectively reduce the noise amplification in axial strain calculation.
Application of wavelet transforms as a time-series analysis tool for nuclear thermalhydraulics
Energy Technology Data Exchange (ETDEWEB)
Pohl, D.J.; Pascoe, J.; Popescu, A.I., E-mail: daniel.pohl@amec.com, E-mail: jason.pascoe@amec.com, E-mail: adrian.popescu@amec.com [AMEC NSS Limited, Toronto, Ontario (Canada)
2011-07-01
Wavelet transforms can be a valuable time-series analysis tool in the field of nuclear thermalhydraulics. As an example, the Morlet wavelet transform can be used to reduce the aleatory (random) uncertainty of a voiding transient in a large loss of coolant accident (LOCA). The wavelet transform is used to determine the cutoff frequency for a low pass Butterworth filter in order to remove the noisy part of the signal without infringing upon the characteristic frequencies of the phenomenon. This technique successfully reduced the standard random uncertainty by 42.4%. (author)
Directory of Open Access Journals (Sweden)
Teresa Sibillano
2010-04-01
Full Text Available The plasma optical radiation emitted during CO2 laser welding of stainless steel samples has been detected with a Si-PIN photodiode and analyzed under different process conditions. The discrete wavelet transform (DWT has been used to decompose the optical signal into various discrete series of sequences over different frequency bands. The results show that changes of the process settings may yield different signal features in the range of frequencies between 200 Hz and 30 kHz. Potential applications of this method to monitor in real time the laser welding processes are also discussed.
Sibillano, Teresa; Ancona, Antonio; Rizzi, Domenico; Lupo, Valentina; Tricarico, Luigi; Lugarà, Pietro Mario
2010-01-01
The plasma optical radiation emitted during CO2 laser welding of stainless steel samples has been detected with a Si-PIN photodiode and analyzed under different process conditions. The discrete wavelet transform (DWT) has been used to decompose the optical signal into various discrete series of sequences over different frequency bands. The results show that changes of the process settings may yield different signal features in the range of frequencies between 200 Hz and 30 kHz. Potential applications of this method to monitor in real time the laser welding processes are also discussed. PMID:22319311
Wavelet-fractional Fourier transforms
Institute of Scientific and Technical Information of China (English)
Yuan Lin
2008-01-01
This paper extends the definition of fractional Fourier transform (FRFT) proposed by Namias V by using other orthonormal bases for L2 (R) instead of Hermite-Ganssian functions.The new orthonormal basis is gained indirectly from multiresolution analysis and orthonormal wavelets. The so defined FRFT is called wavelets-fractional Fourier transform.
Institute of Scientific and Technical Information of China (English)
Zhao Bin; Quan Taifan; Wang Jinrong
2005-01-01
The imaging and target detection methods for stepped frequency signal based on the wavelet transform and its power spectrum are investigated. Not only an imaging and target detection algorithm for stepped frequency signal based on the wavelet transform, but also its respective power spectrum are proposed. The multisampling property of stepped frequency signal is studied and wavelet transform is well suited for analyzing the signal. After multisampling property of stepped frequency signal being studied, it is shown that the wavelet transform is appropriate to analyze the signal. Based on the theory, the wavelet power spectrum analysis is applied to obtain the target range profile and the binary wavelet transform is used to perform target detection. To determine a suitable wavelet scaling for imaging of range profile' s MMW radar, the distance resolution △R technique is proposed. The effectiveness of this new method is evaluated using simulated noisy radar signal. Results show that the proposed method can bring out the exactness and low computational complexity of this method.
Optical encryption with cascaded fractional wavelet transforms
Institute of Scientific and Technical Information of China (English)
BAO Liang-hua; CHEN Lin-fei; ZHAO Dao-mu
2006-01-01
On the basis of fractional wavelet transform, we propose a new method called cascaded fractional wavelet transform to encrypt images. It has the virtues of fractional Fourier transform and wavelet transform. Fractional orders, standard focal lengths and scaling factors are its keys. Multistage fractional Fourier transforms can add the keys easily and strengthen information security. This method can also realize partial encryption just as wavelet transform and fractional wavelet transform. Optical realization of encryption and decryption is proposed. Computer simulations confirmed its possibility.
Application of dual tree complex wavelet transform in tandem mass spectrometry.
Murugesan, Selvaraaju; Tay, David B H; Cooke, Ira; Faou, Pierre
2015-08-01
Mass Spectrometry (MS) is a widely used technique in molecular biology for high throughput identification and sequencing of peptides (and proteins). Tandem mass spectrometry (MS/MS) is a specialised mass spectrometry technique whereby the sequence of peptides can be determined. Preprocessing of the MS/MS data is indispensable before performing any statistical analysis on the data. In this work, preprocessing of MS/MS data is proposed based on the Dual Tree Complex Wavelet Transform (DTCWT) using almost symmetric Hilbert pair of wavelets. After the preprocessing step, the identification of peptides is done using the database search approach. The performance of the proposed preprocessing technique is evaluated by comparing its performance against Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT). The preprocessing performed using DTCWT identified more peptides compared to DWT and SWT.
Fast algorithm of byte-to-byte wavelet transform for image compression applications
Pogrebnyak, Oleksiy B.; Sossa Azuela, Juan H.; Ramirez, Pablo M.
2002-11-01
A new fast algorithm of 2D DWT transform is presented. The algorithm operates on byte represented images and performs image transformation with the Cohen-Daubechies-Feauveau wavelet of the second order. It uses the lifting scheme for the calculations. The proposed algorithm is based on the "checkerboard" computation scheme for non-separable 2D wavelet. The problem of data extension near the image borders is resolved computing 1D Haar wavelet in the vicinity of the borders. With the checkerboard splitting, at each level of decomposition only one detail image is produced that simplify the further analysis for data compression. The calculations are rather simple, without any floating point operation allowing the implementation of the designed algorithm in fixed point DSP processors for fast, near real time processing. The proposed algorithm does not possesses perfect restoration of the processed data because of rounding that is introduced at each level of decomposition/restoration to perform operations with byte represented data. The designed algorithm was tested on different images. The criterion to estimate quantitatively the quality of the restored images was the well known PSNR. For the visual quality estimation the error maps between original and restored images were calculated. The obtained simulation results show that the visual and quantitative quality of the restored images is degraded with number of decomposition level increasing but is sufficiently high even after 6 levels. The introduced distortion are concentrated in the vicinity of high spatial activity details and are absent in the homogeneous regions. The designed algorithm can be used for image lossy compression and in noise suppression applications.
Adaptive boxcar/wavelet transform
Sezer, Osman G.; Altunbasak, Yucel
2009-01-01
This paper presents a new adaptive Boxcar/Wavelet transform for image compression. Boxcar/Wavelet decomposition emphasizes the idea of average-interpolation representation which uses dyadic averages and their interpolation to explain a special case of biorthogonal wavelet transforms (BWT). This perspective for image compression together with lifting scheme offers the ability to train an optimum 2-D filter set for nonlinear prediction (interpolation) that will adapt to the context around the low-pass wavelet coefficients for reducing energy in the high-pass bands. Moreover, the filters obtained after training is observed to posses directional information with some textural clues that can provide better prediction performance. This work addresses a firrst step towards obtaining this new set of training-based fillters in the context of Boxcar/Wavelet transform. Initial experimental results show better subjective quality performance compared to popular 9/7-tap and 5/3-tap BWTs with comparable results in objective quality.
Generalized Tree-Based Wavelet Transform
Ram, Idan; Cohen, Israel
2010-01-01
In this paper we propose a new wavelet transform applicable to functions defined on graphs, high dimensional data and networks. The proposed method generalizes the Haar-like transform proposed in \\cite{gavish2010mwot}, and it is similarly defined via a hierarchical tree, which is assumed to capture the geometry and structure of the input data. It is applied to the data using a multiscale filtering and decimation scheme, which can employ different wavelet filters. We propose a tree construction method which results in efficient representation of the input function in the transform domain. We show that the proposed transform is more efficient than both the 1D and 2D separable wavelet transforms in representing images. We also explore the application of the proposed transform to image denoising, and show that combined with a subimage averaging scheme, it achieves denoising results which are similar to the ones obtained with the K-SVD algorithm.
The convolution theorem for two-dimensional continuous wavelet transform
Institute of Scientific and Technical Information of China (English)
ZHANG CHI
2013-01-01
In this paper , application of two -dimensional continuous wavelet transform to image processes is studied. We first show that the convolution and correlation of two continuous wavelets satisfy the required admissibility and regularity conditions ,and then we derive the convolution and correlation theorem for two-dimensional continuous wavelet transform. Finally, we present numerical example showing the usefulness of applying the convolution theorem for two -dimensional continuous wavelet transform to perform image restoration in the presence of additive noise.
Application of Wavelets Transform to Fault Detection in Rotorcraft UAV Sensor Failure
Institute of Scientific and Technical Information of China (English)
Jun-tong Qi; Jian-da Han
2007-01-01
This paper describes a novel wavelet-based approach to the detection of abrupt fault of Rotorcraft Unmanned Aerial Vehicle (RUAV) sensor system. By use of wavelet transforms that accurately localize the characteristics of a signal both in the time and frequency domains, the occurring instants of abnormal status of a sensor in the output signal can be identified by the multi-scale representation of the signal. Once the instants are detected, the distribution differences of the signal energy on all decomposed wavelet scales of the signal before and after the instants are used to claim and classify the sensor faults.
Wang, Dongqing; Zhang, Xu; Chen, Xiang; Zhou, Ping
2014-01-01
Myoelectric pattern recognition applied to high-density surface electromyographic (sEMG) recordings from paretic muscles has been proven to identify various movement intents of stroke survivors, thus facilitating the design of myoelectrically controlled robotic systems for recovery of upper-limb dexterity. Aiming at effectively decoding neural control information under the condition of neurological injury following stroke, this paper further investigates the application of wavelet packet transform (WPT) on myoelectric feature extraction to identify 20 functional movements performed by the paretic upper limb of 4 chronic stroke subjects. The WPT was used to decompose the original sEMG signals via a tree of subspaces, where optimal ones were selected in term of the classification efficacy. The energies in the selected subspaces were calculated as optimal wavelet packet features, which were finally fed into a linear discriminant classifier. The WPT-based myoelectric feature extraction approach achieved accuracies above 94% for all subjects in a user-specific condition, demonstrating its potential applications in upper limb rehabilitation after stroke.
The berkeley wavelet transform: a biologically inspired orthogonal wavelet transform.
Willmore, Ben; Prenger, Ryan J; Wu, Michael C-K; Gallant, Jack L
2008-06-01
We describe the Berkeley wavelet transform (BWT), a two-dimensional triadic wavelet transform. The BWT comprises four pairs of mother wavelets at four orientations. Within each pair, one wavelet has odd symmetry, and the other has even symmetry. By translation and scaling of the whole set (plus a single constant term), the wavelets form a complete, orthonormal basis in two dimensions. The BWT shares many characteristics with the receptive fields of neurons in mammalian primary visual cortex (V1). Like these receptive fields, BWT wavelets are localized in space, tuned in spatial frequency and orientation, and form a set that is approximately scale invariant. The wavelets also have spatial frequency and orientation bandwidths that are comparable with biological values. Although the classical Gabor wavelet model is a more accurate description of the receptive fields of individual V1 neurons, the BWT has some interesting advantages. It is a complete, orthonormal basis and is therefore inexpensive to compute, manipulate, and invert. These properties make the BWT useful in situations where computational power or experimental data are limited, such as estimation of the spatiotemporal receptive fields of neurons.
Wavelet transforms as solutions of partial differential equations
Energy Technology Data Exchange (ETDEWEB)
Zweig, G.
1997-10-01
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Wavelet transforms are useful in representing transients whose time and frequency structure reflect the dynamics of an underlying physical system. Speech sound, pressure in turbulent fluid flow, or engine sound in automobiles are excellent candidates for wavelet analysis. This project focused on (1) methods for choosing the parent wavelet for a continuous wavelet transform in pattern recognition applications and (2) the more efficient computation of continuous wavelet transforms by understanding the relationship between discrete wavelet transforms and discretized continuous wavelet transforms. The most interesting result of this research is the finding that the generalized wave equation, on which the continuous wavelet transform is based, can be used to understand phenomena that relate to the process of hearing.
Directory of Open Access Journals (Sweden)
Sayadi Omid
2007-01-01
Full Text Available We present a new modified wavelet transform, called the multiadaptive bionic wavelet transform (MABWT, that can be applied to ECG signals in order to remove noise from them under a wide range of variations for noise. By using the definition of bionic wavelet transform and adaptively determining both the center frequency of each scale together with the -function, the problem of desired signal decomposition is solved. Applying a new proposed thresholding rule works successfully in denoising the ECG. Moreover by using the multiadaptation scheme, lowpass noisy interference effects on the baseline of ECG will be removed as a direct task. The method was extensively clinically tested with real and simulated ECG signals which showed high performance of noise reduction, comparable to those of wavelet transform (WT. Quantitative evaluation of the proposed algorithm shows that the average SNR improvement of MABWT is 1.82 dB more than the WT-based results, for the best case. Also the procedure has largely proved advantageous over wavelet-based methods for baseline wandering cancellation, including both DC components and baseline drifts.
Werdiningsih, Indah; Zaman, Badrus; Nuqoba, Barry
2017-08-01
This paper presents classification of brain cancer using wavelet transformation and Adaptive Neighborhood Based Modified Backpropagation (ANMBP). Three stages of the processes, namely features extraction, features reduction, and classification process. Wavelet transformation is used for feature extraction and ANMBP is used for classification process. The result of features extraction is feature vectors. Features reduction used 100 energy values per feature and 10 energy values per feature. Classifications of brain cancer are normal, alzheimer, glioma, and carcinoma. Based on simulation results, 10 energy values per feature can be used to classify brain cancer correctly. The correct classification rate of proposed system is 95 %. This research demonstrated that wavelet transformation can be used for features extraction and ANMBP can be used for classification of brain cancer.
Application of the dual-tree complex wavelet transform in biomedical signal denoising.
Wang, Fang; Ji, Zhong
2014-01-01
In biomedical signal processing, Gibbs oscillation and severe frequency aliasing may occur when using the traditional discrete wavelet transform (DWT). Herein, a new denoising algorithm based on the dual-tree complex wavelet transform (DTCWT) is presented. Electrocardiogram (ECG) signals and heart sound signals are denoised based on the DTCWT. The results prove that the DTCWT is efficient. The signal-to-noise ratio (SNR) and the mean square error (MSE) are used to compare the denoising effect. Results of the paired samples t-test show that the new method can remove noise more thoroughly and better retain the boundary and texture of the signal.
Institute of Scientific and Technical Information of China (English)
Duan Chendong; He Zhengjia; Jiang Hongkai
2004-01-01
A new time-domain analysis method that uses second generation wavelet transform (SGWT) for weak fault feature extraction is proposed. To extract incipient fault feature, a biorthogonal wavelet with the characteristics of impact is constructed by using SGWT. Processing detail signal of SGWT with a sliding window devised on the basis of rotating operation cycle, and extracting modulus maximum from each window, fault features in time-domain are highlighted. To make further analysis on the reason of the fault, wavelet package transform based on SGWT is used to process vibration data again. Calculating the energy of each frequency-band, the energy distribution features of the signal are attained. Then taking account of the fault features and the energy distribution, the reason of the fault is worked out. An early impact-rub fault caused by axis misalignment and rotor imbalance is successfully detected by using this method in an oil refinery.
Liu, Shoubing; Lu, Wenke; Zhu, Changchun
2017-11-01
The goal of this research is to study two-port network of wavelet transform processor (WTP) using surface acoustic wave (SAW) devices and its application. The motive was prompted by the inconvenience of the long research and design cycle and the huge research funding involved with traditional method in this field, which were caused by the lack of the simulation and emulation method of WTP using SAW devices. For this reason, we introduce the two-port network analysis tool, which has been widely used in the design and analysis of SAW devices with uniform interdigital transducers (IDTs). Because the admittance parameters calculation formula of the two-port network can only be used for the SAW devices with uniform IDTs, this analysis tool cannot be directly applied into the design and analysis of the processor using SAW devices, whose input interdigital transducer (IDT) is apodized weighting. Therefore, in this paper, we propose the channel segmentation method, which can convert the WTP using SAW devices into parallel channels, and also provide with the calculation formula of the number of channels, the number of finger pairs and the static capacitance of an interdigital period in each parallel channel firstly. From the parameters given above, we can calculate the admittance parameters of the two port network for each channel, so that we can obtain the admittance parameter of the two-port network of the WTP using SAW devices on the basis of the simplification rule of parallel two-port network. Through this analysis tool, not only can we get the impulse response function of the WTP using SAW devices but we can also get the matching circuit of it. Large numbers of studies show that the parameters of the two-port network obtained by this paper are consistent with those measured by network analyzer E5061A, and the impulse response function obtained by the two-port network analysis tool is also consistent with that measured by network analyzer E5061A, which can meet the
Image fusion using wavelet transform and its application to asymmetric cryptosystem and hiding.
Mehra, Isha; Nishchal, Naveen K
2014-03-10
Image fusion is a popular method which provides better quality fused image for interpreting the image data. In this paper, color image fusion using wavelet transform is applied for securing data through asymmetric encryption scheme and image hiding. The components of a color image corresponding to different wavelengths (red, green, and blue) are fused together using discrete wavelet transform for obtaining a better quality retrieved color image. The fused color components are encrypted using amplitude- and phase-truncation approach in Fresnel transform domain. Also, the individual color components are transformed into different cover images in order to result disguising information of input image to an attacker. Asymmetric keys, Fresnel propagation parameters, weighing factor, and three cover images provide enlarged key space and hence enhanced security. Computer simulation results support the idea of the proposed fused color image encryption scheme.
Local Extrema of Periodic Function's Wavelet Transform
Institute of Scientific and Technical Information of China (English)
FAN Qi-bin; SONG Xiao-yan
2005-01-01
The theory of detecting ridges in the modulus of the continuous wavelet transform is presented as well as reconstructing signal by using information on ridges. To periodic signal we suppose Morlet wavelet as basic wavelet, and research the local extreme point and extrema of the wavelet transform on periodic function for the collection of signal's instantaneous amplitude and period.
Wavelet Transform Signal Processing Applied to Ultrasonics.
1995-05-01
THE WAVELET TRANSFORM IS APPLIED TO THE ANALYSIS OF ULTRASONIC WAVES FOR IMPROVED SIGNAL DETECTION AND ANALYSIS OF THE SIGNALS. In instances where...the mother wavelet is well defined, the wavelet transform has relative insensitivity to noise and does not need windowing. Peak detection of...ultrasonic pulses using the wavelet transform is described and results show good detection even when large white noise was added. The use of the wavelet
AN EFFICIENT 3-DIMENSIONAL DISCRETE WAVELET TRANSFORM ARCHITECTURE FOR VIDEO PROCESSING APPLICATION
Institute of Scientific and Technical Information of China (English)
Ganapathi Hegde; Pukhraj Vaya
2012-01-01
This paper presents an optimized 3-D Discrete Wavelet Transform (3-DDWT) architecture.1-DDWT employed for the design of 3-DDWT architecture uses reduced lifting scheme approach.Further the architecture is optimized by applying block enabling technique,scaling,and rounding of the filter coefficients.The proposed architecture uses biorthogonal (9/7) wavelet filter.The architecture is modeled using Verilog HDL,simulated using ModelSim,synthesized using Xilinx ISE and finally implemented on Virtex-5 FPGA.The proposed 3-DDWT architecture has slice register utilization of 5％,operating frequency of 396 MHz and a power consumption of 0.45 W.
APPLICATION OF TWO-DIMENSIONAL WAVELET TRANSFORM IN NEAR-SHORE X-BAND RADAR IMAGES
Institute of Scientific and Technical Information of China (English)
FENG Xiang-bo; YAN Yi-xin; ZHANG Wei
2011-01-01
Among existing remote sensing applications, land-based X-band radar is an effective technique to monitor the wave fields,and spatial wave information could be obtained from the radar images.Two-dimensional Fourier Transform (2-D FT) is the common algorithm to derive the spectra of radar images.However, the wave field in the nearshore area is highly non-homogeneous due to wave refraction, shoaling, and other coastal mechanisms.When applied in nearshore radar images, 2-D FT would lead to ambiguity of wave characteristics in wave number domain.In this article, we introduce two-dimensional Wavelet Transform (2-D WT) to capture the non-homogeneity of wave fields from nearshore radar images.The results show that wave number spectra by 2-D WT at six parallel space locations in the given image clearly present the shoaling of nearshore waves.Wave number of the peak wave energy is increasing along the inshore direction, and dominant direction of the spectra changes from South South West (SSW) to West South West (WSW).To verify the results of2-D WT, wave shoaling in radar images is calculated based on dispersion relation.The theoretical calculation results agree with the results of 2-D WT on the whole.The encouraging performance of 2-D WT indicates its strong capability of revealing the non-homogeneity of wave fields in nearshore X-band radar images.
Application of 3D wavelet transforms for crack detection in rotor systems
Indian Academy of Sciences (India)
C Nagaraju; K Narayana Rao; K Mallikarjuna Rao
2009-06-01
The dynamics and diagnostics of a cracked rotor have been gaining importance in recent years. The early detection of faults like fatigue cracks in rotor shafts are very important to prevent catastrophic failure of the rotor system. Vibration monitoring during start up or shut-down is as important as during steady state operation to detect cracks especially for machines such as aircraft engines which start and stop quite frequently and run at high speeds. So, the transient data of the cracked rotor has been transformed using the wavelet transforms for crack detection. Most of the works quoted in the literature used 1D wavelets or 2D wavelets (Continuous Wavelet Transform-CWT) for crack detection. The crack detectors in the signals are both time as well as frequency dependent. So, the use of 2D wavelets is also not enough to detect the crack. In the present work a 3D wavelet (CWT) has been utilized which clearly indicates both the time and frequency features of the crack. The presence of sub-criticals in the CWT may be a best crack indicator but it is not always reliable. The addition of noise to the signal may sometimes lead to inaccurate results. So, there is a need to identify a parameter in addition to the sub-criticals. The phase angle between the two signals (cracked and un-cracked) or two transverse vibrations can be a better crack indicator because it is very less sensitive to noise disturbance. So, to extract the above phase angle a new transform has been applied called Cross Wavelet Transform (XWT). The XWT is exploited for the ﬁrst time to a rotor fault detection system in the present work. Some interesting results have been obtained using the same. The advantage of the XWT is that both, the phase angles between the transverse signals and also the amplitudes of sub-criticals are viewed in a single plot. Parametric analysis is also carried out by varying crack depth and crack position for diagnostic purposes. The inverse problem of crack identi
Wavelets associated with Hankel transform and their Weyl transforms
Institute of Scientific and Technical Information of China (English)
PENG; Lizhong; MA; Ruiqin
2004-01-01
The Hankel transform is an important transform. In this paper, westudy the wavelets associated with the Hankel transform, thendefine the Weyl transform of the wavelets. We give criteria of itsboundedness and compactness on the Lp-spaces.
Asymptotic expansion of the wavelet transform with error term
Pathak, R.S.; Pathak, Ashish
2014-01-01
UsingWong's technique asymptotic expansion for the wavelet transform is derived and thereby asymptotic expansions for Morlet wavelet transform, Mexican Hat wavelet transform and Haar wavelet transform are obtained.
Wavelet transform in electrocardiography--data compression.
Provazník, I; Kozumplík, J
1997-06-01
An application of the wavelet transform to electrocardiography is described in the paper. The transform is used as a first stage of a lossy compression algorithm for efficient coding of rest ECG signals. The proposed technique is based on the decomposition of the ECG signal into a set of basic functions covering the time-frequency domain. Thus, non-stationary character of ECG data is considered. Some of the time-frequency signal components are removed because of their low influence to signal characteristics. Resulting components are efficiently coded by quantization, composition into a sequence of coefficients and compression by a run-length coder and a entropic Huffman coder. The proposed wavelet-based compression algorithm can compress data to average code length about 1 bit/sample. The algorithm can be also implemented to a real-time processing system when wavelet transform is computed by fast linear filters described in the paper.
Canbay, Ferhat; Levent, Vecdi Emre; Serbes, Gorkem; Ugurdag, H Fatih; Goren, Sezer; Aydin, Nizamettin
2016-09-01
The authors aimed to develop an application for producing different architectures to implement dual tree complex wavelet transform (DTCWT) having near shift-invariance property. To obtain a low-cost and portable solution for implementing the DTCWT in multi-channel real-time applications, various embedded-system approaches are realised. For comparison, the DTCWT was implemented in C language on a personal computer and on a PIC microcontroller. However, in the former approach portability and in the latter desired speed performance properties cannot be achieved. Hence, implementation of the DTCWT on a reconfigurable platform such as field programmable gate array, which provides portable, low-cost, low-power, and high-performance computing, is considered as the most feasible solution. At first, they used the system generator DSP design tool of Xilinx for algorithm design. However, the design implemented by using such tools is not optimised in terms of area and power. To overcome all these drawbacks mentioned above, they implemented the DTCWT algorithm by using Verilog Hardware Description Language, which has its own difficulties. To overcome these difficulties, simplify the usage of proposed algorithms and the adaptation procedures, a code generator program that can produce different architectures is proposed.
Wavelet Analyses and Applications
Bordeianu, Cristian C.; Landau, Rubin H.; Paez, Manuel J.
2009-01-01
It is shown how a modern extension of Fourier analysis known as wavelet analysis is applied to signals containing multiscale information. First, a continuous wavelet transform is used to analyse the spectrum of a nonstationary signal (one whose form changes in time). The spectral analysis of such a signal gives the strength of the signal in each…
The Application Wavelet Transform Algorithm in Testing ADC Effective Number of Bits
Directory of Open Access Journals (Sweden)
Emad A. Awada
2013-10-01
Full Text Available In evaluating Analog to Digital Convertors, many parameters are checked for performance and error rate.One of these parameters is the device Effective Number of Bits. In classical testing of Effective Number ofBits, testing is based on signal to noise components ratio (SNR, whose coefficients are driven viafrequency domain (Fourier Transform of ADC’s output signal. Such a technique is extremely sensitive tonoise and require large number of data samples. That is, longer and more complex testing process as thedevice under test increases in resolutions. Meanwhile, a new time – frequency domain approach (known asWavelet transform is proposed to measure and analyze Analog-to-Digital Converters parameter ofEffective Number of Bits with less complexity and fewer data samples.In this work, the algorithm of Wavelet transform was used to estimate worst case Effective Number of Bitsand compare the new testing results with classical testing methods. Such an algorithm, Wavelet transform,have shown DSP testing process improvement in terms of time and computations complexity based on itsspecial properties of multi-resolutions.
Comparison of wavelet and Karhunen-Loeve transforms in video compression applications
Musatenko, Yurij S.; Soloveyko, Olexandr M.; Kurashov, Vitalij N.
1999-12-01
In the paper we present comparison of three advanced techniques for video compression. Among them 3D Embedded Zerotree Wavelet (EZW) coding, recently suggested Optimal Image Coding using Karhunen-Loeve (KL) transform (OICKL) and new algorithm of video compression based on 3D EZW coding scheme but with using KL transform for frames decorrelation (3D-EZWKL). It is shown that OICKL technique provides the best performance and usage of KL transform with 3D-EZW coding scheme gives better results than just usage of 3D-EZW algorithm.
The Application of Wavelet Transform in Analysis of Digital Precursory Observational Data
Institute of Scientific and Technical Information of China (English)
Song Zhiping; Wu Anxu; Wang Wei; Geng Jie; Song Xianyue; Ni Youzhong; Zhu Jiamiao; Kan Daoling
2004-01-01
Digital data of precursors is noted for its high accuracy. Therefore, it is important to extract the high frequency information from the low ones in the digital data of precursors and to discriminate between the trend anomalies and the short-term anomalies. This paper presents a method to separate the high frequency information from the low ones by using the wavelet transform to analyze the digital data of precursors, and illustrates with examples the train of thoughts of discriminating the short-term anomalies from trend anomalies by using the wavelet transform, thus provide a new effective approach for extracting the short-term and trend anomalies from the digital data of precursors.
Application of wavelet transform de-noising in pole identification of a system
Institute of Scientific and Technical Information of China (English)
CHEN Shi-Guo; ZHANG Ruan-Yu; WANG Peng; LI Tai-Hua
2004-01-01
Due to the multiscale character of wavelet transform, the method of wavelet transform de-noising (WTDN) is introduced. The WTDN method neither requires extra limit of frequency range for the processed signal,nor needs a prior estimate of impulse response for an identified system, so it is especially suitable to de-noise the wide-band signal and the impulse response of a blind system. The numerical simulation results indicate that the WTDN method is reliable. The WTDN method was used to process the sampled data from a preamplifier coupled to a gas detector. The experimental results also show that the WTDN method can effectively improve the SNR of sampled data and enhance the accuracy in pole identification of the system.
A DNA Structure-Based Bionic Wavelet Transform and Its Application to DNA Sequence Analysis
Directory of Open Access Journals (Sweden)
Fei Chen
2003-01-01
Full Text Available DNA sequence analysis is of great significance for increasing our understanding of genomic functions. An important task facing us is the exploration of hidden structural information stored in the DNA sequence. This paper introduces a DNA structure-based adaptive wavelet transform (WT – the bionic wavelet transform (BWT – for DNA sequence analysis. The symbolic DNA sequence can be separated into four channels of indicator sequences. An adaptive symbol-to-number mapping, determined from the structural feature of the DNA sequence, was introduced into WT. It can adjust the weight value of each channel to maximise the useful energy distribution of the whole BWT output. The performance of the proposed BWT was examined by analysing synthetic and real DNA sequences. Results show that BWT performs better than traditional WT in presenting greater energy distribution. This new BWT method should be useful for the detection of the latent structural features in future DNA sequence analysis.
A novel application of wavelet based SVM to transient phenomena identification of power transformers
Energy Technology Data Exchange (ETDEWEB)
Jazebi, S., E-mail: jazebi@aut.ac.i [Department of Electrical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Vahidi, B., E-mail: vahidi@aut.ac.i [Department of Electrical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Jannati, M., E-mail: M.jannati@uok.ac.i [Department of Electrical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)
2011-02-15
A novel differential protection approach is introduced in the present paper. The proposed scheme is a combination of Support Vector Machine (SVM) and wavelet transform theories. Two common transients such as magnetizing inrush current and internal fault are considered. A new wavelet feature is extracted which reduces the computational cost and enhances the discrimination accuracy of SVM. Particle swarm optimization technique (PSO) has been applied to tune SVM parameters. The suitable performance of this method is demonstrated by simulation of different faults and switching conditions on a power transformer in PSCAD/EMTDC software. The method has the advantages of high accuracy and low computational burden (less than a quarter of a cycle). The other advantage is that the method is not dependent on a specific threshold. Sympathetic and recovery inrush currents also have been simulated and investigated. Results show that the proposed method could remain stable even in noisy environments.
Low-power Analog VLSI Implementation of Wavelet Transform
Institute of Scientific and Technical Information of China (English)
ZHANG Jiang-hong
2009-01-01
For applications requiring low-power, low-voltage and real-time, a novel analog VLSI implementation of continuous Marr wavelet transform based on CMOS log-domain integrator is proposed.Mart wavelet is approximated by a parameterized class of function and with Levenbery-Marquardt nonlinear least square method,the optimum parameters of this function are obtained.The circuits of implementating Mart wavelet transform are composed of analog filter whose impulse response is the required wavelet.The filter design is based on IFLF structure with CMOS log-domain integrators as the main building blocks.SPICE simulations indicate an excellent approximations of ideal wavelet.
A Mellin transform approach to wavelet analysis
Alotta, Gioacchino; Di Paola, Mario; Failla, Giuseppe
2015-11-01
The paper proposes a fractional calculus approach to continuous wavelet analysis. Upon introducing a Mellin transform expression of the mother wavelet, it is shown that the wavelet transform of an arbitrary function f(t) can be given a fractional representation involving a suitable number of Riesz integrals of f(t), and corresponding fractional moments of the mother wavelet. This result serves as a basis for an original approach to wavelet analysis of linear systems under arbitrary excitations. In particular, using the proposed fractional representation for the wavelet transform of the excitation, it is found that the wavelet transform of the response can readily be computed by a Mellin transform expression, with fractional moments obtained from a set of algebraic equations whose coefficient matrix applies for any scale a of the wavelet transform. Robustness and computationally efficiency of the proposed approach are shown in the paper.
Directory of Open Access Journals (Sweden)
Lifeng Wang
2015-01-01
Full Text Available The method based on the continuous wavelet transformation to detect and characterize two-dimensional vortex is analyzed for a synthetic flow and applied to vortex detection of propeller wake. The characteristics of a vortex, such as center location, core radius, and circulation, are extracted based on the Lamb-Oseen and Rankine vortex models, the latter of which is a novel attempt. The effects of various factors such as the difference scheme, the grid and scale discretization, transform variable, and vortex model on vortex detection have been investigated thoroughly. The method is further applied to identify the tip vortex in a propeller wake.
GPS Receiver Performance Inspection by Wavelet Transform
Institute of Scientific and Technical Information of China (English)
Xia Lin-yuan; Liu Jing-nan; Lu Liang-xi
2003-01-01
As a powerful analysis tool and the result of contemporary mathematics development, wavelet transform has shown its promising application potentials through the research in the paper. Three aspects regarding GPS receiver performance is tackled: cycle slip detection, receiver noise analysis and receiver channel bias inspection. Wavelet decomposition for double differential observation has demonstrated that this multi-level transform can reveal cycle slips as small as 0.5 cycles without any pre-adjustment processes or satellite orbit information, it can therefore be regarded as a 'geometry free' method. Based on property assumption of receiver noise, signal of noise serial is obtained at the high frequency scale in wavelet decomposition layers. This kind of noise influence on GPSb aseline result can be effectively eliminated by reconstruction process during wavelet reconstruction. Through observed data analysis, the transform has detected a kind of receiver channel bias that has not been completely removed by processing unit of GPS receiver during clock offset resetting operation. Thus the wavelet approach can be employed as a kind of system diagnosis in a generalized point of view.
Fedi, M.; Primiceri, R.; Quarta, T.; Villani, A. V.
2004-01-01
The discrete wavelet transform (dwt), using the good property of localization of wavelet bases has been used as a powerful tool in filtering and denoising problems. The continuous wavelet transform (cwt) exploits the upward continuation properties of the field horizontal derivative and allows the location of potential field singularities in a simple geometrical manner. Within the cwt space-scale framework, the lines formed by joining, at different scales, the modulus maxima of the wavelet coefficients (multiscale edge detection method) intersect each other at the position of the point source or along the edges of the causative body. As long as the multiscale edge detection method is applied to experimental data the procedure may, however, fail, since the observed anomalies are the superposition of effects of sources having different density contrast, geometrical size and depths. We show that wavelet transform modulus maxima lines attributed to deep sources do not converge toward the true depths, but yield completely erroneous solutions. On the other hand, use of nth-order derivatives of the potential field allows the enhancement of the shallowest source effects, preventing us from obtaining information on the deeper ones. In this paper we therefore try to overcome this problem by a joint application of cwt and dwt. A localized dwt filter coupled to compactness criterion allows the separation of the effects due to the deeper sources from those of the shallower ones. Hence, the multiscale edge detection method, applied separately to the original and the filtered signals enabled the estimation of the depth of shallower and deeper sources, respectively. This analysis, performed on the gravity anomalies of Sardinia (Italy), has given estimations of the depths to both the Campidano graben and the Moho discontinuity, in good agreement with previous interpretations of gravity and seismic data.
Chouakri, S. A.; Djaafri, O.; Taleb-Ahmed, A.
2013-08-01
We present in this work an algorithm for electrocardiogram (ECG) signal compression aimed to its transmission via telecommunication channel. Basically, the proposed ECG compression algorithm is articulated on the use of wavelet transform, leading to low/high frequency components separation, high order statistics based thresholding, using level adjusted kurtosis value, to denoise the ECG signal, and next a linear predictive coding filter is applied to the wavelet coefficients producing a lower variance signal. This latter one will be coded using the Huffman encoding yielding an optimal coding length in terms of average value of bits per sample. At the receiver end point, with the assumption of an ideal communication channel, the inverse processes are carried out namely the Huffman decoding, inverse linear predictive coding filter and inverse discrete wavelet transform leading to the estimated version of the ECG signal. The proposed ECG compression algorithm is tested upon a set of ECG records extracted from the MIT-BIH Arrhythmia Data Base including different cardiac anomalies as well as the normal ECG signal. The obtained results are evaluated in terms of compression ratio and mean square error which are, respectively, around 1:8 and 7%. Besides the numerical evaluation, the visual perception demonstrates the high quality of ECG signal restitution where the different ECG waves are recovered correctly.
Gu, Junhua; Wang, Jingying; An, Tao; Chen, Wen
2013-01-01
We propose a continuous wavelet transform based non-parametric foreground subtraction method for the detection of redshifted 21 cm signal from the epoch of reionization. This method works based on the assumption that the foreground spectra are smooth in frequency domain, while the 21 cm signal spectrum is full of saw-tooth-like structures, thus their characteristic scales are significantly different. We can distinguish them in the wavelet coefficient space easily and perform the foreground subtraction. Compared with the traditional spectral fitting based method, our method is more tolerant to complex foregrounds. Furthermore, we also find that when the instrument has uncorrected response error, our method can also work significantly better than the spectral fitting based method. Our method can obtain similar results with the Wp smoothing method, which is also a non-parametric method, but our method consumes much less computing time.
Wavelet Transforms using VTK-m
Energy Technology Data Exchange (ETDEWEB)
Li, Shaomeng [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Sewell, Christopher Meyer [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-09-27
These are a set of slides that deal with the topics of wavelet transforms using VTK-m. First, wavelets are discussed and detailed, then VTK-m is discussed and detailed, then wavelets and VTK-m are looked at from a performance comparison, then from an accuracy comparison, and finally lessons learned, conclusion, and what is next. Lessons learned are the following: Launching worklets is expensive; Natural logic of performing 2D wavelet transform: Repeat the same 1D wavelet transform on every row, repeat the same 1D wavelet transform on every column, invoke the 1D wavelet worklet every time: num_rows x num_columns; VTK-m approach of performing 2D wavelet transform: Create a worklet for 2D that handles both rows and columns, invoke this new worklet only one time; Fast calculation, but cannot reuse 1D implementations.
Digital Watermarking in Wavelet Transform Domain
Directory of Open Access Journals (Sweden)
D. Levicky
2001-06-01
Full Text Available This paper presents a technique for the digital watermarking ofstill images based on the wavelet transform. The watermark (binaryimage is embedded into original image in its wavelet domain. Theoriginal unmarked image is required for watermark extraction. Themethod of embedding of digital watermarks in wavelet transform domainwas analyzed and verified on grey scale static images.
EEG Signal Decomposition and Improved Spectral Analysis Using Wavelet Transform
2001-10-25
research and medical applications. Wavelet transform (WT) is a new multi-resolution time-frequency analysis method. WT possesses localization feature both... wavelet transform , the EEG signals are successfully decomposed and denoised. In this paper we also use a ’quasi-detrending’ method for classification of EEG
Institute of Scientific and Technical Information of China (English)
ZHANG Xinming; HE Yongyong; HAO Rujiang; CHU Fulei
2007-01-01
Morlet wavelet is suitable to extract the impulse components of mechanical fault signals.And thus its continuous wavelet transform (CWT) has been successfully used in the field of fault diagnosis. The principle of scale selection in CWT is discussed. Based on genetic algorithm, an optimization strategy for the waveform parameters of the mother wavelet is proposed with wavelet entropy as the optimization target. Based on the optimized waveform parameters, the wavelet scalogram is used to analyze the simulated acoustic emission (AE) signal and real AE signal of rolling bearing.The results indicate that the proposed method is useful and efficient to improve the quality of CWT.
Saini, Shiwani; Dewan, Lillie
2016-01-01
This paper highlights the potential of discrete wavelet transforms in the analysis and comparison of genomic sequences of Mycobacterium tuberculosis (MTB) with different resistance characteristics. Graphical representations of wavelet coefficients and statistical estimates of their parameters have been used to determine the extent of similarity between different sequences of MTB without the use of conventional methods such as Basic Local Alignment Search Tool. Based on the calculation of the energy of wavelet decomposition coefficients of complete genomic sequences, their broad classification of the type of resistance can be done. All the given genomic sequences can be grouped into two broad categories wherein the drug resistant and drug susceptible sequences form one group while the multidrug resistant and extensive drug resistant sequences form the other group. This method of segregation of the sequences is faster than conventional laboratory methods which require 3-4 weeks of culture of sputum samples. Thus the proposed method can be used as a tool to enhance clinical diagnostic investigations in near real-time.
Directory of Open Access Journals (Sweden)
Thirion N.
2006-11-01
Full Text Available The wavelet transform can be used to develop the process which allows group and phase velocity measurement of dispersive waves. The method has been applied to acoustic data to measure formation velocities. The behavior and the accuracy of the method have been checked on synthetic full waveform acoustic data. The method was applied to dispersive waves of the Stoneley type and to flexural modes whose low frequency components are propagated at the formation shear velocity. A raw measurement of the phase velocity of a flexural mode gives an estimate of the shear velocity with an error of about 5%. The use of a wavelet transform yields an accurate study of dispersion and gives a shear velocity measurement with an error of less than 1 %. However, all the examples presented here are based on the use of synthetic data, which are not corrupted by noise and were obtained with a numerical model. This algorithm is complete, to the extent in which it enables simulation of all the seismic arrivals for the considered geometry (cylindrical borehole with a circular section, in an homogeneous medium. Nevertheless, such a model remains a simplified version of what will occur in reality, when the irregularities of the borehole, the cementing defects and the background noise may call into question the excellent precision of the results obtained. The process which is described in this paper must be seen as one possible method for the analysis of field data, but it still has to be applied to many recordings of field data before its effectiveness can really be proved. Les analyses Temps-Fréquence caractérisant un signal dans le plan Temps-Fréquence permettent d'obtenir une bonne localisation des composantes spectrales du signal analysé aussi bien dans le domaine fréquentiel que dans le domaine temporel. Dans ce contexte, la théorie des ondelettes sert de base à différentes méthodes développées dans le cadre d'applications variées en traitement du signal. Le
Spatial Verification Using Wavelet Transforms: A Review
Weniger, Michael; Friederichs, Petra
2016-01-01
Due to the emergence of new high resolution numerical weather prediction (NWP) models and the availability of new or more reliable remote sensing data, the importance of efficient spatial verification techniques is growing. Wavelet transforms offer an effective framework to decompose spatial data into separate (and possibly orthogonal) scales and directions. Most wavelet based spatial verification techniques have been developed or refined in the last decade and concentrate on assessing forecast performance (i.e. forecast skill or forecast error) on distinct physical scales. Particularly during the last five years, a significant growth in meteorological applications could be observed. However, a comparison with other scientific fields such as feature detection, image fusion, texture analysis, or facial and biometric recognition, shows that there is still a considerable, currently unused potential to derive useful diagnostic information. In order to tab the full potential of wavelet analysis, we revise the stat...
Ghlaifan, Abdulatef; Tounsi, Yassine; Zada, Sara; Muhire, Desire; Nassim, Abdelkrim
2016-12-01
A method for optical phase extraction based on two-dimensional discrete wavelets transform (2-DWT) decomposition is shown. From modulated fringe pattern, phase distribution is extracted by the ratio between detail and approximation. Modulation process is realized digitally by introducing high-frequency spatial carrier, and this process needs two π/2-shifted fringe patterns. We propose to use only single fringe and generate its quadrature by spiral phase transform (SPT). After validation by computer simulation, we apply the 2-DWT algorithm on experimental speckle fringe correlation taken for hard disk surface. The extracted phase using SPT quadrature was compared with that given using this time experimental quadrature, and we show a good performance by multiscale structural similarity metric.
Complex Wavelet Transform-Based Face Recognition
Directory of Open Access Journals (Sweden)
2009-03-01
Full Text Available Complex approximately analytic wavelets provide a local multiscale description of images with good directional selectivity and invariance to shifts and in-plane rotations. Similar to Gabor wavelets, they are insensitive to illumination variations and facial expression changes. The complex wavelet transform is, however, less redundant and computationally efficient. In this paper, we first construct complex approximately analytic wavelets in the single-tree context, which possess Gabor-like characteristics. We, then, investigate the recently developed dual-tree complex wavelet transform (DT-CWT and the single-tree complex wavelet transform (ST-CWT for the face recognition problem. Extensive experiments are carried out on standard databases. The resulting complex wavelet-based feature vectors are as discriminating as the Gabor wavelet-derived features and at the same time are of lower dimension when compared with that of Gabor wavelets. In all experiments, on two well-known databases, namely, FERET and ORL databases, complex wavelets equaled or surpassed the performance of Gabor wavelets in recognition rate when equal number of orientations and scales is used. These findings indicate that complex wavelets can provide a successful alternative to Gabor wavelets for face recognition.
Implementing wavelet transform with SAW elements
Institute of Scientific and Technical Information of China (English)
LU; Wenke(卢文科); ZHU; Changchun(朱长纯); LIU; Junhua(刘君华); LIU; Qinghong(刘清洪)
2003-01-01
In the design of the finger-overlap envelope according to the envelope of wavelet function, it is concluded that the pulse-response function of the interdigital transducer (IDT) for surface acoustic wave (SAW) is identical to the wavelet function. SAW type of the wavelet-transform element is manufactured. A new method of using two wavelet-transform elements to manufacture the reconstruction element of the wavelet transform is proposed. The sources of the element error are analyzed, and the methods for reducing the error are put forward. SAW type of the wavelet transformation element and its reconstruction element have the following three characteristics: (i) the implementing methods of the wavelet transform element and its reconstruction element are simple, and free of complicated mathematical algorithms of the wavelet transform; (ii) because one of SAW element is fast, the response velocities of SAW type of the wavelet transform element and its reconstruction element are also fast; (iii) the costs of the wavelet transform element and its reconstruction element are low, so the elements may be manufactured in a large quantity.
Wavelet transform of neural spike trains
Kim, Youngtae; Jung, Min Whan; Kim, Yunbok
2000-02-01
Wavelet transform of neural spike trains recorded with a tetrode in the rat primary somatosensory cortex is described. Continuous wavelet transform (CWT) of the spike train clearly shows singularities hidden in the noisy or chaotic spike trains. A multiresolution analysis of the spike train is also carried out using discrete wavelet transform (DWT) for denoising and approximating at different time scales. Results suggest that this multiscale shape analysis can be a useful tool for classifying the spike trains.
Vaudor, Lise; Piegay, Herve; Wawrzyniak, Vincent; Spitoni, Marie
2016-04-01
The form and functioning of a geomorphic system result from processes operating at various spatial and temporal scales. Longitudinal channel characteristics thus exhibit complex patterns which vary according to the scale of study, might be periodic or segmented, and are generally blurred by noise. Describing the intricate, multiscale structure of such signals, and identifying at which scales the patterns are dominant and over which sub-reach, could help determine at which scales they should be investigated, and provide insights into the main controlling factors. Wavelet transforms aim at describing data at multiple scales (either in time or space), and are now exploited in geophysics for the analysis of nonstationary series of data. They provide a consistent, non-arbitrary, and multiscale description of a signal's variations and help explore potential causalities. Nevertheless, their use in fluvial geomorphology, notably to study longitudinal patterns, is hindered by a lack of user-friendly tools to help understand, implement, and interpret them. We have developed a free application, The Wavelet ToolKat, designed to facilitate the use of wavelet transforms on temporal or spatial series. We illustrate its usefulness describing longitudinal channel curvature and slope of three freely meandering rivers in the Amazon basin (the Purus, Juruá and Madre de Dios rivers), using topographic data generated from NASA's Shuttle Radar Topography Mission (SRTM) in 2000. Three types of wavelet transforms are used, with different purposes. Continuous Wavelet Transforms are used to identify in a non-arbitrary way the dominant scales and locations at which channel curvature and slope vary. Cross-wavelet transforms, and wavelet coherence and phase are used to identify scales and locations exhibiting significant channel curvature and slope co-variations. Maximal Overlap Discrete Wavelet Transforms decompose data into their variations at a series of scales and are used to provide
The fast wavelet X-ray transform
R.A. Zuidwijk; P.M. de Zeeuw (Paul)
1999-01-01
textabstractThe wavelet X-ray transform computes one-dimensional wavelet transforms along lines in Euclidian space in order to perform a directional time-scale analysis of functions in several variables. A fast algorithm is proposed which executes this transformation starting with values given on a
Application of Cauchy wavelet transformation to identify time-variant modal parameters of structures
Huang, C. S.; Liu, C. Y.; Su, W. C.
2016-12-01
This work proposes a procedure for accurately identifying instantaneous modal parameters of a linear time-varying system using a time-varying autoregressive with exogenous input (TVARX) model with the continuous Cauchy wavelet transform (CCWT). An appropriate TVARX model is established using the velocity and displacement responses of the system under consideration. The time-varying coefficients of the TVARX are expanded as piecewise polynomial functions. CCWTs with various scale parameters are then applied to the TVARX model to evaluate the instantaneous modal parameters of different modes. The CCWTs of the velocity and displacement responses are analytically obtained from the CCWT of the measured acceleration responses. The effectiveness and accuracy of the proposed procedure are validated by numerical simulations of single and multiple degrees of freedom systems that have periodically varying and sharply varying stiffness and damping coefficients. The effects of noise, the Cauchy wavelet function and the order of the polynomial on the evaluation of the modal parameters are explored in processing the numerically simulated acceleration responses of systems with a single degree of freedom subjected to base excitation. Finally, the proposed procedure is adopted to determine the modal parameters of a five-story symmetric steel frame from its measured acceleration responses in a shaking table test. The measured strains reveal the yielding of columns in the first story. The variations of the identified instantaneous natural frequencies and modal damping ratios with time are consistent with the physical phenomena that are observed from the measured strains and base excitation acceleration.
Haar wavelets with applications
Lepik, Ülo
2014-01-01
This is the first book to present a systematic review of applications of the Haar wavelet method for solving Calculus and Structural Mechanics problems. Haar wavelet-based solutions for a wide range of problems, such as various differential and integral equations, fractional equations, optimal control theory, buckling, bending and vibrations of elastic beams are considered. Numerical examples demonstrating the efficiency and accuracy of the Haar method are provided for all solutions.
Hardware Architectures for the Orthogonal and Biorthogonal Wavelet Transform
Directory of Open Access Journals (Sweden)
G. Knowles
2002-01-01
Full Text Available In this note, optimal hardware architectures for the orthogonal and biorthogonal wavelet transforms are presented. The approach used here is not the standard lifting method, but takes advantage of the symmetries inherent in the coefficients of the transforms and the decimation/interpolation operators. The design is based on a highly optimized datapath, which seamlessly integrates both orthogonal and biorthogonal transforms, data extension at the edges and the forward and inverse transforms. The datapath design could be further optimized for speed or low power. The datapath is controlled by a small fast control unit which is hard programmed according to the wavelet or wavelets required by the application.
Directory of Open Access Journals (Sweden)
Rogelio Ramos
2017-01-01
Full Text Available The present work discusses the problem of induced external electrical noise as well as its removal from the electrical potential obtained from Scanning Vibrating Electrode Technique (SVET in the pitting corrosion process of aluminum alloy A96061 in 3.5% NaCl. An accessible and efficient solution of this problem is presented with the use of virtual instrumentation (VI, embedded systems, and the discrete wavelet transform (DWT. The DWT is a computational algorithm for digital processing that allows obtaining electrical noise with Signal to Noise Ratio (SNR superior to those obtained with Lock-In Amplifier equipment. The results show that DWT and the threshold method are efficient and powerful alternatives to carry out electrical measurements of potential signals from localized corrosion processes measured by SVET.
Spatial verification using wavelet transforms: a review
Weniger, Michael; Kapp, Florian; Friederichs, Petra
2017-01-01
Due to the emergence of new high resolution numerical weather prediction (NWP) models and the availability of new or more reliable remote sensing data, the importance of efficient spatial verification techniques is growing. Wavelet transforms offer an effective framework to decompose spatial data into separate (and possibly orthogonal) scales and directions. Most wavelet based spatial verification techniques have been developed or refined in the last decade and concentrate on assessing forecast performance (i.e. forecast skill or forecast error) on distinct physical scales. Particularly during the last five years, a significant growth in meteorological applications could be observed. However, a comparison with other scientific fields such as feature detection, image fusion, texture analysis, or facial and biometric recognition, shows that there is still a considerable, currently unused potential to derive useful diagnostic information. In order to tab the full potential of wavelet analysis, we revise the state-of-the art in one- and two-dimensional wavelet analysis and its application with emphasis on spatial verification. We further use a technique developed for texture analysis in the context of high-resolution quantitative precipitation forecasts, which is able to assess structural characteristics of the precipitation fields and allows efficient clustering of ensemble data.
Entangled Husimi distribution and Complex Wavelet transformation
Hu, Li-yun
2009-01-01
Based on the proceding Letter [Int. J. Theor. Phys. 48, 1539 (2009)], we expand the relation between wavelet transformation and Husimi distribution function to the entangled case. We find that the optical complex wavelet transformation can be used to study the entangled Husimi distribution function in phase space theory of quantum optics. We prove that the entangled Husimi distribution function of a two-mode quantum state |phi> is just the modulus square of the complex wavelet transform of exp{-(|eta|^2)/2} with phi(eta)being the mother wavelet up to a Gaussian function.
Peak Detection Using Wavelet Transform
Directory of Open Access Journals (Sweden)
Omar Daoud
2014-07-01
Full Text Available A new work based-wavelet transform is designed to o vercome one of the main drawbacks that found in the present new technologies. Orthogonal Frequency Divi sion Multiplexing (OFDMis proposed in the literature to enhance the multimedia resolution. Ho wever, the high peak power (PAPR values will obstr uct such achievements. Therefore, a new proposition is found in this work, making use of the wavelet transforms methods, and it is divided into three ma in stages; de-noising stage, thresholding stage and then the replacement stage. In order to check the system stages validity; a mat hematical model has been built and its checked afte r using a MATLAB simulation. A simulated bit error ra te (BER achievement will be compared with our previously published work, where an enhancement fro m 8×10 -1 to be 5×10 -1 is achieved. Moreover, these results will be compared to the work found in the l iterature, where we have accomplished around 27% PAPR extra reduction. As a result, the BER performance has been improved for the same bandwidth occupancy. Moreover and due to the de-noise stage, the verification rate ha s been improved to reach 81%. This is in addition t o the noise immunity enhancement.
Realization of Wavelet Transform Using SAW Devices
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Based on the characteristics of surface acoustic wave(SAW) devices, the theory for realizing wavelet transform (WT) by SAW is deduced. Simulated experiment shows that the method of implementing WT using SAW devices has virtues of high speed and utility and is compatible with digital technique. It is important to implement wavelet transform.
APPLICATION OF WAVELET TRANSFORM ON DIAGNOSIS AND PREDICTION OF MILLING CHATTER
Institute of Scientific and Technical Information of China (English)
WANG Shih-Ming; LUO Ming-Je; LIN Sheng-Yu; LIAO Hung-Wei
2007-01-01
In order to avoid the accuracy deterioration or tool damage caused by milling chatter, it is necessary to have an efficient and reliable diagnosis system that can on-line predict/detect the occurrence of chatter. The diagnosis/predicting system proposed is to on-line process and analysis the vibration signals of the milling machine measured by accelerometers. According to the analysis results,the system will be able to detect/predict the occurrence of the chatter. The diagnosis algorithm is, first,collecting both the normal signals and chatter signals from milling processes, and then, converting the signals through wavelet transform and fast Fourier transform (FFT). Since the converted chatter signals exhibit different characteristics from the normal signals, through defining the characteristic values, such as root-mean-square value, max value, and ratio of peak value to root-mean-square value,etc, a diagnosis reference library that contains the distribution of these characteristic values is built for diagnosis. When a diagnosis is executing, the characteristic value of the measured signals is contrasted with the diagnosis reference. The approach index which shows the possibility of occurrence of milling chatter will, then, be calculated through the diagnosis system. Cutting experiments are conducted to verify the proposed diagnosis system. The results show the success of early chatter detecting for the system.
An Approach to 2D Wavelet Transform and Its Use for Image Compression
Directory of Open Access Journals (Sweden)
R. Vargic
1998-12-01
Full Text Available In this paper is constructed a new type of two-dimensional wavelet transform. Construction is based on lifting scheme. We transform 1D wavelets with symmetrical factorisation to their 2D counterparts. Comparison to existing similar 2D wavelet constructions is given. Application for image compression is given using progressive (SP1HT and classical type transform coder.
An Approach to Integer Wavelet Transform for Medical Image Compression in PACS
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
We study an approach to integer wavelet transform for lossless compression of medical image in medical picture archiving and communication system (PACS). By lifting scheme a reversible integer wavelet transform is generated, which has the similar features with the corresponding biorthogonal wavelet transform. Experimental results of the method based on integer wavelet transform are given to show better performance and great applicable potentiality in medical image compression.
Shi, Fei; Wang, Beibei; Selesnick, Ivan W.; Wang, Yao
2006-01-01
This paper introduces an anisotropic decomposition structure of a recently introduced 3-D dual-tree discrete wavelet transform (DDWT), and explores the applications for video denoising and coding. The 3-D DDWT is an attractive video representation because it isolates motion along different directions in separate subbands, and thus leads to sparse video decompositions. Our previous investigation shows that the 3-D DDWT, compared to the standard discrete wavelet transform (DWT), complies better with the statistical models based on sparse presumptions, and gives better visual and numerical results when used for statistical denoising algorithms. Our research on video compression also shows that even with 4:1 redundancy, the 3-D DDWT needs fewer coefficients to achieve the same coding quality (in PSNR) by applying the iterative projection-based noise shaping scheme proposed by Kingsbury. The proposed anisotropic DDWT extends the superiority of isotropic DDWT with more directional subbands without adding to the redundancy. Unlike the original 3-D DDWT which applies dyadic decomposition along all three directions and produces isotropic frequency spacing, it has a non-uniform tiling of the frequency space. By applying this structure, we can improve the denoising results, and the number of significant coefficients can be reduced further, which is beneficial for video coding.
Research on ghost imaging method based on wavelet transform
Li, Mengying; He, Ruiqing; Chen, Qian; Gu, Guohua; Zhang, Wenwen
2017-09-01
We present an algorithm of extracting the wavelet coefficients of object based on ghost imaging (GI) system. Through modification of the projected random patterns by using a series of templates, wavelet transform GI (WTGI) can directly measure the high frequency components of wavelet coefficients without needing the original image. In this study, we theoretically and experimentally perform the high frequency components of wavelet coefficients detection with an arrow and a letter A based on GI and WTGI. Comparing with the traditional method, the use of the algorithm proposed in this paper can significantly improve the quality of the image of wavelet coefficients in both cases. The special advantages of GI will make the wavelet coefficient detection based on WTGI very valuable in real applications.
IDENTIFICATION OF CRACKED ROTOR BY WAVELET TRANSFORM
Institute of Scientific and Technical Information of China (English)
邹剑; 陈进; 蒲亚鹏
2002-01-01
The dynamic equation of cracked rotor in rotational frame was modelled, the numerical simulation solutions of the cracked rotor and the uncracked rotor were obtained. By the wavelet transform, the time-frequency properties of the cracked rotor and the uncracked rotor were discussed, the difference of the time-frequency properties between the cracked rotor and the uncracked rotor was compared. A new detection algorithm using wavelet transform to identify crack was proposed. The experiments verify the availability and validity of the wavelet transform in identification of crack.
Random seismic noise attenuation using the Wavelet Transform
Aliouane, L.; Ouadfeul, S.; Boudella, A.; Eladj, S.
2012-04-01
In this paper we propose a technique of random noises attenuation from seismic data using the discrete and continuous wavelet transforms. Firstly the discrete wavelet transform (DWT) is applied to denoise seismic data. This last is based on the threshold method applied at the modulus of the DWT. After we calculate the continuous wavelet transform of the denoised seismic seismogram, the final denoised seismic seismogram is the continuous wavelet transform coefficients at the low scale. Application at a synthetic seismic seismogram shows the robustness of the proposed tool for random noises attenuation. We have applied this idea at a real seismic data of a vertical seismic profile realized in Algeria. Keywords: Seismic data, denoising, DWT, CWT, random noise.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This study was to search for an approach for rapid measurement of orange vitamin C (Vc) content. By using different decomposing levels of Daubechies 3 wavelet transform, the near-infrared spectra signals obtained from intact fruits of 100 navel orange samples were denoised, and the results of the predicted Vc contents for the corresponding samples determined by the reconstructed spectra after denoising were validated by means of PLS-CV (partial least squared-cross validation).It was shown that the prediction effects verified by PLS-CV analysis varied when different wavelet transform decomposing levels were employed. At the wavelet decomposing level 4, the best prediction effect was obtained, with the correlation coefficient R between the prediction and true values being 0.9574 and the expected variance RMSECV being as low as 3.9 mg 100 g-1. Furthermore, the 11 different approaches for the pretreatment of the near-infrared spectrum were compared.It was found that the calibration model established by PLS using spectra pretreated by wavelet transform denoising provided the best prediction for Vc content, exhibiting the highest correlation between the prediction and true values by cross validation. In conclusion, the near infrared spectral model denoised by means of wavelet transform can be used for accurate, rapid, and nondestructive quantitative analysis on navel orange Vc content.
Defacio, Brian; Kim, S.-H.; Vannevel, A.
1994-01-01
The squeezed states or Bogoliubov transformations and wavelets are applied to two problems in nonrelativistic statistical mechanics: the dielectric response of liquid water, epsilon(q-vector,w), and the bubble formation in water during insonnification. The wavelets are special phase-space windows which cover the domain and range of L(exp 1) intersection of L(exp 2) of classical causal, finite energy solutions. The multiresolution of discrete wavelets in phase space gives a decomposition into regions of time and scales of frequency thereby allowing the renormalization group to be applied to new systems in addition to the tired 'usual suspects' of the Ising models and lattice gasses. The Bogoliubov transformation: squeeze transformation is applied to the dipolaron collective mode in water and to the gas produced by the explosive cavitation process in bubble formation.
Directory of Open Access Journals (Sweden)
K. Vijayarekha
2012-12-01
Full Text Available The aim of this study is to classify the citrus fruit images based on the external defect using the features extracted in the spectral domain (transform based and to compare the performance of each of the feature set. Automatic classification of agricultural produce by machine vision technology plays a very important role as it improves the quality of grading. Multi resolution analysis using wavelets yields better results for pattern recognition and object classification. This study details about an image processing method applied for classifying three external surface defects of citrus fruit using wavelet transforms based features and an artificial neural network. The Discrete Wavelet Transform (DWT, Stationary Wavelet Transform (SWT and Wavelet Packet Transform (WPT features viz. mean and standard deviation of the details and approximations were extracted from citrus fruit images and used for classifying the defects. The DWT and SWT features were extracted from 40x40 sub-windows of the fruit image. The WPT features were extracted from the full fruit image of size 640x480. The classification results pertaining to the three wavelet transforms are reported and discussed.
Wavelet transform element of SAW type
Institute of Scientific and Technical Information of China (English)
LU Wenke; ZHU Changchun; LIU Qinghong; LIU Junhua
2005-01-01
This paper proposes to use substrate materials of small electromechanical coupling coefficient k2 (such as X-112YLiTaO3) to manufacture wavelet transform element of SAW type so as to reduce finger reflections, i.e. to reduce the error of wavelet transform element of SAW type. And it is concluded that the smaller the center frequency of the transmitting IDT of wavelet type, the smaller the error. We suggest to choose substrate material with electromechanical coupling coefficient smaller than that of X-112Y LiTaO3 in the manufacture of the transmitting IDTs of wavelet type and the receiving IDTs at center frequencies above 100MHZ, so as to reduce the errors of the transmitting IDTs of wavelet type and the receiving IDTs at center frequencies above 100MHZ.
Wavelet transform based watermark for digital images.
Xia, X G; Boncelet, C; Arce, G
1998-12-07
In this paper, we introduce a new multiresolution watermarking method for digital images. The method is based on the discrete wavelet transform (DWT). Pseudo-random codes are added to the large coefficients at the high and middle frequency bands of the DWT of an image. It is shown that this method is more robust to proposed methods to some common image distortions, such as the wavelet transform based image compression, image rescaling/stretching and image halftoning. Moreover, the method is hierarchical.
Zhai, Guangtao; Sun, Fengrong; Song, Haohao; Zhang, Mingqiang; Liu, Li; Wang, Changyu
2003-09-01
The modulus maxima of a signal's wavelet transform on different levels contain important information of the signal, which can be help to construct wavelet coefficients. A fast algorithm based on Hermite interpolation polynomial for reconstructing signal from its wavelet transform maxima is proposed in this paper. An implementation of this algorithm in medical image enhancement is also discussed. Numerical experiments have shown that compared with the Alternating Projection algorithm proposed by Mallat, this reconstruction algorithm is simpler, more efficient, and at the same time keeps high reconstruction Signal to Noise Ratio. When applied to the image contract enhancement, the computing time of this algorithm is much less compared with the one using Mallat's Alternative Projection, and the results are almost the same, so it is a practical fast reconstruction algorithm.
Optical Planar Discrete Fourier and Wavelet Transforms
Cincotti, Gabriella; Moreolo, Michela Svaluto; Neri, Alessandro
2007-10-01
We present all-optical architectures to perform discrete wavelet transform (DWT), wavelet packet (WP) decomposition and discrete Fourier transform (DFT) using planar lightwave circuits (PLC) technology. Any compact-support wavelet filter can be implemented as an optical planar two-port lattice-form device, and different subband filtering schemes are possible to denoise, or multiplex optical signals. We consider both parallel and serial input cases. We design a multiport decoder/decoder that is able to generate/process optical codes simultaneously and a flexible logarithmic wavelength multiplexer, with flat top profile and reduced crosstalk.
Analysis and removing noise from speech using wavelet transform
Tomala, Karel; Voznak, Miroslav; Partila, Pavol; Rezac, Filip; Safarik, Jakub
2013-05-01
The paper discusses the use of Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT) wavelet in removing noise from voice samples and evaluation of its impact on speech quality. One significant part of Quality of Service (QoS) in communication technology is the speech quality assessment. However, this part is seriously overlooked as telecommunication providers often focus on increasing network capacity, expansion of services offered and their enforcement in the market. Among the fundamental factors affecting the transmission properties of the communication chain is noise, either at the transmitter or the receiver side. A wavelet transform (WT) is a modern tool for signal processing. One of the most significant areas in which wavelet transforms are used is applications designed to suppress noise in signals. To remove noise from the voice sample in our experiment, we used the reference segment of the voice which was distorted by Gaussian white noise. An evaluation of the impact on speech quality was carried out by an intrusive objective algorithm Perceptual Evaluation of Speech Quality (PESQ). DWT and SWT transformation was applied to voice samples that were devalued by Gaussian white noise. Afterwards, we determined the effectiveness of DWT and SWT by means of objective algorithm PESQ. The decisive criterion for determining the quality of a voice sample once the noise had been removed was Mean Opinion Score (MOS) which we obtained in PESQ. The contribution of this work lies in the evaluation of efficiency of wavelet transformation to suppress noise in voice samples.
Getz, Neil H.
1993-11-01
The discrete wavelet transform (DWT) is adapted to functions on the discrete circle to create a discrete periodic wavelet transform (DPWT) for bounded periodic sequences. This extension also offers a solution to the problem of non-invertibility that arises in the application of the DWT to finite length sequences and provides the proper theoretical setting for the completion of some previous incomplete solutions to the invertibility problem. It is proven that the same filter coefficients used with the DWT to create orthonormal wavelets on compact support in l(infinity ) (Z) may be incorporated through the DPWT to create an orthonormal basis of discrete periodic wavelets. By exploiting transform symmetry and periodicity we arrive at easily implementable and fast synthesis and analysis algorithms.
NOVEL ADAPTIVE MULTIUSER DETECTIONALGORITHM BASED ON WAVELET TRANSFORM
Institute of Scientific and Technical Information of China (English)
ZHANGXiao-fei; XUDa-zhuan; YANGBei
2004-01-01
The wavelet transform-based adaptive multiuser detection algorithm is presented. The novel adaptive multiuser detection algorithm uses the wavelet transform for the preprocessing, and wavelet-transformed signal uses LMS algorithm to implement the adaptive multiuser detection. The algorithm makes use of wavelet transform to divide the wavelet space, which shows that the wavelet transform has a better decorrelation ability and leads to better convergence. White noise can be wiped off under the wavelet transform according to different characteristics of signal and white noise under the wavelet transform. Theoretical analyses and simulations demonstrate that the algorithm converges faster than the conventional adaptive multiuser detection algorithm, and has the better performance. Simulation results reveal that the algorithm convergence relates to the wavelet base, and show that the algorithm convergence gets better with the increasing of regularity for the same series of the wavelet base. Finally the algorithm shows that it can be easily implemented.
Study of wavelet transform type high-current transformer
Institute of Scientific and Technical Information of China (English)
卢文科; 朱长纯; 刘君华; 张建军
2002-01-01
The wavelet transformation is applied to the high-current transformer.The high-current transformer elaborated in the paper is mainly applied to the measurement of AC/DC high-current.The principle of the transformer is the Hall direct-measurement principle.The transformer has the following three characteristics:firstly, the effect of the remnant field of the iron core on the measurement is decreased;secondly,because the temperature compensation is adopted,the transformer has good temperature charactreristic;thirdly,be-cause the wavelet transfomation technology is adopted,the transformer has the capacity of good antijanming.
Oriented wavelet transform for image compression and denoising.
Chappelier, Vivien; Guillemot, Christine
2006-10-01
In this paper, we introduce a new transform for image processing, based on wavelets and the lifting paradigm. The lifting steps of a unidimensional wavelet are applied along a local orientation defined on a quincunx sampling grid. To maximize energy compaction, the orientation minimizing the prediction error is chosen adaptively. A fine-grained multiscale analysis is provided by iterating the decomposition on the low-frequency band. In the context of image compression, the multiresolution orientation map is coded using a quad tree. The rate allocation between the orientation map and wavelet coefficients is jointly optimized in a rate-distortion sense. For image denoising, a Markov model is used to extract the orientations from the noisy image. As long as the map is sufficiently homogeneous, interesting properties of the original wavelet are preserved such as regularity and orthogonality. Perfect reconstruction is ensured by the reversibility of the lifting scheme. The mutual information between the wavelet coefficients is studied and compared to the one observed with a separable wavelet transform. The rate-distortion performance of this new transform is evaluated for image coding using state-of-the-art subband coders. Its performance in a denoising application is also assessed against the performance obtained with other transforms or denoising methods.
The lifting scheme of 4-channel orthogonal wavelet transforms
Institute of Scientific and Technical Information of China (English)
PENG Lizhong; CHU Xiaoyong
2006-01-01
The 4-channel smooth wavelets with linear phase and orthogonality are designed from the 2-channel orthogonal wavelets with high transfer vanishing moments. Reversely, for simple lifting scheme of such 4-channel orthogonal wavelet transforms, a new 2-channel orthogonal wavelet associated with this 4-channel wavelet is constructed. The new 2-channel wavelet has at least the same number of vanishing moments as the associated 4-channel one. Finally, by combining the two such 2-channel wavelet systems, the lifting scheme of 4-channel orthogonal wavelet transform, which has simple structure and is easy to apply, is presented.
Comparison of fast discrete wavelet transform algorithms
Institute of Scientific and Technical Information of China (English)
MENG Shu-ping; TIAN Feng-chun; XU Xin
2005-01-01
This paper presents an analysis on and experimental comparison of several typical fast algorithms for discrete wavelet transform (DWT) and their implementation in image compression, particularly the Mallat algorithm, FFT-based algorithm, Short-length based algorithm and Lifting algorithm. The principles, structures and computational complexity of these algorithms are explored in details respectively. The results of the experiments for comparison are consistent to those simulated by MATLAB. It is found that there are limitations in the implementation of DWT. Some algorithms are workable only for special wavelet transform, lacking in generality. Above all, the speed of wavelet transform, as the governing element to the speed of image processing, is in fact the retarding factor for real-time image processing.
Comparison on Integer Wavelet Transforms in Spherical Wavelet Based Image Based Relighting
Institute of Scientific and Technical Information of China (English)
WANGZe; LEEYin; LEUNGChising; WONGTientsin; ZHUYisheng
2003-01-01
To provide a good quality rendering in the Image based relighting (IBL) system, tremendous reference images under various illumination conditions are needed. Therefore data compression is essential to enable interactive action. And the rendering speed is another crucial consideration for real applications. Based on Spherical wavelet transform (SWT), this paper presents a quick representation method with Integer wavelet transform (IWT) for the IBL system. It focuses on comparison on different IWTs with the Embedded zerotree wavelet (EZW) used in the IBL system. The whole compression procedure contains two major compression steps. Firstly, SWT is applied to consider the correlation among different reference images. Secondly, the SW transformed images are compressed with IWT based image compression approach. Two IWTs are used and good results are showed in the simulations.
Remacha, Clément; Coëtmellec, Sébastien; Brunel, Marc; Lebrun, Denis
2013-02-01
Wavelet analysis provides an efficient tool in numerous signal processing problems and has been implemented in optical processing techniques, such as in-line holography. This paper proposes an improvement of this tool for the case of an elliptical, astigmatic Gaussian (AEG) beam. We show that this mathematical operator allows reconstructing an image of a spherical particle without compression of the reconstructed image, which increases the accuracy of the 3D location of particles and of their size measurement. To validate the performance of this operator we have studied the diffraction pattern produced by a particle illuminated by an AEG beam. This study used mutual intensity propagation, and the particle is defined as a chirped Gaussian sum. The proposed technique was applied and the experimental results are presented.
New Algorithm For Calculating Wavelet Transforms
Directory of Open Access Journals (Sweden)
Piotr Lipinski
2009-04-01
Full Text Available In this article we introduce a new algorithm for computing Discrete Wavelet Transforms (DWT. The algorithm aims at reducing the number of multiplications, required to compute a DWT. The algorithm is general and can be used to compute a variety of wavelet transform (Daubechies and CDF. Here we focus on CDF 9/7 filters, which are used in JPEG2000 compression standard. We show that the algorithm outperforms convolution-based and lifting-based algorithms in terms of number of multiplications.
Multiresolution signal decomposition transforms, subbands, and wavelets
Akansu, Ali N; Haddad, Paul R
2001-01-01
The uniqueness of this book is that it covers such important aspects of modern signal processing as block transforms from subband filter banks and wavelet transforms from a common unifying standpoint, thus demonstrating the commonality among these decomposition techniques. In addition, it covers such ""hot"" areas as signal compression and coding, including particular decomposition techniques and tables listing coefficients of subband and wavelet filters and other important properties.The field of this book (Electrical Engineering/Computer Science) is currently booming, which is, of course
Doppler radar fall activity detection using the wavelet transform.
Su, Bo Yu; Ho, K C; Rantz, Marilyn J; Skubic, Marjorie
2015-03-01
We propose in this paper the use of Wavelet transform (WT) to detect human falls using a ceiling mounted Doppler range control radar. The radar senses any motions from falls as well as nonfalls due to the Doppler effect. The WT is very effective in distinguishing the falls from other activities, making it a promising technique for radar fall detection in nonobtrusive inhome elder care applications. The proposed radar fall detector consists of two stages. The prescreen stage uses the coefficients of wavelet decomposition at a given scale to identify the time locations in which fall activities may have occurred. The classification stage extracts the time-frequency content from the wavelet coefficients at many scales to form a feature vector for fall versus nonfall classification. The selection of different wavelet functions is examined to achieve better performance. Experimental results using the data from the laboratory and real inhome environments validate the promising and robust performance of the proposed detector.
RESEARCH OF WAVELET TRANSFORM INSTRUMENT SYSTEM FOR SIGNAL ANALYSIS
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
After brief describing the principle of wavelet transform (WT) of signals, a new signals analysis system based on wavelet transform is introduced. The design and development of the instrument of wavelet transform are described. A number of practical uses of this system demonstrate that wavelet transform system is specially functional in identifying and processing impulse, singular and nonsmooth signals,so that it should be evaluated the most advanced signal analyzing system.
ECG Analysis based on Wavelet Transform and Modulus Maxima
Directory of Open Access Journals (Sweden)
Mourad Talbi
2012-01-01
Full Text Available In this paper, we have developed a new technique of P, Q, R, S and T Peaks detection using Wavelet Transform (WT and Modulus maxima. One of the commonest problems in electrocardiogram (ECG signal processing, is baseline wander removal suppression. Therefore we have removed the baseline wander in order to make easier the detection of the peaks P and T. Those peaks are detected after the QRS detection. The proposed method is based on the application of the discritized continuous wavelet transform (Mycwt used for the Bionic wavelet transform, to the ECG signal in order to detect R-peaks in the first stage and in the second stage, the Q and S peaks are detected using the R-peaks localization. Finally the Modulus maxima are used in the undecimated wavelet transform (UDWT domain in order to detect the others peaks (P, T. This detection is performed by using a varying-length window that is moving along the whole signal. For evaluating the proposed method, we have compared it to others techniques based on wavelets. In this evaluation, we have used many ECG signals taken from MIT-BIH database. The obtained results show that the proposed method outperforms a number of conventional techniques used for our evaluation.
Implementation of Audio signal by using wavelet transform
Directory of Open Access Journals (Sweden)
Chakresh kumar,
2010-10-01
Full Text Available Audio coding is the technology to represent audio in digital form with as few bits as possible while maintaining the intelligibility and quality required for particular application. Interest in audio coding is motivated by the evolution to digital communications and the requirement to minimize bit rate, and hence conserve bandwidth. There is always a tradeoff between compression ratio and maintaining the delivered audio quality and intelligibility. Audio coding is widely used in application such as digital broadcasting, Internet audio or music database to reduce the bit rate of high quality audio signal without comprising the perceptual quality. In this dissertation work Design and implementation of a MPEG Lossless audio codec using wavelet transform has been proposed. The major issues concerning the development of audio codec are choosing optimal wavelets for audio signals, decomposition level in the digital wavelet transform and thresholding criteria for coefficient truncation which is the basis to provide compression ratio for audio with suitable peak signal to noise ratio (PSNR, wavelet packet compression technique has also been used to compare the performanceof audio codec using wavelet transform. A psychoacoustic model is used to improve the quality of audio signal. The proposed audio codec has been implemented on DSK6713 Starter Kit using MATLAB-7.3 and Link to Code Composer Studio and various audio signals of different time duration have been tested. Result obtained show that the proposed codec improves quality of the reconstructed audio signal.
Singularity Detection of Signals Based on their Wavelet Transform
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
This paper introduces a multiresolution decomposition of signals based on their wavelet transform. The different behaviors of the wavelet transform between the signal and the noise are compared. An algorithm of singularity detection and processing in signals is proposed by the modulus maximum of the wavelet transform.
The Discrete, Orthogonal Wavelet Transform, A Protective Approach.
1995-09-01
completely determined by the collection of functions onto which it projects. The wavelet transform projects onto a set of functions which satisfy a...simple linear relationship between different levels of dilation. The properties of the wavelet transform are determined by the coefficients of this linear...relationship. This thesis examines the connections between the wavelet transform properties and the linear relationship coefficients. (AN)
Cosmic Ray elimination using the Wavelet Transform
Orozco-Aguilera, M. T.; Cruz, J.; Altamirano, L.; Serrano, A.
2009-11-01
In this work, we present a method for the automatic cosmic ray elimination in a single CCD exposure using the Wavelet Transform. The proposed method can eliminate cosmic rays of any shape or size. With this method we can eliminate over 95% of cosmic rays in a spectral image.
COSMIC RAY ELIMINATION USING THE WAVELET TRANSFORM
Directory of Open Access Journals (Sweden)
M. T. Orozco-Aguilera
2009-01-01
Full Text Available In this work, we present a method for the automatic cosmic ray elimination in a single CCD exposure using the Wavelet Transform. The proposed method can eliminate cosmic rays of any shape or size. With this method we can eliminate over 95% of cosmic rays in a spectral image.
Analisis Perbandingan Kompresi Haar Wavelet Transform dengan Embedded Zerotree Wavelet pada Citra
Directory of Open Access Journals (Sweden)
LEDYA NOVAMIZANTI
2016-02-01
Full Text Available Abstrak Kompresi data merupakan salah satu teknologi pemicu revolusi multimedia. Haar Wavelet mampu merepresentasikan ciri tekstur dan bentuk, sedangkan Embedded Zerotree Wavelet (EZW mampu menyusun bit-bit menurut tingkat prioritas, sehingga mampu mencapai kompresi maksimal. Pada penelitian ini telah dilakukan perbandingan Haar Wavelet Transform dengan Embendded Zerotree Wavelet untuk kompresi citra. Pengujian menggunakan 4 citra grayscale berformat bitmap (.bmp dengan resolusi 256x256 dan 512x512. Rasio Kompresi yang diperoleh dengan menggunakan algoritma Embedded Zerotree Wavelet dan Haar Wavelet, yaitu 99.54% dan 95.35% pada threshold 80. Laju bit antara Embedded Zerotree Wavelet lebih rendah dibandingkan Haar Wavelet, yaitu 0.06 bpp dan 0.13 bpp. Algoritma Haar Wavelet memberikan waktu kompresi lebih baik dibandingkan EZW dimana selisih antara keduanya sekitar 8 detik. Kata kunci: kompresi citra, threshold, Haar Wavelet, Embedded Zerotree Wavelet Abstract Data compression is one of the triggers of the revolution multimedia technology. Haar Wavelet able to represent the characteristics of texture and shape, while Embedded Zerotree Wavelet (EZW is able to arrange the bits according to priority level, so as to achieve maximum compression. In this study, we had conducted comparison between Haar Wavelet Transform with Embedded Zerotree Wavelet algorithm for image compression. The tests using 4 image format grayscale bitmap (.bmp with resolution of 256x256 pixels and 512x512 pixels. Compression ratio obtained using Embedded Zerotree Wavelet and Wavelet Haar algorithm, which are 99.54% and 95.35% respectively, at the threshold of 80. The bit rate on Embedded Zerotree Wavelet is lower than Haar wavelet, that is 0:06 bpp and 0:13 bpp respectively. Haar Wavelet algorithm gives a better compression time than the EZW, with the difference between the two is about 8 seconds. Keywords: image compression, threshold, Haar Wavelet, Embedded Zerotree
Adaptive wavelet transform algorithm for lossy image compression
Pogrebnyak, Oleksiy B.; Ramirez, Pablo M.; Acevedo Mosqueda, Marco Antonio
2004-11-01
A new algorithm of locally adaptive wavelet transform based on the modified lifting scheme is presented. It performs an adaptation of the wavelet high-pass filter at the prediction stage to the local image data activity. The proposed algorithm uses the generalized framework for the lifting scheme that permits to obtain easily different wavelet filter coefficients in the case of the (~N, N) lifting. Changing wavelet filter order and different control parameters, one can obtain the desired filter frequency response. It is proposed to perform the hard switching between different wavelet lifting filter outputs according to the local data activity estimate. The proposed adaptive transform possesses a good energy compaction. The designed algorithm was tested on different images. The obtained simulation results show that the visual and quantitative quality of the restored images is high. The distortions are less in the vicinity of high spatial activity details comparing to the non-adaptive transform, which introduces ringing artifacts. The designed algorithm can be used for lossy image compression and in the noise suppression applications.
Nuclear data compression and reconstruction via discrete wavelet transform
Energy Technology Data Exchange (ETDEWEB)
Park, Young Ryong; Cho, Nam Zin [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)
1997-12-31
Discrete Wavelet Transforms (DWTs) are recent mathematics, and begin to be used in various fields. The wavelet transform can be used to compress the signal and image due to its inherent properties. We applied the wavelet transform compression and reconstruction to the neutron cross section data. Numerical tests illustrate that the signal compression using wavelet is very effective to reduce the data saving spaces. 7 refs., 4 figs., 3 tabs. (Author)
Discovering the Merit of the Wavelet Transform for Object Classification
2004-03-01
key steps in object recognition. Typically, geometric primitives are extracted from an image using local analysis. However, the wavelet transform provides...network. This thesis examines the benefits of the wavelet transform as a preprocessor to a neural network for object recognition. Scaling of the...benefits of the wavelet transform , the effects of the various post-wavelet scaling functions, and the best neural network topology for this research. This is done by analyzing the system s performance on CAD models.
Sánchez-Úbeda, Juan Pedro; Calvache, María Luisa; Duque, Carlos; López-Chicano, Manuel
2016-11-01
A new methodology has been developed to obtain tidal-filtered time series of groundwater levels in coastal aquifers. Two methods used for oceanography processing and forecasting of sea level data were adapted for this purpose and compared: HA (Harmonic Analysis) and CWT (Continuous Wavelet Transform). The filtering process is generally comprised of two main steps: the detection and fitting of the major tide constituents through the decomposition of the original signal and the subsequent extraction of the complete tidal oscillations. The abilities of the optional HA and CWT methods to decompose and extract the tidal oscillations were assessed by applying them to the data from two piezometers at different depths close to the shoreline of a Mediterranean coastal aquifer (Motril-Salobreña, SE Spain). These methods were applied to three time series of different lengths (one month, one year, and 3.7 years of hourly data) to determine the range of detected frequencies. The different lengths of time series were also used to determine the fit accuracies of the tidal constituents for both the sea level and groundwater heads measurements. The detected tidal constituents were better resolved with increasing depth in the aquifer. The application of these methods yielded a detailed resolution of the tidal components, which enabled the extraction of the major tidal constituents of the sea level measurements from the groundwater heads (e.g., semi-diurnal, diurnal, fortnightly, monthly, semi-annual and annual). In the two wells studied, the CWT method was shown to be a more effective method than HA for extracting the tidal constituents of highest and lowest frequencies from groundwater head measurements.
Hill, Paul; Achim, Alin; Al-Mualla, Mohammed Ebrahim; Bull, David
2016-04-11
Accurate estimation of the contrast sensitivity of the human visual system is crucial for perceptually based image processing in applications such as compression, fusion and denoising. Conventional Contrast Sensitivity Functions (CSFs) have been obtained using fixed sized Gabor functions. However, the basis functions of multiresolution decompositions such as wavelets often resemble Gabor functions but are of variable size and shape. Therefore to use conventional contrast sensitivity functions in such cases is not appropriate. We have therefore conducted a set of psychophysical tests in order to obtain the contrast sensitivity function for a range of multiresolution transforms: the Discrete Wavelet Transform (DWT), the Steerable Pyramid, the Dual-Tree Complex Wavelet Transform (DT-CWT) and the Curvelet Transform. These measures were obtained using contrast variation of each transforms' basis functions in a 2AFC experiment combined with an adapted version of the QUEST psychometric function method. The results enable future image processing applications that exploit these transforms such as signal fusion, super-resolution processing, denoising and motion estimation, to be perceptually optimised in a principled fashion. The results are compared to an existing vision model (HDR-VDP2) and are used to show quantitative improvements within a denoising application compared to using conventional CSF values.
2001-10-25
We evaluate a combined discrete wavelet transform (DWT) and wavelet packet algorithm to improve the homogeneity of magnetic resonance imaging when a...image and uses this information to normalize the image intensity variations. Estimation of the coil sensitivity profile based on the wavelet transform of
Construction of Hilbert Transform Pairs of Wavelet Bases and Gabor-like Transforms
Chaudhury, Kunal Narayan
2009-01-01
We propose a novel method for constructing Hilbert transform (HT) pairs of wavelet bases based on a fundamental approximation-theoretic characterization of scaling functions--the B-spline factorization theorem. In particular, starting from well-localized scaling functions, we construct HT pairs of biorthogonal wavelet bases of L^2(R) by relating the corresponding wavelet filters via a discrete form of the continuous HT filter. As a concrete application of this methodology, we identify HT pairs of spline wavelets of a specific flavor, which are then combined to realize a family of complex wavelets that resemble the optimally-localized Gabor function for sufficiently large orders. Analytic wavelets, derived from the complexification of HT wavelet pairs, exhibit a one-sided spectrum. Based on the tensor-product of such analytic wavelets, and, in effect, by appropriately combining four separable biorthogonal wavelet bases of L^2(R^2), we then discuss a methodology for constructing 2D directional-selective complex...
Optical asymmetric image encryption using gyrator wavelet transform
Mehra, Isha; Nishchal, Naveen K.
2015-11-01
In this paper, we propose a new optical information processing tool termed as gyrator wavelet transform to secure a fully phase image, based on amplitude- and phase-truncation approach. The gyrator wavelet transform constitutes four basic parameters; gyrator transform order, type and level of mother wavelet, and position of different frequency bands. These parameters are used as encryption keys in addition to the random phase codes to the optical cryptosystem. This tool has also been applied for simultaneous compression and encryption of an image. The system's performance and its sensitivity to the encryption parameters, such as, gyrator transform order, and robustness has also been analyzed. It is expected that this tool will not only update current optical security systems, but may also shed some light on future developments. The computer simulation results demonstrate the abilities of the gyrator wavelet transform as an effective tool, which can be used in various optical information processing applications, including image encryption, and image compression. Also this tool can be applied for securing the color image, multispectral, and three-dimensional images.
Hwang, Wen-Jyi; Chine, Ching-Fung; Li, Kuo-Jung
2003-03-01
In this paper, a novel medical data compression algorithm, termed layered set partitioning in hierarchical trees (LSPIHT) algorithm, is presented for telemedicine applications. In the LSPIHT, the encoded bit streams are divided into a number of layers for transmission and reconstruction. Starting from the base layer, by accumulating bit streams up to different enhancement layers, we can reconstruct medical data with various signal-to-noise ratios (SNRs) and/or resolutions. Receivers with distinct specifications can then share the same source encoder to reduce the complexity of telecommunication networks for telemedicine applications. Numerical results show that, besides having low network complexity, the LSPIHT attains better rate-distortion performance as compared with other algorithms for encoding medical data.
Human Body Image Edge Detection Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
李勇; 付小莉
2003-01-01
Human dresses are different in thousands way.Human body image signals have big noise, a poor light and shade contrast and a narrow range of gray gradation distribution. The application of a traditional grads method or gray method to detect human body image edges can't obtain satisfactory results because of false detections and missed detections. According to tte peculiarity of human body image, dyadic wavelet transform of cubic spline is successfully applied to detect the face and profile edges of human body image and Mallat algorithm is used in the wavelet decomposition in this paper.
Wavelet transform of generalized functions in $K^{\\prime}\\{ M_p\\}$ spaces
Indian Academy of Sciences (India)
R S Pathak; Abhishek Singh
2016-05-01
Using convolution theory in $K\\{ M_p\\}$ space we obtain bounded results for the wavelet transform. Calderón-type reproducing formula is derived in distribution sense as an application of the same. An inversion formula for the wavelet transform of generalized functions is established.
ECG signal denoising via empirical wavelet transform.
Singh, Omkar; Sunkaria, Ramesh Kumar
2016-12-29
This paper presents new methods for baseline wander correction and powerline interference reduction in electrocardiogram (ECG) signals using empirical wavelet transform (EWT). During data acquisition of ECG signal, various noise sources such as powerline interference, baseline wander and muscle artifacts contaminate the information bearing ECG signal. For better analysis and interpretation, the ECG signal must be free of noise. In the present work, a new approach is used to filter baseline wander and power line interference from the ECG signal. The technique utilized is the empirical wavelet transform, which is a new method used to compute the building modes of a given signal. Its performance as a filter is compared to the standard linear filters and empirical mode decomposition.The results show that EWT delivers a better performance.
Workman, Michael J; Serov, Alexey; Halevi, Barr; Atanassov, Plamen; Artyushkova, Kateryna
2015-05-01
The discrete wavelet transform (DWT) has found significant utility in process monitoring, filtering, and feature isolation of SEM, AFM, and optical images. Current use of the DWT for surface analysis assumes initial knowledge of the sizes of the features of interest in order to effectively isolate and analyze surface components. Current methods do not adequately address complex, heterogeneous surfaces in which features across multiple size ranges are of interest. Further, in situations where structure-to-property relationships are desired, the identification of features relevant for the function of the material is necessary. In this work, the DWT is examined as a tool for quantitative, length-scale specific surface metrology without prior knowledge of relevant features or length-scales. A new method is explored for determination of the best wavelet basis to minimize variation in roughness and skewness measurements with respect to change in position and orientation of surface features. It is observed that the size of the wavelet does not directly correlate with the size of features on the surface, and a method to measure the true length-scale specific roughness of the surface is presented. This method is applied to SEM and AFM images of non-precious metal catalysts, yielding new length-scale specific structure-to-property relationships for chemical speciation and fuel cell performance. The relationship between SEM and AFM length-scale specific roughness is also explored. Evidence is presented that roughness distributions of SEM images, as measured by the DWT, is representative of the true surface roughness distribution obtained from AFM.
Global motion estimation with Gabor wavelet transform
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
A novel algorithm of global motion estimation is proposed. First, through Gabor wavelet transform (GWT), a kind of energy distribution of image is obtained and checkpoints are selected according to a probability decision approach proposed. Then, the initialized motion vectors are obtained via a hierarchal block-matching based on these checkpoints.Finally, by employing a 3-parameter motion model, precise parameters of global motion are found. From the experiment, the algorithm is reliable and robust.
Inversion of receiver function by wavelet transformation
Institute of Scientific and Technical Information of China (English)
吴庆举; 田小波; 张乃铃; 李桂银; 曾融生
2003-01-01
A new method for receiver function inversion by wavelet transformation is presented in this paper. Receiver func-tion is expanded to different scales with different resolution by wavelet transformation. After an initial model be-ing taken, a generalized least-squares inversion procedure is gradually carried out for receiver function from low tohigh scale, with the inversion result for low order receiver function as the initial model for high order. Aneighborhood containing the global minimum is firstly searched from low scale receiver function, and will gradu-ally focus at the global minimum by introducing high scale information of receiver function. With the gradual ad-dition of high wave-number to smooth background velocity structure, wavelet transformation can keep the inver-sion result converge to the global minimum, reduce to certain extent the dependence of inversion result on theinitial model, overcome the nonuniqueness of generalized least-squares inversion, and obtain reliable crustal andupper mantle velocity with high resolution.
Analysis of phonocardiogram signals using wavelet transform.
Meziani, F; Debbal, S M; Atbi, A
2012-08-01
Phonocardiograms (PCG) are recordings of the acoustic waves produced by the mechanical action of the heart. They generally consist of two kinds of acoustic vibrations: heart sounds and heart murmurs. Heart murmurs are often the first signs of pathological changes of the heart valves, and are usually found during auscultation in primary health care. Heart auscultation has been recognized for a long time as an important tool for the diagnosis of heart disease, although its accuracy is still insufficient to diagnose some heart diseases. It does not enable the analyst to obtain both qualitative and quantitative characteristics of the PCG signals. The efficiency of diagnosis can be improved considerably by using modern digital signal processing techniques. Therefore, these last can provide useful and valuable information on these signals. The aim of this study is to analyse PCG signals using wavelet transform. This analysis is based on an algorithm for the detection of heart sounds (the first and second sounds, S1 and S2) and heart murmurs using the PCG signal as the only source. The segmentation algorithm, which separates the components of the heart signal, is based on denoising by wavelet transform (DWT). This algorithm makes it possible to isolate individual sounds (S1 or S2) and murmurs. Thus, the analysis of various PCGs signals using wavelet transform can provide a wide range of statistical parameters related to the phonocardiogram signal.
Synchrosqueezed wavelet transform for damping identification
Mihalec, Marko; Slavič, Janko; Boltežar, Miha
2016-12-01
Synchrosqueezing is a procedure for improving the frequency localization of a continuous wavelet transform. This research focuses on using a synchrosqueezed wavelet transform (SWT) to determine the damping ratios of a vibrating system using a free-response signal. While synchrosqueezing is advantageous due to its localisation in the frequency, damping identification with the original SWT is not sufficiently accurate. Here, the synchrosqueezing was researched in detail, and it was found that an error in the frequency occurs as a result of the numerical calculation of the preliminary frequencies. If this error were to be compensated, a better damping identification would be expected. To minimize the frequency-shift error, three different strategies are investigated: the scale-dependent coefficient method, the shifted-coefficient method and the autocorrelated-frequency method. Furthermore, to improve the SWT, two synchrosqueezing criteria are introduced: the average SWT and the proportional SWT. Finally, the proposed modifications are tested against close modes and the noise in the signals. It was numerically and experimentally confirmed that the SWT with the proportional criterion offers better frequency localization and performs better than the continuous wavelet transform when tested against noisy signals.
Pedestrian detection based on redundant wavelet transform
Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun
2016-10-01
Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.
Applications of Multidimensional Wavelet Filtering in Geosciences
Yuen, D. A.; Vincent, A. P.; Kido, M.
2001-12-01
Today we are facing a severe crisis of being flooded with huge amounts of data being generated by higher-resolution numerical simulations , laboratory instrumentions and satellite observations. Since there is no way one can visualize the full data set, we must extract essential features from the data-set. One way of addressing this problem is to use mathematical filters , such as multidimensional wavelets. We present imaging results in the geosciences based on using multidimensional Gaussian wavelets as a filter. This approach has been applied to a wide-range of problems, which span from the nanoscale in mineral surfaces imaged by atomic force microscopy to hundreds of kilometers in geoidal undulations determined from satellite orbits or small-scale plumes in high Rayleigh number convection. Besides decomposing the field under consideration into various scales , called a scalogram, we have also constructed two-dimensional maps, delineating the spatial distributions of the maximum of the wavelet transformed quantity E-max and the associated local wave-number. We have generalized the application of multidimensional wavelets to quantify in terms of a two-dimensional map the correlation C for two multidimensional fields A and B. We will show a simple 2D isotropic wavelet-like transform for a spherical surface. We have analyzed the transformed geoid data with a band-pass filter in the spherical harmonic domain and have shown the equivalency of the two representations. This spherical wavelet-like filter can be applied also to problems in planetary science, such as the surface topography and geoid of other planetary bodies, like Mars.
Understanding wavelet analysis and filters for engineering applications
Parameswariah, Chethan Bangalore
Wavelets are signal-processing tools that have been of interest due to their characteristics and properties. Clear understanding of wavelets and their properties are a key to successful applications. Many theoretical and application-oriented papers have been written. Yet the choice of a right wavelet for a given application is an ongoing quest that has not been satisfactorily answered. This research has successfully identified certain issues, and an effort has been made to provide an understanding of wavelets by studying the wavelet filters in terms of their pole-zero and magnitude-phase characteristics. The magnitude characteristics of these filters have flat responses in both the pass band and stop band. The phase characteristics are almost linear. It is interesting to observe that some wavelets have the exact same magnitude characteristics but their phase responses vary in the linear slopes. An application of wavelets for fast detection of the fault current in a transformer and distinguishing from the inrush current clearly shows the advantages of the lower slope and fewer coefficients---Daubechies wavelet D4 over D20. This research has been published in the IEEE transactions on Power systems and is also proposed as an innovative method for protective relaying techniques. For detecting the frequency composition of the signal being analyzed, an understanding of the energy distribution in the output wavelet decompositions is presented for different wavelet families. The wavelets with fewer coefficients in their filters have more energy leakage into adjacent bands. The frequency bandwidth characteristics display flatness in the middle of the pass band confirming that the frequency of interest should be in the middle of the frequency band when performing a wavelet transform. Symlets exhibit good flatness with minimum ripple but the transition regions do not have sharper cut off. The number of wavelet levels and their frequency ranges are dependent on the two
A Study on System Identification Using Wavelet Transformation
Energy Technology Data Exchange (ETDEWEB)
Baek, Wook Jin; Han, Jeong Woo; Kang, Sung Ju [Department of Chemical Engineering, Chonnam National University, Kwangju (Korea); Chung, Chang Bock [Faculty of Applied Chemical Engineering, Chonnam National University, Kwangju (Korea)
2001-04-01
The wavelet transformation, which was developed in order to overcome the defects of traditional Fourier transformation, is applied to many fields of study in various ways-for example, de-noising, data compression and mathematic applications such as solving partial differential equations, etc. De-noising is one of the wavelet transformation and has been studied by many researchers. The effect of de-noising depends upon the shrinkage function and the method of choosing the threshold value for the function. The objective of this work is to analyze the results of applying various threshold algorithms according to characteristics for signals and noise level. By applying the de-noising to the system identification, we compared the performances of signals which went through the de-noising process with those of signals with out de-noising. 28 refs., 12 figs., 10 tabs.
Wavelet transform in similarity paradigm
Z.R. Struzik; A.P.J.M. Siebes (Arno)
1998-01-01
textabstract[INS-R9802] Searching for similarity in time series finds still broader applications in data mining. However, due to the very broad spectrum of data involved, there is no possibility of defining one single notion of similarity suitable to serve all applications. We present a powerful
Directory of Open Access Journals (Sweden)
Kohei Arai
2014-02-01
Full Text Available Human has a duty to preserve the nature, preserving the plant is one of the examples. This research emphasis on ornamental plant that has functionality not only as ornament plant but also as a medicinal plant. Purpose of this research is to find the best of the particular feature extraction components from several wavelet transformations. It consists of Daubechies, Dyadic, and Dual-tree complex wavelet transformation. Dyadic and Dual-tree complex wavelet transformations have shift invariant property. While Daubechies is a standard wavelet transform that widely used for many applications. This comparison is utilizing leaf image datasets from ornamental plants. From the experiments, obtained that best classification performance attained by Dual-tree complex wavelet transformation with 96.66% of overall performance result.
The application of wavelet transform in medical image processing%小波变换在医学图像处理中的应用
Institute of Scientific and Technical Information of China (English)
乜大伟
2014-01-01
医学成像设备的使用在辅助医生对病情做出正确诊断的过程中发挥了越来越重要的作用。由于人体器官本身具有复杂、运动、多样的特性，因此处理医学图像时需要综合多个方面的因素，这使处理医学图像的技术变得非常复杂。本文从小波变换说起，探讨其在医学图像处理上的边缘提取、去噪、图像特征加强等方面的应用，简要阐述小波变换技术在医学图像处理上的局限性，并展望小波变换的未来发展方向。%Medical imaging equipment has played an increasingly important role in the procedure of assisting doctors to make an accurate diagnosis of the disease. Because of the complexity, motility and diversity of human organs, it re-quires a combination of various factors when dealing with medical images, which makes the technology of medical im-age processing extremely complicated. The present thesis makes a tentative investigation and analysis on the application of wavelet transform in medical image processing from the aspects of edge extraction, denoising, intensification of image feature, etc. Additionally, it presents a brief description of the limitations of the wavelet transform technology in medi-cal image processing, and eventually ends with a prospect of the development of wavelet transform in the future.
Hybrid Coding of Image Sequences by Using Wavelet Transform
Directory of Open Access Journals (Sweden)
M. Surin
2000-04-01
Full Text Available In this paper, a new method of hybrid coding of image sequences byusing wavelet transform is proposed. The basic MPEG scheme with DCT hasbeen modificated in sense of replacement DCT by wavelet transform. Inthe proposed method, the motion estimation and compensation are usedfor motion vectors calculation and different frame between currentframe and compensated frame is coded by using wavelet transform. Someexperimental results of image sequences coding by using a new methodare presented.
Matrix Expression of the Orthogonal Wavelet(Packets)Transform
Institute of Scientific and Technical Information of China (English)
杜红彬; 姚平经; 等
2002-01-01
Matrix expression of finite orthogonal wavelet transform of finite impulse response signal is nmore valuable for theoretical analysis and understanding.However,clear deduction for matrix expression has not been provided yet.In this paper,the formulation to generate the related matrix is put forware and the theorem on the orthogonality of this matrix proved.This effort deploys a basis for more deeper and wider applications in chemical processes.
Four-Point Wavelets and Their Applications
Institute of Scientific and Technical Information of China (English)
魏国富; 陈发来
2002-01-01
Multiresolution analysis (MRA) and wavelets provide useful and efficient tools for representing functions at multiple levels of details. Wavelet representations have been used in a broad range of applications, including image compression, physical simulation and numerical analysis. In this paper, the authors construct a new class of wavelets, called four-point wavelets,based on an interpolatory four-point subdivision scheme. They are of local support, symmetric and stable. The analysis and synthesis algorithms have linear time complexity. Depending on different weight parameters w, the scaling functions and wavelets generated by the four-point subdivision scheme are of different degrees of smoothness. Therefore the user can select better wavelets relevant to the practice among the classes of wavelets. The authors apply the fourpoint wavelets in signal compression. The results show that the four-point wavelets behave much better than B-spline wavelets in many situations.
OPTICAL REALIZATION OF WAVELET TRANSFORM WITH A SINGLE LENS
Institute of Scientific and Technical Information of China (English)
王取泉; 熊贵光; 李承芳; 张苏淮; 王琳
2001-01-01
Two optical set-ups to implement wavelet transform with a single lens have been proposed, in which the wavelet filter was placed in front of the imaging lens or on the frequency plane. The general formula of the complex field distribution of the output plane has been deduced. The analysing wavelet functions of the band-pass wavelet filters with double and circular slits have been discussed.
Watermarking on 3D mesh based on spherical wavelet transform
Institute of Scientific and Technical Information of China (English)
金剑秋; 戴敏雅; 鲍虎军; 彭群生
2004-01-01
In this paper we propose a robust watermarking algorithm for 3D mesh. The algorithm is based on spherical wavelet transform. Our basic idea is to decompose the original mesh into a series of details at different scales by using spherical wavelet transform; the watermark is then embedded into the different levels of details. The embedding process includes: global sphere parameterization, spherical uniform sampling, spherical wavelet forward transform, embedding watermark, spherical wavelet inverse transform, and at last resampling the mesh watermarked to recover the topological connectivity of the original model. Experiments showed that our algorithm can improve the capacity of the watermark and the robustness of watermarking against attacks.
RESEARCH OF PROBLEMS ON REALIZING DIRECT ALGORITHM OF WAVELET TRANSFORM
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
Direct algorithm of wavelet transform (WT) is the numerical algorithm obtained from the integral formula of WT by directly digitization.Some problems on realizing the algorithm are studied.Some conclusions on the direct algorithm of discrete wavelet transform (DWT), such as discrete convolution operation formula of wavelet coefficients and wavelet components, sampling principle and technology to wavelets, deciding method for scale range of wavelets, measures to solve edge effect problem, etc, are obtained.The realization of direct algorithm of continuous wavelet transform (CWT) is also studied.The computing cost of direct algorithm and Mallat algorithm of DWT are still studied, and the computing formulae are obtained.These works are beneficial to deeply understand WT and Mallat algorithm.Examples in the end show that direct algorithm can also be applied widely.
Novel Adaptive Beamforming Algorithm Based on Wavelet Packet Transform
Institute of Scientific and Technical Information of China (English)
Zhang Xiaofei; Xu Dazhuan
2005-01-01
An analysis of the received signal of array antennas shows that the received signal has multi-resolution characteristics, and hence the wavelet packet theory can be used to detect the signal. By emplying wavelet packet theory to adaptive beamforming, a wavelet packet transform-based adaptive beamforming algorithm (WP-ABF) is proposed . This WP-ABF algorithm uses wavelet packet transform as the preprocessing, and the wavelet packet transformed signal uses least mean square algorithm to implement the adaptive beamforming. White noise can be wiped off under wavelet packet transform according to the different characteristics of signal and white under the wavelet packet transform. Theoretical analysis and simulations demonstrate that the proposed WP-ABF algorithm converges faster than the conventional adaptive beamforming algorithm and the wavelet transform-based beamforming algorithm. Simulation results also reveal that the convergence of the algorithm relates closely to the wavelet base and series; that is, the algorithm convergence gets better with the increasing of series, and for the same series of wavelet base the convergence gets better with the increasing of regularity.
Image Compression Using Discrete Wavelet Transform
Directory of Open Access Journals (Sweden)
Mohammad Mozammel Hoque Chowdhury
2012-07-01
Full Text Available Image compression is a key technology in transmission and storage of digital images because of vast data associated with them. This research suggests a new image compression scheme with pruning proposal based on discrete wavelet transformation (DWT. The effectiveness of the algorithm has been justified over some real images, and the performance of the algorithm has been compared with other common compression standards. The algorithm has been implemented using Visual C++ and tested on a Pentium Core 2 Duo 2.1 GHz PC with 1 GB RAM. Experimental results demonstrate that the proposed technique provides sufficient high compression ratios compared to other compression techniques.
Cardiac Arrhythmia Classification by Wavelet Transform
Directory of Open Access Journals (Sweden)
Hadji Salah
2015-05-01
Full Text Available Cardiovascular diseases are the major public health parameter; they are the leading causes of mortality in the world. In fact many studies have been implemented to reduce the risk, including promoting education, prevention, and monitoring of patients at risk. In this paper we propose to develop classification system heartbeats. This system is based mainly on Wavelet Transform to extract features and Kohonen self-organization map the arrhythmias are considered in this study: N,(Normal, V(PrematureVentricular, A(AtrialPremature, S(Extrasystolesupraventriculaire, F(FusionN+S, R(RightBundle Branch.
Towards discrete wavelet transform-based human activity recognition
Khare, Manish; Jeon, Moongu
2017-06-01
Providing accurate recognition of human activities is a challenging problem for visual surveillance applications. In this paper, we present a simple and efficient algorithm for human activity recognition based on a wavelet transform. We adopt discrete wavelet transform (DWT) coefficients as a feature of human objects to obtain advantages of its multiresolution approach. The proposed method is tested on multiple levels of DWT. Experiments are carried out on different standard action datasets including KTH and i3D Post. The proposed method is compared with other state-of-the-art methods in terms of different quantitative performance measures. The proposed method is found to have better recognition accuracy in comparison to the state-of-the-art methods.
3-D surface profilometry based on modulation measurement by applying wavelet transform method
Zhong, Min; Chen, Feng; Xiao, Chao; Wei, Yongchao
2017-01-01
A new analysis of 3-D surface profilometry based on modulation measurement technique by the application of Wavelet Transform method is proposed. As a tool excelling for its multi-resolution and localization in the time and frequency domains, Wavelet Transform method with good localized time-frequency analysis ability and effective de-noizing capacity can extract the modulation distribution more accurately than Fourier Transform method. Especially for the analysis of complex object, more details of the measured object can be well remained. In this paper, the theoretical derivation of Wavelet Transform method that obtains the modulation values from a captured fringe pattern is given. Both computer simulation and elementary experiment are used to show the validity of the proposed method by making a comparison with the results of Fourier Transform method. The results show that the Wavelet Transform method has a better performance than the Fourier Transform method in modulation values retrieval.
Automated transformation-invariant shape recognition through wavelet multiresolution
Brault, Patrice; Mounier, Hugues
2001-12-01
We present here new results in Wavelet Multi-Resolution Analysis (W-MRA) applied to shape recognition in automatic vehicle driving applications. Different types of shapes have to be recognized in this framework. They pertain to most of the objects entering the sensors field of a car. These objects can be road signs, lane separation lines, moving or static obstacles, other automotive vehicles, or visual beacons. The recognition process must be invariant to global, affine or not, transformations which are : rotation, translation and scaling. It also has to be invariant to more local, elastic, deformations like the perspective (in particular with wide angle camera lenses), and also like deformations due to environmental conditions (weather : rain, mist, light reverberation) or optical and electrical signal noises. To demonstrate our method, an initial shape, with a known contour, is compared to the same contour altered by rotation, translation, scaling and perspective. The curvature computed for each contour point is used as a main criterion in the shape matching process. The original part of this work is to use wavelet descriptors, generated with a fast orthonormal W-MRA, rather than Fourier descriptors, in order to provide a multi-resolution description of the contour to be analyzed. In such way, the intrinsic spatial localization property of wavelet descriptors can be used and the recognition process can be speeded up. The most important part of this work is to demonstrate the potential performance of Wavelet-MRA in this application of shape recognition.
Detection of inrush current in distribution transformer using wavelet transform
Energy Technology Data Exchange (ETDEWEB)
Sedighi, A.-R.; Haghifam, M.-R. [Tarbiat Modarres Univ., Dept. of Electrical Engineering, Tehran (Iran)
2005-07-01
Inrush currents in transformers are non-sinusoidal, high magnitude currents generated due to flux saturation in the core during energization. For protection purpose, in this paper an efficient method for detection of inrush current in distribution transformer based on wavelet transform is presented. Using this method inrush current can be discriminated from the other switching transients such as: load switching, capacitor switching and single phase to ground fault. Inrush current and other events for feature extraction and discrimination are simulated using Electro Magnetic Transient Program (EMTP). Results in all cases show the effectiveness of proposed procedure in identifying inrush current from other transients. (Author)
Wavelet Transform of Fixed Pattern Noise in Focal Plane Arrays
1994-02-01
AD-A276 963 1111111111 I NAWCWPNS TP 8185 Wavelet Transform of Fixed Pattern Noise in Focal Plane Arrays OTIC by ELECTE Dr. Gary Hewer MAR 151994 and...REPORT TYPE AND DATES COVERED IFebruary 1994 Final; 199 ,L TTLE ND SBTILE LFUNDNG UBER Wavelet Transform of Fixed Pattern Noise in Focal Plane Arrays...nonlinearity 71,(w) = sgn(w)(IwI-t). with threshold t to each empirical sample value w in the wavelet transform d scales. After thresholding the wavelet
Image denoising with the dual-tree complex wavelet transform
Yaseen, Alauldeen S.; Pavlova, Olga N.; Pavlov, Alexey N.; Hramov, Alexander E.
2016-04-01
The purpose of this study is to compare image denoising techniques based on real and complex wavelet-transforms. Possibilities provided by the classical discrete wavelet transform (DWT) with hard and soft thresholding are considered, and influences of the wavelet basis and image resizing are discussed. The quality of image denoising for the standard 2-D DWT and the dual-tree complex wavelet transform (DT-CWT) is studied. It is shown that DT-CWT outperforms 2-D DWT at the appropriate selection of the threshold level.
Embedded wavelet packet transform technique for texture compression
Li, Jin; Cheng, Po-Yuen; Kuo, C.-C. Jay
1995-09-01
A highly efficient texture compression scheme is proposed in this research. With this scheme, energy compaction of texture images is first achieved by the wavelet packet transform, and an embedding approach is then adopted for the coding of the wavelet packet transform coefficients. By comparing the proposed algorithm with the JPEG standard, FBI wavelet/scalar quantization standard and the EZW scheme with extensive experimental results, we observe a significant improvement in the rate-distortion performance and visual quality.
Directory of Open Access Journals (Sweden)
Zhi Qiu
2015-02-01
Full Text Available This paper presents a hybrid damage detection method based on continuous wavelet transform (CWT and modal parameter identification techniques for beam-like structures. First, two kinds of mode shape estimation methods, herein referred to as the quadrature peaks picking (QPP and rational fraction polynomial (RFP methods, are used to identify the first four mode shapes of an intact beam-like structure based on the hammer/accelerometer modal experiment. The results are compared and validated using a numerical simulation with ABAQUS software. In order to determine the damage detection effectiveness between the QPP-based method and the RFP-based method when applying the CWT technique, the first two mode shapes calculated by the QPP and RFP methods are analyzed using CWT. The experiment, performed on different damage scenarios involving beam-like structures, shows that, due to the outstanding advantage of the denoising characteristic of the RFP-based (RFP-CWT technique, the RFP-CWT method gives a clearer indication of the damage location than the conventionally used QPP-based (QPP-CWT method. Finally, an overall evaluation of the damage detection is outlined, as the identification results suggest that the newly proposed RFP-CWT method is accurate and reliable in terms of detection of damage locations on beam-like structures.
Novel Fractional Wavelet Transform with Closed-Form Expression
Directory of Open Access Journals (Sweden)
K. O. O. Anoh
2014-01-01
Full Text Available A new wavelet transform (WT is introduced based on the fractional properties of the traditional Fourier transform. The new wavelet follows from the fractional Fourier order which uniquely identifies the representation of an input function in a fractional domain. It exploits the combined advantages of WT and fractional Fourier transform (FrFT. The transform permits the identification of a transformed function based on the fractional rotation in time-frequency plane. The fractional rotation is then used to identify individual fractional daughter wavelets. This study is, for convenience, limited to one-dimension. Approach for discussing two or more dimensions is shown.
Li, Jingsong; Yu, Benli; Fischer, Horst
2015-04-01
This paper presents a novel methodology-based discrete wavelet transform (DWT) and the choice of the optimal wavelet pairs to adaptively process tunable diode laser absorption spectroscopy (TDLAS) spectra for quantitative analysis, such as molecular spectroscopy and trace gas detection. The proposed methodology aims to construct an optimal calibration model for a TDLAS spectrum, regardless of its background structural characteristics, thus facilitating the application of TDLAS as a powerful tool for analytical chemistry. The performance of the proposed method is verified using analysis of both synthetic and observed signals, characterized with different noise levels and baseline drift. In terms of fitting precision and signal-to-noise ratio, both have been improved significantly using the proposed method.
Automatic Target Detection Using Wavelet Transform
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Ganesan L
2004-01-01
Full Text Available Automatic target recognition (ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. This paper presents an algorithm for detecting a specified set of target objects embedded in visual images for an ATR application. The developed algorithm employs a novel technique for automatically detecting man-made and non-man-made single, two, and multitargets from nontarget objects, located within a cluttered environment by evaluating nonoverlapping image blocks, where block-by-block comparison of wavelet cooccurrence feature is done. The results of the proposed algorithm are found to be satisfactory.
Inertial Sensor Signals Denoising with Wavelet Transform
Directory of Open Access Journals (Sweden)
Ioana-Raluca EDU
2015-03-01
Full Text Available In the current paper we propose a new software procedure for processing data from an inertial navigation system boarded on a moving vehicle, in order to achieve accurate navigation information on the displacement of the vehicle in terms of position, speed, acceleration and direction. We divided our research in three phases. In the first phase of our research, we implemented a real-time evaluation criterion with the intention of achieving real-time data from an accelerometer. It is well-known that most errors in the detection of position, velocity and attitude in inertial navigation occur due to difficult numerical integration of noise. In the second phase, we were interested in achieving a better estimation and compensation of the gyro sensor angular speed measurements. The errors of these sensors occur because of their miniaturization, they cannot be eliminated but can be modelled by applying specific signal processing methods. The objective of both studies was to propose a signal processing algorithm, based on Wavelet filter, along with a criterion for evaluating and updating the optimal decomposition level of Wavelet transform for achieving accurate information from inertial sensors. In the third phase of our work we are suggesting the utility of a new complex algorithm for processing data from an inertial measurement unit, containing both miniaturized accelerometers and gyros, after undergoing a series of numerical simulations and after obtaining accurate information on vehicle displacement
Directory of Open Access Journals (Sweden)
Md. Rafiqul Islam
2012-05-01
Full Text Available Fingerprint analysis plays a crucial role in crucial legal matters such as investigation of crime and security system. Due to the large number and size of fingerprint images, data compression has to be applied to reduce the storage and communication bandwidth requirements of those images. To do this, there are many types of wavelet has been used for fingerprint image compression. In this paper we haveused Coiflet-Type wavelets and our aim is to determine the most appropriate Coiflet-Type wavelet for better compression of a digitized fingerprint image and to achieve our goal Retain Energy (RE and Number of Zeros (NZ in percentage is determined for different Coiflet-Type wavelets at different threshold values at the fixed decomposition level 3 using wavelet and wavelet packet transform. We have used 8-bit grayscale left thumb digitized fingerprint image of size 480×400 as a test image.
All-optical image processing and compression based on Haar wavelet transform.
Parca, Giorgia; Teixeira, Pedro; Teixeira, Antonio
2013-04-20
Fast data processing and compression methods based on wavelet transform are fundamental tools in the area of real-time 2D data/image analysis, enabling high definition applications and redundant data reduction. The need for information processing at high data rates motivates the efforts on exploiting the speed and the parallelism of the light for data analysis and compression. Among several schemes for optical wavelet transform implementation, the Haar transform offers simple design and fast computation, plus it can be easily implemented by optical planar interferometry. We present an all optical scheme based on an asymmetric couplers network for achieving fast image processing and compression in the optical domain. The implementation of Haar wavelet transform through a 3D passive structure is supported by theoretical formulation and simulations results. Asymmetrical coupler 3D network design and optimization are reported and Haar wavelet transform, including compression, was achieved, thus demonstrating the feasibility of our approach.
Reusability of Patterns Using Discrete Wavelet Transformation in Watermarking
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Gurpreet Kaur
2014-03-01
Full Text Available Digital image watermarking is hiding information in any form in original image without degrading its perceptual quality. Watermarking is done for copyright protection of the original data. In this paper, a hybrid and robust watermarking technique for copyright protection based on Discrete Cosine Transform and Discrete Wavelet Transform is proposed. Wavelet transform has been applied widely in watermarking research as its excellent multi-resolution analysis property. The watermark is embedded based on the frequency coefficients of the discrete wavelet transform. The robustness of the technique is tested by applying noise attacks on the host signal and here the host signal is the database set containing satellite images.
A simple denoising algorithm using wavelet transform
Roy, M F; Kulkarni, B D; Sanderson, J; Rhodes, M; Stappen, M; Roy, Manojit; Sanderson, John; Rhodes, Martin; Stappen, Michel vander
1999-01-01
We have presented a new and alternative algorithm for noise reduction using the methods of discrete wavelet transform and numerical differentiation of the data. In our method the threshold for reducing noise comes out automatically. The algorithm has been applied to three model flow systems - Lorenz, Autocatalator, and Rossler systems - all evolving chaotically. The method is seen to work quite well for a wide range of noise strengths, even as large as 10% of the signal level. We have also applied the method successfully to noisy time series data obtained from the measurement of pressure fluctuations in a fluidized bed, and also to that obtained by conductivity measurement in a liquid surfactant experiment. In all the illustrations we have been able to observe that there is a clean separation in the frequencies covered by the differentiated signal and white noise.
Image Compression using Haar and Modified Haar Wavelet Transform
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Mohannad Abid Shehab Ahmed
2013-04-01
Full Text Available Efficient image compression approaches can provide the best solutions to the recent growth of the data intensive and multimedia based applications. As presented in many papers the Haar matrix–based methods and wavelet analysis can be used in various areas of image processing such as edge detection, preserving, smoothing or filtering. In this paper, color image compression analysis and synthesis based on Haar and modified Haar is presented. The standard Haar wavelet transformation with N=2 is composed of a sequence of low-pass and high-pass filters, known as a filter bank, the vertical and horizontal Haar filters are composed to construct four 2-dimensional filters, such filters applied directly to the image to speed up the implementation of the Haar wavelet transform. Modified Haar technique is studied and implemented for odd based numbers i.e. (N=3 & N=5 to generate many solution sets, these sets are tested using the energy function or numerical method to get the optimum one.The Haar transform is simple, efficient in memory usage due to high zero value spread (it can use sparse principle, and exactly reversible without the edge effects as compared to DCT (Discrete Cosine Transform. The implemented Matlab simulation results prove the effectiveness of DWT (Discrete Wave Transform algorithms based on Haar and Modified Haar techniques in attaining an efficient compression ratio (C.R, achieving higher peak signal to noise ratio (PSNR, and the resulting images are of much smoother as compared to standard JPEG especially for high C.R. A comparison between standard JPEG, Haar, and Modified Haar techniques is done finally which approves the highest capability of Modified Haar between others.
Extraction of MHD Signal Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
赵晴初; 赵彤; 李旻; 黄胜华; 徐佩霞
2002-01-01
Mirnov signals mixed with interferences are a kind of non-stationary signal. It can not obtain satisfactory effects to extract MHD signals from mirnov signals by Fourier Transform. This paper suggests that the wavelet transform can be used to treat mirnov signals. Theoretical analysis and experimental result have indicated that using the time-frequency analysis characteristics of the wavelet transform to filter mirnov signals can remove effectively interferences and extract useful MHD signals.
A Fractional Random Wavelet Transform Based Image Steganography
G.K. Rajini; RAMACHANDRA REDDY G.
2015-01-01
This study presents a novel technique for image steganography based on Fractional Random Wavelet Transform. This transform has all the features of wavelet transform with randomness and fractional order built into it. The randomness and fractional order in the algorithm brings in robustness and additional layers of security to steganography. The stegano image generated by this algorithm contains both cover image and hidden image and image degradation is not observed in it. The steganography st...
Directory of Open Access Journals (Sweden)
Abhijit Bhattacharyya
2017-03-01
Full Text Available This paper analyses the complexity of multivariate electroencephalogram (EEG signals in different frequency scales for the analysis and classification of focal and non-focal EEG signals. The proposed multivariate sub-band entropy measure has been built based on tunable-Q wavelet transform (TQWT. In the field of multivariate entropy analysis, recent studies have performed analysis of biomedical signals with a multi-level filtering approach. This approach has become a useful tool for measuring inherent complexity of the biomedical signals. However, these methods may not be well suited for quantifying the complexity of the individual multivariate sub-bands of the analysed signal. In this present study, we have tried to resolve this difficulty by employing TQWT for analysing the sub-band signals of the analysed multivariate signal. It should be noted that higher value of Q factor is suitable for analysing signals with oscillatory nature, whereas the lower value of Q factor is suitable for analysing signals with non-oscillatory transients in nature. Moreover, with an increased number of sub-bands and a higher value of Q-factor, a reasonably good resolution can be achieved simultaneously in high and low frequency regions of the considered signals. Finally, we have employed multivariate fuzzy entropy (mvFE to the multivariate sub-band signals obtained from the analysed signal. The proposed Q-based multivariate sub-band entropy has been studied on the publicly available bivariate Bern Barcelona focal and non-focal EEG signals database to investigate the statistical significance of the proposed features in different time segmented signals. Finally, the features are fed to random forest and least squares support vector machine (LS-SVM classifiers to select the best classifier. Our method has achieved the highest classification accuracy of 84.67% in classifying focal and non-focal EEG signals with LS-SVM classifier. The proposed multivariate sub-band fuzzy
MIXED SCHEME FOR IMAGE EDGE DETECTION BASED ON WAVELET TRANSFORM
Institute of Scientific and Technical Information of China (English)
Xie Hongmei; Yu Bianzhang; Zhao Jian
2004-01-01
A mixed scheme based on Wavelet Transformation (WT) is proposed for image edge detection. The scheme combines the wavelet transform and traditional Sobel and LoG (Laplacian of Gaussian) operator edge-detection algorithms. The precise theory analysis is given to show that the wavelet transformation has an advantage for signal processing. Simulation results show that the new scheme is better than only using the Sobel or LoG methods. Complexity analysis is also given and the conclusion is acceptable, therefore the proposed scheme is effective for edge detection.
Invariant wavelet transform-based automatic target recognition
Sadovnik, Lev S.; Rashkovskiy, Oleg; Tebelev, Igor
1995-03-01
The authors' previous work (SPIE Vol. 2237) on scale-, rotation- and shift-invariant wavelet transform is extended to accommodate multiple objects in the scene and a nonuniform background. After background elimination and segmentation, a set of windows each containing a single object are analyzed based on an invariant wavelet feature extraction algorithm and neural network-based classifier.
[The noise filtering and baseline correction for harmonic spectrum based on wavelet transform].
Guo, Yuan; Zhao, Xue-Hong; Zhang, Rui; Hu, Ya-Jun; Wang, Yan
2013-08-01
The problem of noise and baseline drift is a hot topic in infrared spectral harmonic detection system. This paper presents a new algorithm based on wavelet transform Mallet decomposition to solve the problem of eliminating a variety of complex noise and baseline drift in the harmonic detection. In the algorithm, the appropriate wavelet function and decomposition level were selected to decomposed the noise, baseline drift and useful signal in the harmonic curve into different frequency bands. the bands' information was analysed and a detecting band was set, then the information in useful frequency was reserved by zeroing method of treatment and the coefficient of the threshold. We can just use once transform and reconstruction to remove interference noise and baseline from double-harmonic signal by applying the wavelet transform technique to the harmonic detection spectrum pretreatment. Experiments show that the wavelet transform method can be used to different harmonic detection systems and has universal applicability.
对偶树复小波在脑电消噪中的应用%Application of dual-tree complex wavelet transform in EEG denoising
Institute of Scientific and Technical Information of China (English)
姚家扬; 罗志增
2015-01-01
To solve information loss and frequency aliasing by discrete wavelet transform in the process of electroencephalogram (EEG)denoising,a new EEG signal denoising algorithm was pro-posed,which was based on dual-tree complex wavelet transform.The dual-tree complex wavelet transform was used to conduct a multilayered decomposition on the EEG inputted,so the real tree and the imaginary tree could be obtained,and the median threshold function was used to process the off-spring wavelet coefficients of the real tree and the imaginary tree,then the denoised wavelet was ob-tained by the method of inverse transformation.Simulation results reveal that the SNR and mean square error (MSE)of the proposed method are better than those of traditional discrete wavelet de-noising method,and the proposed method is more suitable for processing the weak EEG signal.%为解决脑电去噪过程中离散小波带来的信息丢失与频率混叠问题，提出了一种新型对偶树复小波去噪方法。用对偶树复小波对输入脑电信号（EEG）进行多层分解，得到实树部分与虚树部分，分别对实树部与虚树部各子代小波系数进行小波中值阈值处理，再逆变换得到去噪小波。仿真结果表明：该方法可以比传统离散小波去噪方法获得更好的信噪比与均方误差，因此更适合于处理微弱的脑电信号。
Wavelet transform based ECG signal filtering implemented on FPGA
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Germán-Salló Zoltán
2011-12-01
Full Text Available Filtering electrocardiographic (ECG signals is always a challenge because the accuracy of their interpretation depends strongly on filtering results. The Discrete Wavelet Transform (DWT is an efficient, new and useful tool for signal processing applications and it’s adopted in many domains as biomedical signal filtering. This transform came about from different fields, including mathematics, physics and signal processing, it has a growing applicability due to its so-called multiresolution analyzing capabilities. FPGAs are reconfigurable logic devices made up of arrays of logic cells and routing channels having some specific characteristics which allow to use them in signal processing applications. This paper presents a DWT based ECG signal denoising method implemented on FPGA, using Matlab specific Xilinx tool, as System Generator, the procedure is simulated and evaluated through filtering specific parameters.
Li, Gang; Men, Jian-Long; Sun, Zhao-Min; Wang, Hui-Quan; Lin, Ling; Tong, Ying; Zhang, Bao-Ju
2011-02-01
Time-varying noises in spectra collection process have influence on the prediction accuracy of quantitative calibration in the non-invasive blood components measurement which is based on dynamic spectrum (DS) method. By wavelet transform, we focused on the absorbance wave of fingertip transmission spectrum in pulse frequency band. Then we increased the signal to noise ratio of DS data, and improved the detecting precision of quantitative calibration. After carrying out spectrum data continuous acquisition of the same subject for 10 times, we used wavelet transform de-noising to increase the average correlation coefficient of DS data from 0.979 6 to 0.990 3. BP neural network was used to establish the calibration model of subjects' blood components concentration values against dynamic spectrum data of 110 volunteers. After wavelet transform de-noising, the correlation coefficient of prediction set increased from 0.677 4 to 0.846 8, and the average relative error was decreased from 15.8% to 5.3%. Experimental results showed that the introduction of wavelet transform can effectively remove the noise in DS data, improve the detecting precision, and accelerate the development of non-invasive blood components measurement based on DS method.
IMPROVEMENT OF ANOMALY DETECTION ALGORITHMS IN HYPERSPECTRAL IMAGES USING DISCRETE WAVELET TRANSFORM
Kamal Jamshidi; Mohsen Zare Baghbidi; Ahmad Reza Naghsh Nilchi; Saeid Homayouni
2012-01-01
Recently anomaly detection (AD) has become an important application for target detection in hyperspectral remotely sensed images. In many applications, in addition to high accuracy of detection we need a fast and reliable algorithm as well. This paper presents a novel method to improve the performance of current AD algorithms. The proposed method first calculates Discrete Wavelet Transform (DWT) of every pixel vector of image using Daubechies4 wavelet. Then, AD algorithm performs on four band...
A Secret Image Sharing Method Using Integer Wavelet Transform
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Li Ching-Chung
2007-01-01
Full Text Available A new image sharing method, based on the reversible integer-to-integer (ITI wavelet transform and Shamir's threshold scheme is presented, that provides highly compact shadows for real-time progressive transmission. This method, working in the wavelet domain, processes the transform coefficients in each subband, divides each of the resulting combination coefficients into shadows, and allows recovery of the complete secret image by using any or more shadows . We take advantages of properties of the wavelet transform multiresolution representation, such as coefficient magnitude decay and excellent energy compaction, to design combination procedures for the transform coefficients and processing sequences in wavelet subbands such that small shadows for real-time progressive transmission are obtained. Experimental results demonstrate that the proposed method yields small shadow images and has the capabilities of real-time progressive transmission and perfect reconstruction of secret images.
Terahertz digital holography image denoising using stationary wavelet transform
Cui, Shan-Shan; Li, Qi; Chen, Guanghao
2015-04-01
Terahertz (THz) holography is a frontier technology in terahertz imaging field. However, reconstructed images of holograms are inherently affected by speckle noise, on account of the coherent nature of light scattering. Stationary wavelet transform (SWT) is an effective tool in speckle noise removal. In this paper, two algorithms for despeckling SAR images are implemented to THz images based on SWT, which are threshold estimation and smoothing operation respectively. Denoised images are then quantitatively assessed by speckle index. Experimental results show that the stationary wavelet transform has superior denoising performance and image detail preservation to discrete wavelet transform. In terms of the threshold estimation, high levels of decomposing are needed for better denoising result. The smoothing operation combined with stationary wavelet transform manifests the optimal denoising effect at single decomposition level, with 5×5 average filtering.
Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram
Energy Technology Data Exchange (ETDEWEB)
Anant, K.S.
1997-06-01
In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals. The two key signal processing applications of the wavelet transform, namely feature identification and representation (i.e., compression), are shown by solving important problems involving the seismogram and the electrocardiogram. The seismic feature identification problem involved locating in time the P and S phase arrivals. Locating these arrivals accurately (particularly the S phase) has been a constant issue in seismic signal processing. In Chapter 3, I show that the wavelet transform can be used to locate both the P as well as the S phase using only information from single station three-component seismograms. This is accomplished by using the basis function (wave-let) of the wavelet transform as a matching filter and by processing information across scales of the wavelet domain decomposition. The `pick` time results are quite promising as compared to analyst picks. The representation application involved the compression of the electrocardiogram which is a recording of the electrical activity of the heart. Compression of the electrocardiogram is an important problem in biomedical signal processing due to transmission and storage limitations. In Chapter 4, I develop an electrocardiogram compression method that applies vector quantization to the wavelet transform coefficients. The best compression results were obtained by using orthogonal wavelets, due to their ability to represent a signal efficiently. Throughout this thesis the importance of choosing wavelets based on the problem at hand is stressed. In Chapter 5, I introduce a wavelet design method that uses linear prediction in order to design wavelets that are geared to the signal or feature being analyzed. The use of these designed wavelets in a test feature identification application led to positive results. The methods developed in this thesis; the
Facial Expression Recognition Using Stationary Wavelet Transform Features
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Huma Qayyum
2017-01-01
Full Text Available Humans use facial expressions to convey personal feelings. Facial expressions need to be automatically recognized to design control and interactive applications. Feature extraction in an accurate manner is one of the key steps in automatic facial expression recognition system. Current frequency domain facial expression recognition systems have not fully utilized the facial elements and muscle movements for recognition. In this paper, stationary wavelet transform is used to extract features for facial expression recognition due to its good localization characteristics, in both spectral and spatial domains. More specifically a combination of horizontal and vertical subbands of stationary wavelet transform is used as these subbands contain muscle movement information for majority of the facial expressions. Feature dimensionality is further reduced by applying discrete cosine transform on these subbands. The selected features are then passed into feed forward neural network that is trained through back propagation algorithm. An average recognition rate of 98.83% and 96.61% is achieved for JAFFE and CK+ dataset, respectively. An accuracy of 94.28% is achieved for MS-Kinect dataset that is locally recorded. It has been observed that the proposed technique is very promising for facial expression recognition when compared to other state-of-the-art techniques.
Wavelets theory and applications for manufacturing
Gao, Robert X
2011-01-01
With the aim of facilitating signal processing in manufacturing, this book presents a systematic description of the fundamentals on wavelet transform and the ways of applying it to the condition monitoring and health diagnosis of rotating machine components.
Contrast Enhancement of Radiographs Using Shift Invariant Wavelet Transform
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A novel approach using shift invariant wavelet transform is presented for the contrast enhancement of radiographs. By exploiting cross-scale correlation among wavelet coefficients, edge information of radiographic images is extracted and protected, while noise is smoothed out in the wavelet domain. Radiographs are then reconstructed from the transform coefficients modified at multi-scales by nonlinear enhancement operator. The method can achieve effectively contrast enhancement and edge-preserved denoising simultaneously, yet it is capable of giving visually distinct images and offering considerable benefits in medical diagnosis.
Wavelet analysis and its applications an introduction
Yajnik, Archit
2013-01-01
"Wavelet analysis and its applications: an introduction" demonstrates the consequences of Fourier analysis and introduces the concept of wavelet followed by applications lucidly. While dealing with one dimension signals, sometimes they are required to be oversampled. A novel technique of oversampling the digital signal is introduced in this book alongwith necessary illustrations. The technique of feature extraction in the development of optical character recognition software for any natural language alongwith wavelet based feature extraction technique is demonstrated using multiresolution analysis of wavelet in the book.
Chen, Cao; Chu, Xinzhao
2017-09-01
Waves in the atmosphere and ocean are inherently intermittent, with amplitudes, frequencies, or wavelengths varying in time and space. Most waves exhibit wave packet-like properties, propagate at oblique angles, and are often observed in two-dimensional (2-D) datasets. These features make the wavelet transforms, especially the 2-D wavelet approach, more appealing than the traditional windowed Fourier analysis, because the former allows adaptive time-frequency window width (i.e., automatically narrowing window size at high frequencies and widening at low frequencies), while the latter uses a fixed envelope function. This study establishes the mathematical formalism of modified 1-D and 2-D Morlet wavelet transforms, ensuring that the power of the wavelet transform in the frequency/wavenumber domain is equivalent to the mean power of its counterpart in the time/space domain. Consequently, the modified wavelet transforms eliminate the bias against high-frequency/small-scale waves in the conventional wavelet methods and many existing codes. Based on the modified 2-D Morlet wavelet transform, we put forward a wave recognition methodology that automatically identifies and extracts 2-D quasi-monochromatic wave packets and then derives their wave properties including wave periods, wavelengths, phase speeds, and time/space spans. A step-by-step demonstration of this methodology is given on analyzing the lidar data taken during 28-30 June 2014 at McMurdo, Antarctica. The newly developed wave recognition methodology is then applied to two more lidar observations in May and July 2014, to analyze the recently discovered persistent gravity waves in Antarctica. The decomposed inertia-gravity wave characteristics are consistent with the conclusion in Chen et al. (2016a) that the 3-10 h waves are persistent and dominant, and exhibit lifetimes of multiple days. They have vertical wavelengths of 20-30 km, vertical phase speeds of 0.5-2 m/s, and horizontal wavelengths up to several
Application of wavelets in speech processing
Farouk, Mohamed Hesham
2014-01-01
This book provides a survey on wide-spread of employing wavelets analysis in different applications of speech processing. The author examines development and research in different application of speech processing. The book also summarizes the state of the art research on wavelet in speech processing.
Cheng, Lizhi; Luo, Yong; Chen, Bo
2014-01-01
This book could be divided into two parts i.e. fundamental wavelet transform theory and method and some important applications of wavelet transform. In the first part, as preliminary knowledge, the Fourier analysis, inner product space, the characteristics of Haar functions, and concepts of multi-resolution analysis, are introduced followed by a description on how to construct wavelet functions both multi-band and multi wavelets, and finally introduces the design of integer wavelets via lifting schemes and its application to integer transform algorithm. In the second part, many applications are discussed in the field of image and signal processing by introducing other wavelet variants such as complex wavelets, ridgelets, and curvelets. Important application examples include image compression, image denoising/restoration, image enhancement, digital watermarking, numerical solution of partial differential equations, and solving ill-conditioned Toeplitz system. The book is intended for senior undergraduate stude...
Early Detection of Rogue Waves by the Wavelet Transforms
Bayindir, Cihan
2015-01-01
We discuss the possible advantages of using the wavelet transform over the Fourier transform for the early detection of rogue waves. We show that the triangular wavelet spectra of the rogue waves can be detected at early stages of the development of rogue waves in a chaotic wave field. Compared to the Fourier spectra, the wavelet spectra is capable of detecting not only the emergence of a rogue wave but also its possible spatial (or temporal) location. Due to this fact, wavelet transform is also capable of predicting the characteristic distances between successive rogue waves. Therefore multiple simultaneous breaking of the successive rogue waves on ships or on the offshore structures can be predicted and avoided by smart designs and operations.
Tree-structured wavelet transform signature for classification of melanoma
Patwardhan, Sachin V.; Dhawan, Atam P.; Relue, Patricia A.
2002-05-01
The purpose of this work is to evaluate the use of a wavelet transform based tree structure in classifying skin lesion images in to melanoma and dysplastic nevus based on the spatial/frequency information. The classification is done using the wavelet transform tree structure analysis. Development of the tree structure in the proposed method uses energy ratio thresholds obtained from a statistical analysis of the coefficients in the wavelet domain. The method is used to obtain a tree structure signature of melanoma and dysplastic nevus, which is then used to classify the data set in to the two classes. Images are classified by using a semantic comparison of the wavelet transform tree structure signatures. Results show that the proposed method is effective and simple for classification based on spatial/frequency information, which also includes the textural information.
Tree wavelet approximations with applications
Institute of Scientific and Technical Information of China (English)
XU Yuesheng; ZOU Qingsong
2005-01-01
We construct a tree wavelet approximation by using a constructive greedy scheme(CGS). We define a function class which contains the functions whose piecewise polynomial approximations generated by the CGS have a prescribed global convergence rate and establish embedding properties of this class. We provide sufficient conditions on a tree index set and on bi-orthogonal wavelet bases which ensure optimal order of convergence for the wavelet approximations encoded on the tree index set using the bi-orthogonal wavelet bases. We then show that if we use the tree index set associated with the partition generated by the CGS to encode a wavelet approximation, it gives optimal order of convergence.
De-Noising SPECT Images from a Typical Collimator Using Wavelet Transform
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Farshid Babapour Mofrad
2009-12-01
Full Text Available Introduction: SPECT is a diagnostic imaging technique the main disadvantage of which is the existence of Poisson noise. So far, different methods have been used by scientists to improve SPECT images. The Wavelet Transform is a new method for de-noising which is widely used for noise reduction and quality enhancement of images. The purpose of this paper is evaluation of noise reduction in SPECT images by wavelet. Material and Methods: To calculate and simulate noise in images, it is common in nuclear medicine to use Monte Carlo techniques. The SIMIND software was used to simulate SPECT images in this research. The simulated and real images formed using the current typical (hexagonal collimator were de-noised by different types of wavelets. Results: The best type of wavelet was selected for SPECT images. The results demonstrated that the best type of wavelet in the simulated and real images increased Signal to Noise Ratio (SNR by 33% and 45% respectively. Also, Coefficient of Variation (CV decreased by 77% and 71% respectively, while Contrast of Recovery (CR was reduced by only 4% and 9% respectively. Conclusion: Comparing the results for real SPECT images in this paper with previously acquired results in real PET images, it can be concluded that the images of both nuclear medicine systems using Wavelet Transform differ in SNR and CR by only 5% and 7% respectively, and in CV by about 20%. Therefore, wavelet transform is applicable for nuclear medicine image de-noising.
THEORY AND APPLICATION OF WAVELET ANALYSIS INSTRUMENT LIBRARY
Institute of Scientific and Technical Information of China (English)
BO Lin; QIN Shuren; LIU Xiaofeng
2006-01-01
Some new theory and algorithms on wavelet analysis are proposed, including continuous wavelet transform (CWT), discrete wavelet transform (DWT), wavelet package transform (WPT),wavelet denosing and mother wavelet selection, etc. Using the component-based hierarchy mode, the platform for virtual instrument (Ⅵ) is constructed, and the functions such as data sampling, data analysis and data present, etc are provided. Subsequently, the wavelet analysis library is designed and developed. The library consists of expert system, experienced database, development platform and abundant wavelet analysis functional module, which together implement general and special wavelet analysis in the field of mechanical engineering, energy source, transportation and biomedicine, etc.Finally, the wavelet analysis virtual instrument library is applied to detect fault called engine knock.Experimental result indicates that the wavelet analysis virtual instrument library can efficiently solve the engineering problem such as detecting engine knock.
Using the Dual-Tree Complex Wavelet Transform for Improved Fabric Defect Detection
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Hermanus Vermaak
2016-01-01
Full Text Available The dual-tree complex wavelet transform (DTCWT solves the problems of shift variance and low directional selectivity in two and higher dimensions found with the commonly used discrete wavelet transform (DWT. It has been proposed for applications such as texture classification and content-based image retrieval. In this paper, the performance of the dual-tree complex wavelet transform for fabric defect detection is evaluated. As experimental samples, the fabric images from TILDA, a textile texture database from the Workgroup on Texture Analysis of the German Research Council (DFG, are used. The mean energies of real and imaginary parts of complex wavelet coefficients taken separately are identified as effective features for the purpose of fabric defect detection. Then it is shown that the use of the dual-tree complex wavelet transform yields greater performance as compared to the undecimated wavelet transform (UDWT with a detection rate of 4.5% to 15.8% higher depending on the fabric type.
Wavelet Transform - A New Tool for Analysis of Harmonics in Power Systems
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Osipov D. S.
2016-01-01
Full Text Available This paper presents a review of application of discrete wavelet transform in power system transient analyses. Based on the discrete time domain approximation, the system components such as resistor and inductor are modeled respectively in discrete wavelet domain for the purpose of transient and steady state analyses. Numerical results for transient inductor model can be implemented by any kind of power system including normal and emergency operating modes.
Combining Wavelet Transform and Hidden Markov Models for ECG Segmentation
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Jérôme Boudy
2007-01-01
Full Text Available This work aims at providing new insights on the electrocardiogram (ECG segmentation problem using wavelets. The wavelet transform has been originally combined with a hidden Markov models (HMMs framework in order to carry out beat segmentation and classification. A group of five continuous wavelet functions commonly used in ECG analysis has been implemented and compared using the same framework. All experiments were realized on the QT database, which is composed of a representative number of ambulatory recordings of several individuals and is supplied with manual labels made by a physician. Our main contribution relies on the consistent set of experiments performed. Moreover, the results obtained in terms of beat segmentation and premature ventricular beat (PVC detection are comparable to others works reported in the literature, independently of the type of the wavelet. Finally, through an original concept of combining two wavelet functions in the segmentation stage, we achieve our best performances.
Human Iris Recognition System using Wavelet Transform and LVQ
Energy Technology Data Exchange (ETDEWEB)
Lee, Kwan Yong; Lim, Shin Young [Electronics and Telecommunications Research Institute (Korea); Cho, Seong Won [Hongik University (Korea)
2000-07-01
The popular methods to check the identity of individuals include passwords and ID cards. These conventional methods for user identification and authentication are not altogether reliable because they can be stolen and forgotten. As an alternative of the existing methods, biometric technology has been paid much attention for the last few decades. In this paper, we propose an efficient system for recognizing the identity of a living person by analyzing iris patterns which have a high level of stability and distinctiveness than other biometric measurements. The proposed system is based on wavelet transform and a competitive neural network with the improved mechanisms. After preprocessing the iris data acquired through a CCD camera, feature vectors are extracted by using Haar wavelet transform. LVQ(Learning Vector Quantization) is exploited to classify these feature vectors. We improve the overall performance of the proposed system by optimizing the size of feature vectors and by introducing an efficient initialization of the weight vectors and a new method for determining the winner in order to increase the recognition accuracy of LVQ. From the experiments, we confirmed that the proposed system has a great potential of being applied to real applications in an efficient and effective way. (author). 14 refs., 13 figs., 7 tabs.
Remote sensing image compression method based on lift scheme wavelet transform
Tao, Hongjiu; Tang, Xinjian; Liu, Jian; Tian, Jinwen
2003-06-01
Based on lifting scheme and the construction theorem of the integer Haar wavelet and biorthogonal wavelet, we propose a new integer wavelet transform construct method on the basis of lift scheme after introduciton of constructing specific-demand biorthogonal wavelet transform using Harr wavelet and Lazy wavelet. In this paper, we represent the method and algorithm of the lifting scheme, and we also give mathematical formulation on this method and experimental results as well.
New Blocking Artifacts Reduction Method Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
SHI Min; YI Qing-ming
2007-01-01
It is well known that a block discrete cosine transform compressed image exhibits visually annoying blocking artifacts at low-bit-rate. A new post-processing deblocking algorithm in wavelet domain is proposed. The algorithm exploits blocking-artifact features shown in wavelet domain. The energy of blocking artifacts is concentrated into some lines to form annoying visual effects after wavelet transform. The aim of reducing blocking artifacts is to capture excessive energy on the block boundary effectively and reduce it below the visual scope. Adaptive operators for different subbands are computed based on the wavelet coefficients. The operators are made adaptive to different images and characteristics of blocking artifacts. Experimental results show that the proposed method can significantly improve the visual quality and also increase the peak signal-noise-ratio(PSNR) in the output image.
Digital Watermarking Algorithm Based on Wavelet Transform and Neural Network
Institute of Scientific and Technical Information of China (English)
WANG Zhenfei; ZHAI Guangqun; WANG Nengchao
2006-01-01
An effective blind digital watermarking algorithm based on neural networks in the wavelet domain is presented. Firstly, the host image is decomposed through wavelet transform. The significant coefficients of wavelet are selected according to the human visual system (HVS) characteristics. Watermark bits are added to them. And then effectively cooperates neural networks to learn the characteristics of the embedded watermark related to them. Because of the learning and adaptive capabilities of neural networks, the trained neural networks almost exactly recover the watermark from the watermarked image. Experimental results and comparisons with other techniques prove the effectiveness of the new algorithm.
THE WAVELET TRANSFORM OF PERIODIC FUNCTION AND NONSTATIONARY PERIODIC FUNCTION
Institute of Scientific and Technical Information of China (English)
刘海峰; 周炜星; 王辅臣; 龚欣; 于遵宏
2002-01-01
Some properties of the wavelet transform of trigonometric function, periodic function and nonstationary periodic function have been investigated. The results show that the peak height and width in wavelet energy spectrum of a periodic function are in proportion to its period. At the same time, a new equation, which can truly reconstruct a trigonometric function with only one scale wavelet coefficient, is presented. The reconstructed wave shape of a periodic function with the equation is better than any term of its Fourier series. And the reconstructed wave shape of a class of nonstationary periodic function with this equation agrees well with the function.
Energy Technology Data Exchange (ETDEWEB)
Hsieh, Cheng-Tao [Department of Electrical Engineering, Kun Shan University, Tainan 70101 (China); Lin, Jeu-Min [Department of Electrical Engineering, Far Eat University, Tainan 70101 (China); Huang, Shyh-Jier [Department of Electrical Engineering, National Cheng Kung University, Tainan 70101 (China)
2008-12-15
In this paper, a wavelet transform-based approach is proposed to detect the occurrence of islanding events in distributed generation systems. Thanks to time-frequency localization capabilities exhibited by wavelet transform, the approach embedded with this transform technique has grasped the appearance of the islanding event in a highly effective manner. Moreover, for those regions which are in need of a better visualization, the proposed approach would serve as an efficient aid such that the mains power disconnection can be better distinguished. To validate the feasibility of this approach, the method has been validated through several scenarios. Test results supported the effectiveness of the method for the application considered. (author)
Adaptive synthesis of a wavelet transform using fast neural network
J. Stolarek
2011-01-01
This paper introduces a new method for an adaptive synthesis of a wavelet transform using a fast neural network with a topology based on the lattice structure. The lattice structure and the orthogonal lattice structure are presented and their properties are discussed. A novel method for unsupervised training of the neural network is introduced. The proposed approach is tested by synthesizing new wavelets with an expected energy distribution between low- and high-pass filters. Energy compactio...
Automatic Image Registration Algorithm Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
LIU Qiong; NI Guo-qiang
2006-01-01
An automatic image registration approach based on wavelet transform is proposed. This proposed method utilizes multiscale wavelet transform to extract feature points. A coarse-to-fine feature matching method is utilized in the feature matching phase. A two-way matching method based on cross-correlation to get candidate point pairs and a fine matching based on support strength combine to form the matching algorithm. At last, based on an affine transformation model, the parameters are iteratively refined by using the least-squares estimation approach. Experimental results have verified that the proposed algorithm can realize automatic registration of various kinds of images rapidly and effectively.
Region-Based Fractional Wavelet Transform Using Post Processing Artifact Reduction
Directory of Open Access Journals (Sweden)
Jassim M. Abdul-Jabbar
2010-06-01
Full Text Available Wavelet-based algorithms are increasingly used in the source coding of remote sensing, satellite and other geospatial imagery. At the same time, wavelet-based coding applications are also increased in robust communication and network transmission of images. Although wireless multimedia sensors are widely used to deliver multimedia content due to the availability of inexpensive CMOS cameras, their computational and memory resources are still typically very limited. It is known that allowing a low-cost camera sensor node with limited RAM size to perform a multi-level wavelet transform, will in return limit the size of the acquired image. Recently, fractional wavelet filter technique became an interesting solution to reduce communication energy and wireless bandwidth, for resource-constrained devices (e.g. digital cameras. The reduction in the required memory in these fractional wavelet transforms is achieved at the expense of the image quality. In this paper, an adaptive fractional artifacts reduction approach is proposed for efficient filtering operations according to the desired compromise between the effectiveness of artifact reduction and algorithm simplicity using some local image features to reduce boundaries artifacts caused by fractional wavelet. Applying such technique on different types of images with different sizes using CDF 9/7 wavelet filters results in a good performance.
MRS3D: 3D Spherical Wavelet Transform on the Sphere
Lanusse, F.; Rassat, A.; Starck, J.-L.
2011-12-01
Future cosmological surveys will provide 3D large scale structure maps with large sky coverage, for which a 3D Spherical Fourier-Bessel (SFB) analysis is natural. Wavelets are particularly well-suited to the analysis and denoising of cosmological data, but a spherical 3D isotropic wavelet transform does not currently exist to analyse spherical 3D data. We present a new fast Discrete Spherical Fourier-Bessel Transform (DSFBT) based on both a discrete Bessel Transform and the HEALPIX angular pixelisation scheme. We tested the 3D wavelet transform and as a toy-application, applied a denoising algorithm in wavelet space to the Virgo large box cosmological simulations and found we can successfully remove noise without much loss to the large scale structure. The new spherical 3D isotropic wavelet transform, called MRS3D, is ideally suited to analysing and denoising future 3D spherical cosmological surveys; it uses a novel discrete spherical Fourier-Bessel Transform. MRS3D is based on two packages, IDL and Healpix and can be used only if these two packages have been installed.
Predictive depth coding of wavelet transformed images
Lehtinen, Joonas
1999-10-01
In this paper, a new prediction based method, predictive depth coding, for lossy wavelet image compression is presented. It compresses a wavelet pyramid composition by predicting the number of significant bits in each wavelet coefficient quantized by the universal scalar quantization and then by coding the prediction error with arithmetic coding. The adaptively found linear prediction context covers spatial neighbors of the coefficient to be predicted and the corresponding coefficients on lower scale and in the different orientation pyramids. In addition to the number of significant bits, the sign and the bits of non-zero coefficients are coded. The compression method is tested with a standard set of images and the results are compared with SFQ, SPIHT, EZW and context based algorithms. Even though the algorithm is very simple and it does not require any extra memory, the compression results are relatively good.
Denoising CT Images using wavelet transform
Directory of Open Access Journals (Sweden)
Lubna Gabralla
2015-05-01
Full Text Available Image denoising is one of the most significant tasks especially in medical image processing, where the original images are of poor quality due the noises and artifacts introduces by the acquisition systems. In this paper, we propose a new image denoising scheme by modifying the wavelet coefficients using soft-thresholding method, we present a comparative study of different wavelet denoising techniques for CT images and we discuss the obtained results. The denoising process rejects noise by thresholding in the wavelet domain. The performance is evaluated using Peak Signal-to-Noise Ratio (PSNR and Mean Squared Error (MSE. Finally, Gaussian filter provides better PSNR and lower MSE values. Hence, we conclude that this filter is an efficient one for preprocessing medical images.
Wavelets for approximate Fourier transform and data compression
Guo, Haitao
This dissertation has two parts. In the first part, we develop a wavelet-based fast approximate Fourier transform algorithm. The second part is devoted to the developments of several wavelet-based data compression techniques for image and seismic data. We propose an algorithm that uses the discrete wavelet transform (DWT) as a tool to compute the discrete Fourier transform (DFT). The classical Cooley-Tukey FFT is shown to be a special case of the proposed algorithm when the wavelets in use are trivial. The main advantage of our algorithm is that the good time and frequency localization of wavelets can be exploited to approximate the Fourier transform for many classes of signals, resulting in much less computation. Thus the new algorithm provides an efficient complexity versus accuracy tradeoff. When approximations are allowed, under certain sparsity conditions, the algorithm can achieve linear complexity, i.e. O(N). The proposed algorithm also has built-in noise reduction capability. For waveform and image compression, we propose a novel scheme using the recently developed Burrows-Wheeler transform (BWT). We show that the discrete wavelet transform (DWT) should be used before the Burrows-Wheeler transform to improve the compression performance for many natural signals and images. We demonstrate that the simple concatenation of the DWT and BWT coding performs comparably as the embedded zerotree wavelet (EZW) compression for images. Various techniques that significantly improve the performance of our compression scheme are also discussed. The phase information is crucial for seismic data processing. However, traditional compression schemes do not pay special attention to preserving the phase of the seismic data, resulting in the loss of critical information. We propose a lossy compression method that preserves the phase as much as possible. The method is based on the self-adjusting wavelet transform that adapts to the locations of the significant signal components
Surface Electromyography Feature Extraction Based on Wavelet Transform
Directory of Open Access Journals (Sweden)
Farzaneh Akhavan Mahdavi
2012-12-01
Full Text Available Considering the vast variety of EMG signal applications such as rehabilitation of people suffering from some mobility limitations, scientists have done much research on EMG control system. In this regard, feature extraction of EMG signal has been highly valued as a significant technique to extract the desired information of EMG signal and remove unnecessary parts. In this study, Wavelet Transform (WT has been applied as the main technique to extract Surface EMG (SEMG features because WT is consistent with the nature of EMG as a nonstationary signal. Furthermore, two evaluation criteria, namely, RES index (the ratio of a Euclidean distance to a standard deviation and scatter plot are recruited to investigate the efficiency of wavelet feature extraction. The results illustrated an improvement in class separability of hand movements in feature space. Accordingly, it has been shown that only the SEMG features extracted from first and second level of WT decomposition by second order of Daubechies family (db2 yielded the best class separability.
Fast Wavelet Transform Algorithms With Low Memory Requirements
Directory of Open Access Journals (Sweden)
Maya Babuji
2010-06-01
Full Text Available In this paper, a new algorithm to efficiently compute the two-dimensional wavelet transform is presented. This algorithm aims at low memory consumption and reduced complexity, meeting these requirements by means of line-by-line processing. In this proposal,we use recursion to automatically place the order in which the wavelet transform is computed. This way, we solve some synchronization problems that have not been tackled byprevious proposals. Furthermore, unlike other similar proposals, our proposal can be straightforwardly implemented from the algorithm description. To this end, a general algorithm is given which is further detailed to allow its implementation with a simple filterbank or using the more efficient lifting scheme. We also include a new fast run-length encoder to be used along with the proposed wavelet transform for fast image compression and reduced memory consumption.
ECG Signal Analysis and Arrhythmia Detection using Wavelet Transform
Kaur, Inderbir; Rajni, Rajni; Marwaha, Anupma
2016-12-01
Electrocardiogram (ECG) is used to record the electrical activity of the heart. The ECG signal being non-stationary in nature, makes the analysis and interpretation of the signal very difficult. Hence accurate analysis of ECG signal with a powerful tool like discrete wavelet transform (DWT) becomes imperative. In this paper, ECG signal is denoised to remove the artifacts and analyzed using Wavelet Transform to detect the QRS complex and arrhythmia. This work is implemented in MATLAB software for MIT/BIH Arrhythmia database and yields the sensitivity of 99.85 %, positive predictivity of 99.92 % and detection error rate of 0.221 % with wavelet transform. It is also inferred that DWT outperforms principle component analysis technique in detection of ECG signal.
The fast parametric slantlet transform with applications
Agaian, Sos S.; Tourshan, Khaled; Noonan, Joseph P.
2004-05-01
Transform methods have played an important role in signal and image processing applications. Recently, Selesnick has constructed the new orthogonal discrete wavelet transform, called the slantlet wavelet, with two zero moments and with improved time localization. The discrete slantlet wavelet transform is carried out by an existing filterbank which lacks a tree structure and has a complexity problem. The slantlet wavelet has been successfully applied in compression and denoising. In this paper, we present a new class of orthogonal parametric fast Haar slantlet transform system where the slantlet wavelet and Haar transforms are special cases of it. We propose designing the slantlet wavelet transform using Haar slantlet transform matrix. A new class of parametric filterbanks is developed. The behavior of the parametric Haar slantlet transforms in signal and image denoising is presented. We show that the new technique performs better than the slantlet wavelet transform in denoising for piecewise constant signals. We also show that the parametric Haar slantlet transform performs better than the cosine and Fourier transforms for grey level images.
Steganography Based on Integer Wavelet Transform and Bicubic Interpolation
Directory of Open Access Journals (Sweden)
N. Ajeeshvali
2012-11-01
Full Text Available Steganography is the art and science of hiding information in unremarkable cover media so as not to observe any suspicion. It is an application under information security field, being classified under information security, Steganography will be characterized by having set of measures that rely on strengths and counter attacks that are caused by weaknesses and vulnerabilities. The aim of this paper is to propose a modified high capacity image steganography technique that depends on integer wavelet transform with acceptable levels of imperceptibility and distortion in the cover image as a medium file and high levels of security. Bicubic interpolation causes overshoot, which increases acutance (apparent sharpness. The Bicubic algorithm is frequently used for scaling images and video for display. The algorithm preserves fine details of the image better than the common bilinear algorithm.
Lin, Yong; Liu, Shirong; Li, Chongwei; Ge, Jianqing; Suo, Anning; Chen, Baoyu
2005-09-01
Runoff is an important component of regional water resources, and its dynamics is to some extent an indicator of water resources dynamics in a region. To know the runoff dynamics and water resources in a region is essential for the sustainable utilization and planning of water resources, and for the research on hydrological response of vegetation change at watershed scale. To disclose the water resources dynamics in Upper Minjiang River, one of the large reaches of Yangze River in southwest China, this paper analyzed the runoff dynamic features of Zagunao watershed, an important watershed in Minjiang River basin. Multi-Resolution Analysis (MRA) and periodicity analysis were conducted with Dmey wavelet function on the monthly runoff data from 1962 to 2002 observed by Zagunao hydrological station, which provided a data-based approximation on the evolution of monthly runoff in Zagunao watershed. It was found that the runoff dynamics in Zagunao watershed was relatively stable during 1962 - 1978, despite that this period was just in correspondence with the term of intensive deforestation activities in Upper Minjiang River basin. It was also clear that the runoff in Zagunao watershed was increased from 1986 to 1997, which was inconsistent with the commonly accepted viewpoint that the runoff decreased with increasing vegetation cover in forest watershed. However, the increasing trend from 1986 - 1997 was consistent with the research results in Yichang by Wang Wensheng and with the global warming at global and continent scale, which meant that global climate change plays a big role in runoff dynamics in Upper Minjiang River. Periodicity analysis showed that the rich-short water periodicity at the scale of 10 years (120 months) and 5 years (60 months) was 3 and 7 times, respectively, which could provide invaluable information for the eco-hydrological function research of forest landscape in Minjiang river basin and the sustainable utilization of water resources. The results
Singularity-preserving image interpolation using wavelet transform extrema extrapolation
Zhai, Guangtao; Zhang, Yang; Zheng, Xiaoshi
2003-09-01
One common task of image interpolation is to enhance the resolution of the image, which means to magnify the image without loss in its clarity. Traditional methods often assume that the original images are smooth enough so as to possess continues derivatives, which tend to blur the edges of the interpolated image. A novel fast image interpolation algorithm based on wavelet transform and multi-resolution analysis is proposed in this paper. It uses interpolation and extrapolation polynomial to estimate the higher resolution informatoin of the image and generate a new sub-band of wavelet transform coefficients to get processed image with shaper edges and preserved singularities.
Synchronization of two 3-scroll hyperchaotic attractors using wavelet transform
Institute of Scientific and Technical Information of China (English)
Li Jian; Zhou Jiliu; Wang Yong; Zhi Yong
2006-01-01
The synchronization of two 3-scroll hyperchaotic attractors is realized based on wavelet transform and single variables' feedback. In the transmitter, one signal is decomposed by wavelet transform and the detailed information is removed, then the component with low frequency is reconstructed and sent into the channel. In the receiver, the received signal is used as the feedback signal to realize the synchronization of two chaotic systems. Using this synchronous method, the transmitting signal is transported in compressible way, the system resource is saved, furthermore, because the transported signal is not a whole chaotic signal, the performance of security of the system is improved.
FAST TEXT LOCATION BASED ON DISCRETE WAVELET TRANSFORM
Institute of Scientific and Technical Information of China (English)
Li Xiaohua; Shen Lansun
2005-01-01
The paper describes a texture-based fast text location scheme which operates directly in the Discrete Wavelet Transform (DWT) domain. By the distinguishing texture characteristics encoded in wavelet transform domain, the text is fast detected from complex background images stored in the compressed format such as JPEG2000 without full decompress. Compared with some traditional character location methods, the proposed scheme has the advantages of low computational cost, robust to size and font of characters and high accuracy. Preliminary experimental results show that the proposed scheme is efficient and effective.
2D image compression using concurrent wavelet transform
Talukder, Kamrul Hasan; Harada, Koichi
2011-10-01
In the recent years wavelet transform (WT) has been widely used for image compression. As WT is a sequential process, much time is required to transform data. Here a new approach has been presented where the transformation process is executed concurrently. As a result the procedure runs first and the time of transformation is reduced. Multiple threads are used for row and column transformation and the communication among threads has been managed effectively. Thus, the transformation time has been reduced significantly. The proposed system provides better compression ratio and PSNR value with lower time complexity.
Wavelet matrix transform for time-series similarity measurement
Institute of Scientific and Technical Information of China (English)
HU Zhi-kun; XU Fei; GUI Wei-hua; YANG Chun-hua
2009-01-01
A time-series similarity measurement method based on wavelet and matrix transform was proposed, and its anti-noise ability, sensitivity and accuracy were discussed. The time-series sequences were compressed into wavelet subspace, and sample feature vector and orthogonal basics of sample time-series sequences were obtained by K-L transform. Then the inner product transform was carried out to project analyzed time-series sequence into orthogonal basics to gain analyzed feature vectors. The similarity was calculated between sample feature vector and analyzed feature vector by the Euclid distance. Taking fault wave of power electronic devices for example, the experimental results show that the proposed method has low dimension of feature vector, the anti-noise ability of proposed method is 30 times as large as that of plain wavelet method, the sensitivity of proposed method is 1/3 as large as that of plain wavelet method, and the accuracy of proposed method is higher than that of the wavelet singular value decomposition method. The proposed method can be applied in similarity matching and indexing for lager time series databases.
Zhang, Hongbo; Yi, Xingwen; Chen, Lei; Zhang, Jing; Deng, Mingliang; Qiu, Kun
2012-10-01
As an alternate to fast Fourier transform-based orthogonal frequency-division multiplexing (OFDM), wavelet packet transform (WPT)-based OFDM (WPT-OFDM) does not require cyclic prefix to avoid inter-symbol-interference. The wavelet has many varieties and therefore, it can provide more freedom for system design to suit different applications. We propose a real-valued WPT-OFDM that uses intensity modulation/direct detection. We also conduct an experiment to verify its performance through a 75-km standard single-mode fiber.
Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany
2016-07-01
Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.
Hegazy, Maha A; Lotfy, Hayam M; Mowaka, Shereen; Mohamed, Ekram Hany
2016-07-05
Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.
Directory of Open Access Journals (Sweden)
Gözde Pektaş
2009-01-01
Full Text Available Signal processing methods based on the combined use of the continuous wavelet transform (CWT and zero-crossing technique were applied to the simultaneous spectrophotometric determination of perindopril (PER and indapamide (IND in tablets. These signal processing methods do not require any priory separation step. Initially, various wavelet families were tested to identify the optimum signal processing giving the best recovery results. From this procedure, the Haar and Biorthogonal1.5 continuous wavelet transform (HAAR-CWT and BIOR1.5-CWT, respectively were found suitable for the analysis of the related compounds. After transformation of the absorbance vectors by using HAAR-CWT and BIOR1.5-CWT, the CWT-coefficients were drawn as a graph versus wavelength and then the HAAR-CWT and BIOR1.5-CWT spectra were obtained. Calibration graphs for PER and IND were obtained by measuring the CWT amplitudes at 231.1 and 291.0 nm in the HAAR-CWT spectra and at 228.5 and 246.8 nm in BIOR1.5-CWT spectra, respectively. In order to compare the performance of HAAR-CWT and BIOR1.5-CWT approaches, derivative spectrophotometric (DS method and HPLC as comparison methods, were applied to the PER-IND samples. In this DS method, first derivative absorbance values at 221.6 for PER and 282.7 nm for IND were used to obtain the calibration graphs. The validation of the CWT and DS signal processing methods was carried out by using the recovery study and standard addition technique. In the following step, these methods were successfully applied to the commercial tablets containing PER and IND compounds and good accuracy and precision were reported for the experimental results obtained by all proposed signal processing methods.
Image compression algorithm using wavelet transform
Cadena, Luis; Cadena, Franklin; Simonov, Konstantin; Zotin, Alexander; Okhotnikov, Grigory
2016-09-01
Within the multi-resolution analysis, the study of the image compression algorithm using the Haar wavelet has been performed. We have studied the dependence of the image quality on the compression ratio. Also, the variation of the compression level of the studied image has been obtained. It is shown that the compression ratio in the range of 8-10 is optimal for environmental monitoring. Under these conditions the compression level is in the range of 1.7 - 4.2, depending on the type of images. It is shown that the algorithm used is more convenient and has more advantages than Winrar. The Haar wavelet algorithm has improved the method of signal and image processing.
AN APPLIED RESEARCH ON APPROACH OF DYADIC WAVELET TRANSFORM FOR REMOTE SENSING IMAGE EDGE DETECTION
Institute of Scientific and Technical Information of China (English)
Fu Wei; Xing Guangzhong; Hou Lantian; Qin Qiming; Wang Wenjun
2006-01-01
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.
Wavelet transform approach to video compression
Li, Jin; Cheng, Po-Yuen; Kuo, C.-C. Jay
1995-04-01
In this research, we propose a video compression scheme that uses the boundary-control vectors to represent the motion field and the embedded zerotree wavelet (EZW) to compress the displacement frame difference. When compared to the DCT-based MPEG, the proposed new scheme achieves a better compression performance in terms of the MSE (mean square error) value and visual perception for the same given bit rate.
Sohrabi, Mahmoud Reza; Darabi, Golnaz
2016-01-05
Flavonoids are γ-benzopyrone derivatives, which are highly regarded in these researchers for their antioxidant property. In this study, two new signals processing methods been coupled with UV spectroscopy for spectral resolution and simultaneous quantitative determination of Myricetin, Kaempferol and Quercetin as flavonoids in Laurel, St. John's Wort and Green Tea without the need for any previous separation procedure. The developed methods are continuous wavelet transform (CWT) and least squares support vector machine (LS-SVM) methods integrated with UV spectroscopy individually. Different wavelet families were tested by CWT method and finally the Daubechies wavelet family (Db4) for Myricetin and the Gaussian wavelet families for Kaempferol (Gaus3) and Quercetin (Gaus7) were selected and applied for simultaneous analysis under the optimal conditions. The LS-SVM was applied to build the flavonoids prediction model based on absorption spectra. The root mean square errors for prediction (RMSEP) of Myricetin, Kaempferol and Quercetin were 0.0552, 0.0275 and 0.0374, respectively. The developed methods were validated by the analysis of the various synthetic mixtures associated with a well- known flavonoid contents. Mean recovery values of Myricetin, Kaempferol and Quercetin, in CWT method were 100.123, 100.253, 100.439 and in LS-SVM method were 99.94, 99.81 and 99.682, respectively. The results achieved by analyzing the real samples from the CWT and LS-SVM methods were compared to the HPLC reference method and the results were very close to the reference method. Meanwhile, the obtained results of the one-way ANOVA (analysis of variance) test revealed that there was no significant difference between the suggested methods.
Sohrabi, Mahmoud Reza; Darabi, Golnaz
2016-01-01
Flavonoids are γ-benzopyrone derivatives, which are highly regarded in these researchers for their antioxidant property. In this study, two new signals processing methods been coupled with UV spectroscopy for spectral resolution and simultaneous quantitative determination of Myricetin, Kaempferol and Quercetin as flavonoids in Laurel, St. John's Wort and Green Tea without the need for any previous separation procedure. The developed methods are continuous wavelet transform (CWT) and least squares support vector machine (LS-SVM) methods integrated with UV spectroscopy individually. Different wavelet families were tested by CWT method and finally the Daubechies wavelet family (Db4) for Myricetin and the Gaussian wavelet families for Kaempferol (Gaus3) and Quercetin (Gaus7) were selected and applied for simultaneous analysis under the optimal conditions. The LS-SVM was applied to build the flavonoids prediction model based on absorption spectra. The root mean square errors for prediction (RMSEP) of Myricetin, Kaempferol and Quercetin were 0.0552, 0.0275 and 0.0374, respectively. The developed methods were validated by the analysis of the various synthetic mixtures associated with a well- known flavonoid contents. Mean recovery values of Myricetin, Kaempferol and Quercetin, in CWT method were 100.123, 100.253, 100.439 and in LS-SVM method were 99.94, 99.81 and 99.682, respectively. The results achieved by analyzing the real samples from the CWT and LS-SVM methods were compared to the HPLC reference method and the results were very close to the reference method. Meanwhile, the obtained results of the one-way ANOVA (analysis of variance) test revealed that there was no significant difference between the suggested methods.
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
This paper puts forward wavelet transform method to identify P and S phases in three component seismograms using polarization information contained in the wavelet transform coefficients of signal. The P and S wave locator functions are constructed by using eigenvalue analysis method to wavelet transform coefficient across several scales. Locator functions formed by wavelet transform have stated noise resistance capability, and is proved to be very effective in identifying the P and S arrivals of the test data and actual earthquake data.
Method of Infrared Image Enhancement Based on Stationary Wavelet Transform
Institute of Scientific and Technical Information of China (English)
QI Fei; LI Yan-jun; ZHANG Ke
2008-01-01
Aiming at the problem, i.e. infrared images own the characters of bad contrast ratio and fuzzy edges, a method to enhance the contrast of infrared image is given, which is based on stationary wavelet transform. After making stationary wavelet transform to an infrared image, denoising is done by the proposed method of double-threshold shrinkage in detail coefficient matrixes that have high noisy intensity. For the approximation coefficient matrix with low noisy intensity, enhancement is done by the proposed method based on histogram. The enhanced image can be got by wavelet coefficient reconstruction. Furthermore, an evaluation criterion of enhancement performance is introduced. The results show that this algorithm ensures target enhancement and restrains additive Gauss white noise effectively. At the same time, its amount of calculation is small and operation speed is fast.
Stationary wavelet transform for under-sampled MRI reconstruction.
Kayvanrad, Mohammad H; McLeod, A Jonathan; Baxter, John S H; McKenzie, Charles A; Peters, Terry M
2014-12-01
In addition to coil sensitivity data (parallel imaging), sparsity constraints are often used as an additional lp-penalty for under-sampled MRI reconstruction (compressed sensing). Penalizing the traditional decimated wavelet transform (DWT) coefficients, however, results in visual pseudo-Gibbs artifacts, some of which are attributed to the lack of translation invariance of the wavelet basis. We show that these artifacts can be greatly reduced by penalizing the translation-invariant stationary wavelet transform (SWT) coefficients. This holds with various additional reconstruction constraints, including coil sensitivity profiles and total variation. Additionally, SWT reconstructions result in lower error values and faster convergence compared to DWT. These concepts are illustrated with extensive experiments on in vivo MRI data with particular emphasis on multiple-channel acquisitions.
Pautomatic Sea Target Detection Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
PEI Li-li; LUO Hai-bo
2009-01-01
An effective automatic target detection algorithm based on wavelet transform, which takes advantage of the localization and the orientation of wavelet analysis, is proposed. The algorithm detects the target in the vertical component of the wavelet transformation of the image. After mutual energy combination and sea clutter suppression through spatial weighting and thresholding, the target is located through maximum energy determination and its size is indicated through similarity measurement function of two overlapping windows. Experiment results show that the target can be detected by the algorithm in a single image frame and the better efficiency can be obtained also under the complicated backgrounds of existing the disturbances of cloud layer and fish scale light.
Directory of Open Access Journals (Sweden)
Na Wu
2013-11-01
Full Text Available Transformer differential protection may be of malfunction at the emergence of inrush current, and it will affect the normal operation of the transformer. So the paper puts forward a new application of wavelet energy spectrum entropy-neural network theory in transformer microcomputer protection, in which the multi-resolution analysis of wavelet transform and information entropy technology are combined firstly and forms a new conception named wavelet energy spectrum entropy, and it will be put into neural network theory as the feature vector, forms the new algorithm in the end. This method decomposes signal through wavelet transform, and extracts the high frequency part of energy in each scale of wavelet transform from inrush current signal and the short circuit current signal, and calculates the wavelet energy entropy value, which will be as the input feature vector of modified BP neural network. And this feature vector is used as training characteristic value for training in BP neural network. According to the measured data of the system, it has achieved good effect. At the same time, for the large amount of calculation and the high requirements of signal sampling rate in wavelet energy entropy - neural network algorithm, a new idea which uses the high-speed hardware platform of FPGA to realize the algorithm application is put forward, and it will break the bottleneck of traditional microcomputer protection that the MCU would not give consideration to both the speed and the accuracy of the protection at the same time.
Improvement of Anomoly Detection Algorithms in Hyperspectral Images using Discrete Wavelet Transform
Baghbidi, Mohsen Zare; Nilchi, Ahmad Reza Naghsh; Homayouni, Saeid; 10.5121/sipij.2011.2402
2012-01-01
Recently anomaly detection (AD) has become an important application for target detection in hyperspectral remotely sensed images. In many applications, in addition to high accuracy of detection we need a fast and reliable algorithm as well. This paper presents a novel method to improve the performance of current AD algorithms. The proposed method first calculates Discrete Wavelet Transform (DWT) of every pixel vector of image using Daubechies4 wavelet. Then, AD algorithm performs on four bands of "Wavelet transform" matrix which are the approximation of main image. In this research some benchmark AD algorithms including Local RX, DWRX and DWEST have been implemented on Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral datasets. Experimental results demonstrate significant improvement of runtime in proposed method. In addition, this method improves the accuracy of AD algorithms because of DWT's power in extracting approximation coefficients of signal, which contain the main behaviour of sig...
Energy Technology Data Exchange (ETDEWEB)
Rodriguez G, A.; Bowtell, R.; Mansfield, P. [Area de Procesamiento Digital de Senales e Imagenes Biomedicas. Universidad Autonoma Metropolitana Iztapalapa. Mexico D.F. 09340 Mexico (Mexico)
1998-12-31
Velocity maps were studied combining Doyle and Mansfield method (1986) with each of the following transforms: Fourier, window Fourier and wavelet (Mexican hat). Continuous wavelet transform was compared against the two Fourier transform to determine which technique is best suited to study blood maps generated by Half Fourier Echo-Planar Imaging. Coefficient images were calculated and plots of the pixel intensity variation are presented. Finally, contour maps are shown to visualize the behavior of the blood flow in the cardiac chambers for the wavelet technique. (Author)
Quantum Mechanics Version of Wavelet Transform Studied by Virtue of IWOP Technique
Institute of Scientific and Technical Information of China (English)
FAN Hong-Yi; L(U) Jian-Feng
2004-01-01
Using the technique of integral within an ordered product (IWOP) of operators we show that the wavelet transform can be recasted to a matrix element of squeezing-displacing operator between the mother wavelet state vector and the state vector to be transformed in the context of quantum mechanics. In this way many quantum optical states'wavelet transform can be easily derived.
Implementation of Texture Based Image Retrieval Using M-band Wavelet Transform
Institute of Scientific and Technical Information of China (English)
LiaoYa-li; Yangyan; CaoYang
2003-01-01
Wavelet transform has attracted attention because it is a very useful tool for signal analyzing. As a fundamental characteristic of an image, texture traits play an important role in the human vision system for recognition and interpretation of images. The paper presents an approach to implement texture-based image retrieval using M-band wavelet transform. Firstly the traditional 2-band wavelet is extended to M-band wavelet transform. Then the wavelet moments are computed by M-band wavelet coefficients in the wavelet domain. The set of wavelet moments forms the feature vector related to the texture distribution of each wavelet images. The distances between the feature vectors describe the similarities of different images. The experimental result shows that the M-band wavelet moment features of the images are effective for image indexing.The retrieval method has lower computational complexity, yet it is capable of giving better retrieval performance for a given medical image database.
Implementation of Texture Based Image Retrieval Using M-band Wavelet Transform
Institute of Scientific and Technical Information of China (English)
Liao Ya-li; Yang Yan; Cao Yang
2003-01-01
Wavelet transform has attracted attention because it is a very useful tool for signal analyzing. As a fundamental characteristic of an image, texture traits play an important role in the human vision system for recognition and interpretation of images. The paper presents an approach to implement texture-based image retrieval using M-band wavelet transform. Firstly the traditional 2-band wavelet is extended to M-band wavelet transform. Then the wavelet moments are computed by M-band wavelet coefficients in the wavelet domain. The set of wavelet moments forms the feature vector related to the texture distribution of each wavelet images. The distances between the feature vectors describe the similarities of different images. The experimental result shows that the M-band wavelet moment features of the images are effective for image indexing. The retrieval method has lower computational complexity, yet it is capable of giving better retrieval performance for a given medical image database.
A Quaternionic Wavelet Transform-based Approach for Object Recognition
Directory of Open Access Journals (Sweden)
R. Ahila Priyadharshini
2014-07-01
Full Text Available Recognizing the objects in complex natural scenes is the challenging task as the object may be occluded, may vary in shape, position and in size. In this paper a method to recognize objects from different categories of images using quaternionic wavelet transform (QWT is presented. This transform separates the information contained in the image better than a traditional Discrete wavelet transform and provides a multiscale image analysis whose coefficients are 2D analytic, with one near-shift invariant magnitude and three phases. The two phases encode local image shifts and the third one contains texture information. In the domain of object recognition, it is often to classify objects from images that make only limited part of the image. Hence to identify local features and certain region of images, patches are extracted over the interest points detected from the original image using Wavelet based interest point detector. Here QWT magnitude and phase features are computed for every patch. Then these features are trained, tested and classified using SVM classifier in order to have supervised learning model. In order to compare the performance of local feature with global feature, the transform is applied to the entire image and the global features are derived. The performance of QWT is compared with discrete wavelet transform (DWT and dual tree discrete wavelet transform (DTDWT. Observations revealed that QWT outperforms the DWT and shift invariant DTDWT with lesser equal error rate. The experimental evaluation is done using the complex Graz databases.Defence Science Journal, Vol. 64, No. 4, July 2014, pp. 350-357, DOI:http://dx.doi.org/10.14429/dsj.64.4503
Detection of K-complexes based on the wavelet transform
DEFF Research Database (Denmark)
Krohne, Lærke K.; Hansen, Rie B.; Christensen, Julie Anja Engelhard;
2014-01-01
Sleep scoring needs computational assistance to reduce execution time and to assure high quality. In this pilot study a semi-automatic K-Complex detection algorithm was developed using wavelet transformation to identify pseudo-K-Complexes and various feature thresholds to reject false positives...
Wavelet Transform Modulus Maxima-Based Robust Digital Image Watermarking in Wavelet Domain
Institute of Scientific and Technical Information of China (English)
LUO Ting; HONG Fan
2009-01-01
A new robust watermarking approach was proposed in 2D continuous wavelet domain (CWT).The watermark is embedded into the large coefficients in the middle band of wavelet transform modulus maxima (WTMM) of the host image.After possible attacks,the watermark is then detected and extracted by correlation analysis.Compared with other wavelet domain watermarking approaches,the WTMM approach can endow the image with both rotation and shift invariant properties.On the other hand,scale invariance is achieved with the geometric normalization during watermark detection.Case studies involve various attacks such as shifting,lossy compression,scaling,rotation and median filtering on the watermarked image,and the result shows that the approach is robust to these attacks.
Abstract harmonic analysis of continuous wavelet transforms
Führ, Hartmut
2005-01-01
This volume contains a systematic discussion of wavelet-type inversion formulae based on group representations, and their close connection to the Plancherel formula for locally compact groups. The connection is demonstrated by the discussion of a toy example, and then employed for two purposes: Mathematically, it serves as a powerful tool, yielding existence results and criteria for inversion formulae which generalize many of the known results. Moreover, the connection provides the starting point for a – reasonably self-contained – exposition of Plancherel theory. Therefore, the book can also be read as a problem-driven introduction to the Plancherel formula.
Application of Wavelets Transform to Analysis of Multiphase Flow%小波分析技术在多相流系统中的应用
Institute of Scientific and Technical Information of China (English)
冀海峰; 黄志尧; 吴贤国; 王保良; 李海青
2001-01-01
A method of analysis of multiphase flow using wavelets transform for identifying the flow regimes was proposed．After the wavelet decomposition of the multiphase flow signal，the eigenvalue of different scales were calculated and were used to analyze the multiphase flow system．Methods for obtaining eigenvalue of gas-liquid two phase flow or gas-solid fluidized bed were developed．The results showed that the method was effective for identification of the regime of gas-liquid two phase flow and the transformation of gas-solid fluidized bed from fixed bed to fluidized bed．%提出了一种将小波分析技术应用于多相流系统进行流型判别的方法。对采集的多相流信号进行小波分解，在不同尺度上提取特征值，并提出了两种特征值参数的提取方法，分别应用于气液两相流和气固流化床系统中，进行流型的辨识。试验结果表明利用所提出的特征值可以有效地对气液两相流流型以及气固流化床从固定床向鼓泡床的转变进行判别。
A Fractional Random Wavelet Transform Based Image Steganography
Directory of Open Access Journals (Sweden)
G.K. Rajini
2015-04-01
Full Text Available This study presents a novel technique for image steganography based on Fractional Random Wavelet Transform. This transform has all the features of wavelet transform with randomness and fractional order built into it. The randomness and fractional order in the algorithm brings in robustness and additional layers of security to steganography. The stegano image generated by this algorithm contains both cover image and hidden image and image degradation is not observed in it. The steganography strives for security and pay load capacity. The performance measures like PeakSignal to Noise Ratio (PSNR, Mean Square Error (MSE, Structural Similarity Index Measure (SSIM and Universal Image Quality Index (UIQI are computed. In this proposed algorithm, imperceptibility and robustness are verified and it can sustain geometric transformations like rotation, scaling and translation and is compared with some of the existing algorithms. The numerical results show the effectiveness of the proposed algorithm.
Video Coding with Motion-Compensated Lifted Wavelet Transforms
Flierl, M.; Girod, B.
2004-01-01
This article explores the efficiency of motion-compensated three-dimensional transform coding, a compression scheme that employs a motion-compensated transform for a group of pictures. We investigate this coding scheme experimentally and theoretically. The practical coding scheme employs in temporal direction a wavelet decomposition with motion-compensated lifting steps. Further, we compare the experimental results to that of a predictive video codec with single-hypothesis motion compensation...
Natural frequencies and damping estimation based on continuous wavelet transform
Institute of Scientific and Technical Information of China (English)
DAI Yu; SUN He-yi; LI Hui-peng; TANG Wen-yan
2008-01-01
The continuous wavelet transform (CWT) based method was improved for estimating the natural fre-quencies and damping ratios of a structural system in this paper. The appropriate scale of CWT was selected by means of the least squares method to identify the systems with closely spaced modes. The important issues relat-ed to estimation accuracy such as mode separation and end effect, were also investigated. These issues were as-sociated with the parameter selection of wavelet function based on the fitting error of least squares. The efficien-cy of the method was confirmed by applying it to a simulated 3dof damped system with two close modes.
Image Watermarking Method Using Integer-to-Integer Wavelet Transforms
Institute of Scientific and Technical Information of China (English)
陈韬; 王京春
2002-01-01
Digital watermarking is an efficient method for copyright protection for text, image, audio, and video data. This paper presents a new image watermarking method based on integer-to-integer wavelet transforms. The watermark is embedded in the significant wavelet coefficients by a simple exclusive OR operation. The method avoids complicated computations and high computer memory requirements that are the main drawbacks of common frequency domain based watermarking algorithms. Simulation results show that the embedded watermark is perceptually invisible and robust to various operations, such as low quality joint picture expert group (JPEG) compression, random and Gaussian noises, and smoothing (mean filtering).
Ganesan, Karthikeyan; Acharya, U Rajendra; Chua, Chua Kuang; Min, Lim Choo; Abraham, Thomas K
2014-12-01
Mammograms are one of the most widely used techniques for preliminary screening of breast cancers. There is great demand for early detection and diagnosis of breast cancer using mammograms. Texture based feature extraction techniques are widely used for mammographic image analysis. In specific, wavelets are a popular choice for texture analysis of these images. Though discrete wavelets have been used extensively for this purpose, spherical wavelets have rarely been used for Computer-Aided Diagnosis (CAD) of breast cancer using mammograms. In this work, a comparison of the performance between the features of Discrete Wavelet Transform (DWT) and Spherical Wavelet Transform (SWT) based on the classification results of normal, benign and malignant stage was studied. Classification was performed using Linear Discriminant Classifier (LDC), Quadratic Discriminant Classifier (QDC), Nearest Mean Classifier (NMC), Support Vector Machines (SVM) and Parzen Classifier (ParzenC). We have obtained a maximum classification accuracy of 81.73% for DWT and 88.80% for SWT features using SVM classifier.
Wavelet and ANN Based Relaying for Power Transformer Protection
Directory of Open Access Journals (Sweden)
S. Sudha
2007-01-01
Full Text Available This paper presents an efficient wavelet and neural network (WNN based algorithm for distinguishing magnetizing inrush currents from internal fault currents in three phase power transformers. The wavelet transform is applied first to decompose the current signals of the power transformer into a series of detailed wavelet components. The values of the detailed coefficients obtained can accurately discriminate between an internal fault and magnetizing inrush currents in power transformers. The detailed coefficients are further used to train an Artificial Neural Network (ANN. The trained ANN clearly distinguishes an internal fault current from magnetizing inrush current. A typical 750 MVA, 27/420KV, ∆/Y power transformer connected between a 27KV source at the sending end and a 420KV transmission line connected to an infinite bus power system at the receiving end were simulated using PSCAD/EMTDC software. The generated data were used by the MATLAB software to test the performance of the proposed technique. The simulation results obtained show that the new algorithm is more reliable and accurate. It provides a high operating sensitivity for internal faults and remains stable for inrush currents of the power transformers.
Phase synchronization based on a Dual-Tree Complex Wavelet Transform
Ferreira, Maria Teodora; Domingues, Margarete Oliveira; Macau, Elbert E. N.
2016-11-01
In this work, we show the applicability of our Discrete Complex Wavelet Approach (DCWA) to verify the phenomenon of phase synchronization transition in two coupled chaotic Lorenz systems. DCWA is based on the phase assignment from complex wavelet coefficients obtained by using a Dual-Tree Complex Wavelet Transform (DT-CWT). We analyzed two coupled chaotic Lorenz systems, aiming to detect the transition from non-phase synchronization to phase synchronization. In addition, we check how good is the method in detecting periods of 2π phase-slips. In all experiments, DCWA is compared with classical phase detection methods such as the ones based on arctangent and Hilbert transform showing a much better performance.
Super-resolution image restoration algorithm based on orthogonal discrete wavelet transform
Institute of Scientific and Technical Information of China (English)
Yangyang Liu(刘扬阳); Weiqi Jin(金伟其); Binghua Su(苏秉华)
2004-01-01
By using orthogonal discrete wavelet transform(ODWT)and generalized cross validation(GCV),and combining with Luck-Richardson algorithm based on Poisson-Markovmodel (MPML),several new superresolution image restoration algorithms are proposed.According to simulation experiments for practical images,all the proposed algor ithms could retain image details better than MPML,and be more suitable to low signal-to-noise ratio(SNR)images.The single operation wavelet MPML(SW-MPML)algorithm and MPML algorithm based on single operation wavelet transform(MPML-SW)avoid the iterative operation of self-adaptive parameter in MPML particularly,and improve operating speed and precision.They are instantaneous to super-resolution image restoration process and have extensive application foreground.
Wavelet transform and real-time learning method for myoelectric signal in motion discrimination
Liu, Haihua; Chen, Xinhao; Chen, Yaguang
2005-01-01
This paper discusses the applicability of the Wavelet transform for analyzing an EMG signal and discriminating motion classes. In many previous works, researchers have dealt with steady EMG and have proposed suitable analyzing methods for the EMG, for example FFT and STFT. Therefore, it is difficult for the previous approaches to discriminate motions from the EMG in the different phases of muscle activity, i.e., pre-activity, in activity, postactivity phases, as well as the period of motion transition from one to another. In this paper, we introduce the Wavelet transform using the Coiflet mother wavelet into our real-time EMG prosthetic hand controller for discriminating motions from steady and unsteady EMG. A preliminary experiment to discriminate three hand motions from four channel EMG in the initial pre-activity and in activity phase is carried out to show the effectiveness of the approach. However, future research efforts are necessary to discriminate more motions much precisely.
Yaseen, Alauldeen S.; Pavlov, Alexey N.; Hramov, Alexander E.
2016-03-01
Speech signal processing is widely used to reduce noise impact in acquired data. During the last decades, wavelet-based filtering techniques are often applied in communication systems due to their advantages in signal denoising as compared with Fourier-based methods. In this study we consider applications of a 1-D double density complex wavelet transform (1D-DDCWT) and compare the results with the standard 1-D discrete wavelet-transform (1DDWT). The performances of the considered techniques are compared using the mean opinion score (MOS) being the primary metric for the quality of the processed signals. A two-dimensional extension of this approach can be used for effective image denoising.
Elastic wavelets and their application to problems of solitary wave propagation
Directory of Open Access Journals (Sweden)
Cattani, Carlo
2008-03-01
Full Text Available The paper can be referred to that direction in the wavelet theory, which was called by Kaiser "the physical wavelets". He developed the analysis of first two kinds of physical wavelets - electromagnetic (optic and acoustic wavelets. Newland developed the technique of application of harmonic wavelets especially for studying the harmonic vibrations. Recently Cattani and Rushchitsky proposed the 4th kind of physical wavelets - elastic wavelets. This proposal was based on three main elements: 1. Kaiser's idea of constructing the physical wavelets on the base of specially chosen (admissible solutions of wave equations. 2. Developed by one of authors theory of solitary waves (with profiles in the form of Chebyshov-Hermite functions propagated in elastic dispersive media. 3. The theory and practice of using the wavelet "Mexican Hat" system, the mother and farther wavelets (and their Fourier transforms of which are analytically represented as the Chebyshov-Hermite functions of different indexes. An application of elastic wavelets to studying the evolution of solitary waves of different shape during their propagation through composite materials is shown on many examples.
Dual tree fractional quaternion wavelet transform for disparity estimation.
Kumar, Sanoj; Kumar, Sanjeev; Sukavanam, Nagarajan; Raman, Balasubramanian
2014-03-01
This paper proposes a novel phase based approach for computing disparity as the optical flow from the given pair of consecutive images. A new dual tree fractional quaternion wavelet transform (FrQWT) is proposed by defining the 2D Fourier spectrum upto a single quadrant. In the proposed FrQWT, each quaternion wavelet consists of a real part (a real DWT wavelet) and three imaginary parts that are organized according to the quaternion algebra. First two FrQWT phases encode the shifts of image features in the absolute horizontal and vertical coordinate system, while the third phase has the texture information. The FrQWT allowed a multi-scale framework for calculating and adjusting local disparities and executing phase unwrapping from coarse to fine scales with linear computational efficiency.
Long memory analysis by using maximal overlapping discrete wavelet transform
Shafie, Nur Amalina binti; Ismail, Mohd Tahir; Isa, Zaidi
2015-05-01
Long memory process is the asymptotic decay of the autocorrelation or spectral density around zero. The main objective of this paper is to do a long memory analysis by using the Maximal Overlapping Discrete Wavelet Transform (MODWT) based on wavelet variance. In doing so, stock market of Malaysia, China, Singapore, Japan and United States of America are used. The risk of long term and short term investment are also being looked into. MODWT can be analyzed with time domain and frequency domain simultaneously and decomposing wavelet variance to different scales without loss any information. All countries under studied show that they have long memory. Subprime mortgage crisis in 2007 is occurred in the United States of America are possible affect to the major trading countries. Short term investment is more risky than long term investment.
Adaptive Dual-Threshold Edge Detection Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
侯舒娟; 梅文博; 张志明
2003-01-01
In order to solve the problems of local-maximum modulus extraction and threshold selection in the edge detection of finite-resolution digital images, a new wavelet transform based adaptive dual-threshold edge detection algorithm is proposed. The local-maximum modulus is extracted by linear interpolation in wavelet domain. With the analysis on histogram, the image is filtered with an adaptive dual-threshold method, which effectively detects the contours of small structures as well as the boundaries of large objects. A wavelet domain's propagation function is used to further select weak edges. Experimental results have shown the self-adaptivity of the threshold to images having the same kind of histogram, and the efficiency even in noise-tampered images.
Modelling spatial density using continuous wavelet transforms
Indian Academy of Sciences (India)
D Sudheer Reddy; N Gopal Reddy; A K Anilkumar
2013-02-01
Due to increase in the satelite launch activities from many countries around the world the orbital debris issue has become a major concern for the space agencies to plan a collision-free orbit design. The risk of collisions is calculated using the in situ measurements and available models. Spatial density models are useful in understanding the long-term likelihood of a collision in a particular region of space and also helpful in pre-launch orbit planning. In this paper, we present a method of estimating model parameters such as number of peaks and peak locations of spatial density model using continuous wavelets. The proposed methodology was experimented with two line element data and the results are presented.
A Physical Interpretation of The Poisson Wavelet Transform of Potential Fields
Hornby, P.; Horowitz, F. G.; Boschetti, F.
note the implication that a limiting solution to a Tikhonov stabilisation can be obtained directly from a wavelet transform. 1 The application of this technique to magnetic field strengths is most simply accom- plished via the pseudo-gravity transform of the observed field. Many examples will be displayed at the meeting. 1. Hornby, P., F. Boschetti, and F.G. Horowitz, "Analysis of Potential Field Data in the Wavelet Domain", Geophysical Journal International, v. 137, pp. 175-196, 1999. 2
小波变换在地震动模拟中应用研究%Research on application of wavelet transform in ground motion simulation
Institute of Scientific and Technical Information of China (English)
宋志勇
2012-01-01
The study explores the nonstationarity in the simulation of random ground motion,simulates the nonstationarity feature of the ground motion by adopting the wavelet transform and analyzing all sorts of frequency components in the ground motion,and utilizing the relationship between the wavelet coefficients and the power spectral density function,and indicates it is more consistent with the factual ground motion by comparing its with the traditional stable analyzing models,so as to lay the foundation for further research.%对模拟随机地震动的非平稳性进行了探讨,利用小波变换,通过分析地震动中各频率成分,利用小波系数与功率谱密度函数的关系模拟地震动的非平稳特性,和传统的平稳分析模型相比,更符合地震动实际,为进一步研究奠定了基础。
Chowdhury, Suman Kanti; Nimbarte, Ashish D; Jaridi, Majid; Creese, Robert C
2013-10-01
Assessment of neuromuscular fatigue is essential for early detection and prevention of risks associated with work-related musculoskeletal disorders. In recent years, discrete wavelet transform (DWT) of surface electromyography (SEMG) has been used to evaluate muscle fatigue, especially during dynamic contractions when the SEMG signal is non-stationary. However, its application to the assessment of work-related neck and shoulder muscle fatigue is not well established. Therefore, the purpose of this study was to establish DWT analysis as a suitable method to conduct quantitative assessment of neck and shoulder muscle fatigue under dynamic repetitive conditions. Ten human participants performed 40min of fatiguing repetitive arm and neck exertions while SEMG data from the upper trapezius and sternocleidomastoid muscles were recorded. The ten of the most commonly used wavelet functions were used to conduct the DWT analysis. Spectral changes estimated using power of wavelet coefficients in the 12-23Hz frequency band showed the highest sensitivity to fatigue induced by the dynamic repetitive exertions. Although most of the wavelet functions tested in this study reasonably demonstrated the expected power trend with fatigue development and recovery, the overall performance of the "Rbio3.1" wavelet in terms of power estimation and statistical significance was better than the remaining nine wavelets.
Evaluating Interpersonal Synchrony: Wavelet Transform Toward an Unstructured Conversation.
Fujiwara, Ken; Daibo, Ikuo
2016-01-01
This study examined whether interpersonal synchrony could be extracted using spectrum analysis (i.e., wavelet transform) in an unstructured conversation. Sixty-two female undergraduates were randomly paired and they engaged in a 6-min unstructured conversation. Interpersonal synchrony was evaluated by calculating the cross-wavelet coherence of the time-series movement data, extracted using a video-image analysis software. The existence of synchrony was tested using a pseudo-synchrony paradigm. In addition, the frequency at which the synchrony occurred and the distribution of the relative phase was explored. The results showed that the value of cross-wavelet coherence was higher in the experimental participant pairs than in the pseudo pairs. Further, the coherence value was higher in the frequency band under 0.5 Hz. These results support the validity of evaluating interpersonal synchron Behavioral mimicry and interpersonal syyby using wavelet transform even in an unstructured conversation. However, the role of relative phase was not clear; there was no significant difference between each relative-phase region. The theoretical contribution of these findings to the area of interpersonal coordination is discussed.
IMPROVEMENT OF ANOMALY DETECTION ALGORITHMS IN HYPERSPECTRAL IMAGES USING DISCRETE WAVELET TRANSFORM
Directory of Open Access Journals (Sweden)
Kamal Jamshidi
2012-01-01
Full Text Available Recently anomaly detection (AD has become an important application for target detection in hyperspectralremotely sensed images. In many applications, in addition to high accuracy of detection we need a fast andreliable algorithm as well. This paper presents a novel method to improve the performance of current ADalgorithms. The proposed method first calculates Discrete Wavelet Transform (DWT of every pixel vectorof image using Daubechies4 wavelet. Then, AD algorithm performs on four bands of “Wavelet transform”matrix which are the approximation of main image. In this research some benchmark AD algorithmsincluding Local RX, DWRX and DWEST have been implemented on Airborne Visible/Infrared ImagingSpectrometer (AVIRIS hyperspectral datasets. Experimental results demonstrate significant improvementof runtime in proposed method. In addition, this method improves the accuracy of AD algorithms becauseof DWT’s power in extracting approximation coefficients of signal, which contain the main behaviour ofsignal, and abandon the redundant information in hyperspectral image data.
Edge detection based on object tree image representation and wavelet transform
Institute of Scientific and Technical Information of China (English)
屈彦呈; 王常虹; 庄显义
2003-01-01
In applications such as image retrieval and recognition, precise edge detection for interested regions plays a decisive role. Existing methods generally take little care about local characteristics, or become time-consuming if every detail is considered. In the paper, a new method is put forward based on the combination of effective image representation and multiscale wavelet analysis. A new object tree image representation is introduced. Then a series of object trees are constructed based on wavelet transform modulus maxima at different scales in descending order. Computation is only needed for interested regions. Implementation steps are also given with an illustrative example.
Calvi, M; Bottura, L; Masi, A; Siemko, A
2006-01-01
Premature training quenches are caused by transient energy released within the magnet coil while it is energized. Signals recorded across the so-called quench antenna carry information about these disturbances. A new method for identifying and characterizing those events is proposed, which applies the wavelet transform approach to the recorded signals. Such an approach takes into account the time of occurrence as well as frequency content of the events. The choice of the optimal mother wavelet is discussed, and the results obtained from the application of the method to actual signals are given. The criteria to recognize the interesting events are presented as well as the methodology to classify their global behavior.
Institute of Scientific and Technical Information of China (English)
Liu Xiqiang; Shen Ping; Li Hong; Shan Changlun; Ji Aidong; Zhang Ping; Cai Mingjun
2004-01-01
Based on the Gauss linear frequency-modulated wavelet transform, a new characteristic index is presented, namely time-frequency energy attenuation factor which can reflect the difference features of waveform in earthquake focus mechanism, wave traveling path and its attenuation characteristics in focal area or near field. In order to test its validity, we select the natural earthquakes and explosion or collapse events whose focus mechanisms vary obviously, and some natural earthquakes located at the same site or in a very small area. The study indicates that the time-frequency energy attenuation factors of the natural earthquakes are obviously different with that of explosion or collapse events, and the change of the time-frequency energy attenuation factors is relatively stable for the earthquakes under the normal seismicity background. Using the above-mentioned method, it is expected to offer a useful criterion for strong earthquake prediction by continuous earthquake observation.
Tree wavelet approximations with applications
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
[1]Baraniuk, R. G., DeVore, R. A., Kyriazis, G., Yu, X. M., Near best tree approximation, Adv. Comput. Math.,2002, 16: 357-373.[2]Cohen, A., Dahmen, W., Daubechies, I., DeVore, R., Tree approximation and optimal encoding, Appl. Comput.Harmonic Anal., 2001, 11: 192-226.[3]Dahmen, W., Schneider, R., Xu, Y., Nonlinear functionals of wavelet expansions-adaptive reconstruction and fast evaluation, Numer. Math., 2000, 86: 49-101.[4]DeVore, R. A., Nonlinear approximation, Acta Numer., 1998, 7: 51-150.[5]Davis, G., Mallat, S., Avellaneda, M., Adaptive greedy approximations, Const. Approx., 1997, 13: 57-98.[6]DeVore, R. A., Temlyakov, V. N., Some remarks on greedy algorithms, Adv. Comput. Math., 1996, 5: 173-187.[7]Kashin, B. S., Temlyakov, V. N., Best m-term approximations and the entropy of sets in the space L1, Mat.Zametki (in Russian), 1994, 56: 57-86.[8]Temlyakov, V. N., The best m-term approximation and greedy algorithms, Adv. Comput. Math., 1998, 8:249-265.[9]Temlyakov, V. N., Greedy algorithm and m-term trigonometric approximation, Constr. Approx., 1998, 14:569-587.[10]Hutchinson, J. E., Fractals and self similarity, Indiana. Univ. Math. J., 1981, 30: 713-747.[11]Binev, P., Dahmen, W., DeVore, R. A., Petruchev, P., Approximation classes for adaptive methods, Serdica Math.J., 2002, 28: 1001-1026.[12]Gilbarg, D., Trudinger, N. S., Elliptic Partial Differential Equations of Second Order, Berlin: Springer-Verlag,1983.[13]Ciarlet, P. G., The Finite Element Method for Elliptic Problems, New York: North Holland, 1978.[14]Birman, M. S., Solomiak, M. Z., Piecewise polynomial approximation of functions of the class Wαp, Math. Sb.,1967, 73: 295-317.[15]DeVore, R. A., Lorentz, G. G., Constructive Approximation, New York: Springer-Verlag, 1993.[16]DeVore, R. A., Popov, V., Interpolation of Besov spaces, Trans. Amer. Math. Soc., 1988, 305: 397-414.[17]Devore, R., Jawerth, B., Popov, V., Compression of wavelet decompositions, Amer. J. Math., 1992, 114: 737-785.[18]Storozhenko, E
On the Shiftability of Dual-Tree Complex Wavelet Transforms
Chaudhury, Kunal Narayan
2009-01-01
The dual-tree complex wavelet transform (DT-CWT) is known to exhibit better shift-invariance than the conventional discrete wavelet transform. We propose an amplitude-phase representation of the DT-CWT which, among other things, offers a direct explanation for the improvement in the shift-invariance. The representation is based on the shifting action of the group of fractional Hilbert transform (fHT) operators, which extends the notion of arbitrary phase-shifts from sinusoids to finite-energy signals (wavelets in particular). In particular, we characterize the shiftability of the DT-CWT in terms of the shifting property of the fHTs. At the heart of the representation are certain fundamental invariances of the fHT group, namely that of translation, dilation, and norm, which play a decisive role in establishing the key properties of the transform. It turns out that these fundamental invariances are exclusive to this group. Next, by introducing a generalization of the Bedrosian theorem for the fHT operator, we d...
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A new method of resolving overlapped peak, Fourier self-deconvolution (FSD) using approximation CN obtained from frequency domain wavelet transform of F(ω) yielded by Fourier transform of overlapped peak signals f(t) as the linear function, was presented in this paper.Compared with classical FSD, the new method exhibits excellent resolution for different overlapped peak signals such as HPLC signals, and have some characteristics such as an extensive applicability for any overlapped peak shape signals and a simple operation because of no selection procedure of the linear function. Its excellent resolution for those different overlapped peak signals is mainly because F(ω) obtained from Fourier transform of f(t) and CN obtained from wavelet transform of F(ω) have the similar linearity and peak width. The effect of those fake peaks can be eliminated by the algorithm proposed by authors. This method has good potential in the process of different overlapped peak signals.
A simple structure wavelet transform circuit employing function link neural networks and SI filters
Mu, Li; Yigang, He
2016-12-01
Signal processing by means of analog circuits offers advantages from a power consumption viewpoint. Implementing wavelet transform (WT) using analog circuits is of great interest when low-power consumption becomes an important issue. In this article, a novel simple structure WT circuit in analog domain is presented by employing functional link neural network (FLNN) and switched-current (SI) filters. First, the wavelet base is approximated using FLNN algorithms for giving a filter transfer function that is suitable for simple structure WT circuit implementation. Next, the WT circuit is constructed with the wavelet filter bank, whose impulse response is the approximated wavelet and its dilations. The filter design that follows is based on a follow-the-leader feedback (FLF) structure with multiple output bilinear SI integrators and current mirrors as the main building blocks. SI filter is well suited for this application since the dilation constant across different scales of the transform can be precisely implemented and controlled by the clock frequency of the circuit with the same system architecture. Finally, to illustrate the design procedure, a seventh-order FLNN-approximated Gaussian wavelet is implemented as an example. Simulations have successfully verified that the designed simple structure WT circuit has low sensitivity, low-power consumption and litter effect to the imperfections.
Li, Fang; Wang, Ji-hua; Lu, An-xiang; Han, Ping
2015-04-01
The concentration of Cr, Cu, Zn, As and Pb in soil was tested by portable X-ray fluorescence spectrometer. Each sample was tested for 3 times, then after using wavelet threshold noise filtering method for denoising and smoothing the spectra, a standard curve for each heavy metal was established according to the standard values of heavy metals in soil and the corresponding counts which was the average of the 3 processed spectra. The signal to noise ratio (SNR), mean square error (MSE) and information entropy (H) were taken to assess the effects of denoising when using wavelet threshold noise filtering method for determining the best wavelet basis and wavelet decomposition level. Some samples with different concentrations and H3 B03 (blank) were chosen to retest this instrument to verify its stability. The results show that: the best denoising result was obtained with the coif3 wavelet basis at the decomposition level of 3 when using the wavelet transform method. The determination coefficient (R2) range of the instrument is 0.990-0.996, indicating that a high degree of linearity was found between the contents of heavy metals in soil and each X-ray fluorescence spectral characteristic peak intensity with the instrument measurement within the range (0-1,500 mg · kg(-1)). After retesting and calculating, the results indicate that all the detection limits of the instrument are below the soil standards at national level. The accuracy of the model has been effectively improved, and the instrument also shows good precision with the practical application of wavelet transform to the establishment and improvement of X-ray fluorescence spectrometer detection model. Thus the instrument can be applied in on-site rapid screening of heavy metal in contaminated soil.
The transverse Talbot effect: Scaling analyses based on wavelet transforms
Rosu, H C; Ludu, A
2013-01-01
Berry and Klein [J. Mod. Opt. 43, 2139 (1996)] studied the fractal properties of the paraxial diffracted field behind a Ronchi grating. In particular, they studied the transverse Talbot images formed at fractional distances in units of the Talbot distance chosen from the Fibonacci convergents to the complement of the inverse golden mean zeta_G=(3-square root of 5)/2. Here, we analyze these Talbot images with two well-known scaling methods, the wavelet transform modulus maxima (WTMM) and the wavelet transform multifractal detrended fluctuation analysis (WT-MFDFA). We use the widths of the singularity spectra, Delta(alpha)=alpha_H-alpha_min, as a characteristic feature of the Talbot images. The tau scaling exponents of the q moments are linear in q within the two methods, which is a strong argument in favor of the monofractality of the transverse diffractive paraxial field
Directory of Open Access Journals (Sweden)
Yu Zhao
2013-01-01
Full Text Available In the study, we discussed the generalized autoregressive conditional heteroskedasticity model and enhanced it with wavelet transform to evaluate the daily returns for 1/4/2002-30/12/2011 period in Brent oil market. We proposed discrete wavelet transform generalized autoregressive conditional heteroskedasticity model to increase the forecasting performance of the generalized autoregressive conditional heteroskedasticity model. Our new approach can overcome the defect of generalized autoregressive conditional heteroskedasticity family models which can’t describe the detail and partial features of times series and retain the advantages of them at the same time. Comparing with the generalized autoregressive conditional heteroskedasticity model, the new approach significantly improved forecast results and greatly reduces conditional variances.
Yan, Jingwen; Chen, Jiazhen
2007-03-01
A new hyperspectral image compression method of spectral feature classification vector quantization (SFCVQ) and embedded zero-tree of wavelet (EZW) based on Karhunen-Loeve transformation (KLT) and integer wavelet transformation is represented. In comparison with the other methods, this method not only keeps the characteristics of high compression ratio and easy real-time transmission, but also has the advantage of high computation speed. After lifting based integer wavelet and SFCVQ coding are introduced, a system of nearly lossless compression of hyperspectral images is designed. KLT is used to remove the correlation of spectral redundancy as one-dimensional (1D) linear transform, and SFCVQ coding is applied to enhance compression ratio. The two-dimensional (2D) integer wavelet transformation is adopted for the decorrelation of 2D spatial redundancy. EZW coding method is applied to compress data in wavelet domain. Experimental results show that in comparison with the method of wavelet SFCVQ (WSFCVQ), the method of improved BiBlock zero tree coding (IBBZTC) and the method of feature spectral vector quantization (FSVQ), the peak signal-to-noise ratio (PSNR) of this method can enhance over 9 dB, and the total compression performance is improved greatly.
Institute of Scientific and Technical Information of China (English)
Jingwen Yan; Jiazhen Chen
2007-01-01
A new hyperspectral image compression method of spectral feature classification vector quantization (SFCVQ) and embedded zero-tree of wavelet (EZW) based on Karhunen-Loeve transformation (KLT) and integer wavelet transformation is represented. In comparison with the other methods, this method not only keeps the characteristics of high compression ratio and easy real-time transmission, but also has the advantage of high computation speed. After lifting based integer wavelet and SFCVQ coding are introduced, a system of nearly lossless compression of hyperspectral images is designed. KLT is used to remove the correlation of spectral redundancy as one-dimensional (1D) linear transform, and SFCVQ coding is applied to enhance compression ratio. The two-dimensional (2D) integer wavelet transformation is adopted for the decorrelation of 2D spatial redundancy. EZW coding method is applied to compress data in wavelet domain. Experimental results show that in comparison with the method of wavelet SFCVQ (WSFCVQ),the method of improved BiBlock zero tree coding (IBBZTC) and the method of feature spectral vector quantization (FSVQ), the peak signal-to-noise ratio (PSNR) of this method can enhance over 9 dB, and the total compression performance is improved greatly.
Addison, Paul S
2015-01-01
A novel method of identifying stable phase coupling behavior of two signals within the wavelet transform time-frequency plane is presented. The technique employs the cross-wavelet transform to provide a map of phase coupling followed by synchrosqueezing to collect the stable phase regime information. The resulting synchrosqueezed cross-wavelet transform method (Synchro-CrWT) is illustrated using a synthetic signal and then applied to the analysis of the relationship between biosignals used in the analysis of cerebral autoregulation function.
Remote Sensing Image Fusion Using Ica and Optimized Wavelet Transform
Hnatushenko, V. V.; Vasyliev, V. V.
2016-06-01
In remote-sensing image processing, fusion (pan-sharpening) is a process of merging high-resolution panchromatic and lower resolution multispectral (MS) imagery to create a single high-resolution color image. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. However, the pan-sharpening image produced by these methods gets the high color distortion of spectral information. In this paper, to minimize the spectral distortion we propose a remote sensing image fusion method which combines the Independent Component Analysis (ICA) and optimization wavelet transform. The proposed method is based on selection of multiscale components obtained after the ICA of images on the base of their wavelet decomposition and formation of linear forms detailing coefficients of the wavelet decomposition of images brightness distributions by spectral channels with iteratively adjusted weights. These coefficients are determined as a result of solving an optimization problem for the criterion of maximization of information entropy of the synthesized images formed by means of wavelet reconstruction. Further, reconstruction of the images of spectral channels is done by the reverse wavelet transform and formation of the resulting image by superposition of the obtained images. To verify the validity, the new proposed method is compared with several techniques using WorldView-2 satellite data in subjective and objective aspects. In experiments we demonstrated that our scheme provides good spectral quality and efficiency. Spectral and spatial quality metrics in terms of RASE, RMSE, CC, ERGAS and SSIM are used in our experiments. These synthesized MS images differ by showing a better contrast and clarity on the boundaries of the "object of interest - the background". The results show that the proposed approach performs better than some compared methods according to the performance metrics.
Classification of Transient Phenomena in Distribution System using wavelet Transform
Sedighi, Alireza
2014-05-01
An efficient procedure for classification of transient phenomena in distribution systems is proposed in this paper. The proposed method has been applied to classify some transient phenomena such as inrush current, load switching, capacitor switching and single phase to ground fault. The new scheme is based on wavelet transform algorithm. All of the events for feature extraction and test are simulated using Electro Magnetic Transient Program (EMTP). Results show high accuracy of proposed method.
CONTINUOUS WAVELET TRANSFORM OF TURBULENT BOUNDARY LAYER FLOW
Institute of Scientific and Technical Information of China (English)
LIU Ying-zheng; KE Feng; CHEN Han-ping
2005-01-01
The spatio-temporal characteristics of the velocity fluctuations in a fully-developed turbulent boundary layer flow was investigated using hotwire. A low-speed wind tunnel was established. The experimental data was extensively analyzed in terms of continuous wavelet transform coefficients and their auto-correlation. The results yielded a potential wealth of information on inherent characteristics of coherent structures embedded in turbulent boundary layer flow. Spatial and temporal variations of the low- and high- frequency motions were revealed.
Wavelet Packet Transform Based Driver Distraction Level Classification Using EEG
Directory of Open Access Journals (Sweden)
Mousa Kadhim Wali
2013-01-01
Full Text Available We classify the driver distraction level (neutral, low, medium, and high based on different wavelets and classifiers using wireless electroencephalogram (EEG signals. 50 subjects were used for data collection using 14 electrodes. We considered for this research 4 distraction stimuli such as Global Position Systems (GPS, music player, short message service (SMS, and mental tasks. Deriving the amplitude spectrum of three different frequency bands theta, alpha, and beta of EEG signals was based on fusion of discrete wavelet packet transform (DWPT and FFT. Comparing the results of three different classifiers (subtractive fuzzy clustering probabilistic neural network, -nearest neighbor was based on spectral centroid, and power spectral features extracted by different wavelets (db4, db8, sym8, and coif5. The results of this study indicate that the best average accuracy achieved by subtractive fuzzy inference system classifier is 79.21% based on power spectral density feature extracted by sym8 wavelet which gave a good class discrimination under ANOVA test.
New Wavelet Theory and Application in Nondestructive Testing
Institute of Scientific and Technical Information of China (English)
张秀峰; 施克仁; 郑立男
2004-01-01
A new ultrasound signal processing model that provides fast real-time performance was developed. The model is based on the "rotation angle series fast wavelet transform" algorithm developed for real-time digital signal processing. Instead of the traditional convolution-based algorithms, the algorithm uses a cascaded structure which can be quickly implemented on digital signal processors. The algorithm runs twice as fast as and is more flexible than the fast wavelet transform, and is applicable for multi-channel and phased array ultrasound systems. By using this algorithm, multi-channel ultrasound systems, including phased array ultrasound systems can have less complex software and hardware designs, lower cost, smaller size, and especially more powerful functions.
Filtering of the Radon transform to enhance linear signal features via wavelet pyramid decomposition
Meckley, John R.
1995-09-01
The information content in many signal processing applications can be reduced to a set of linear features in a 2D signal transform. Examples include the narrowband lines in a spectrogram, ship wakes in a synthetic aperture radar image, and blood vessels in a medical computer-aided tomography scan. The line integrals that generate the values of the projections of the Radon transform can be characterized as a bank of matched filters for linear features. This localization of energy in the Radon transform for linear features can be exploited to enhance these features and to reduce noise by filtering the Radon transform with a filter explicitly designed to pass only linear features, and then reconstructing a new 2D signal by inverting the new filtered Radon transform (i.e., via filtered backprojection). Previously used methods for filtering the Radon transform include Fourier based filtering (a 2D elliptical Gaussian linear filter) and a nonlinear filter ((Radon xfrm)**y with y >= 2.0). Both of these techniques suffer from the mismatch of the filter response to the true functional form of the Radon transform of a line. The Radon transform of a line is not a point but is a function of the Radon variables (rho, theta) and the total line energy. This mismatch leads to artifacts in the reconstructed image and a reduction in achievable processing gain. The Radon transform for a line is computed as a function of angle and offset (rho, theta) and the line length. The 2D wavelet coefficients are then compared for the Haar wavelets and the Daubechies wavelets. These filter responses are used as frequency filters for the Radon transform. The filtering is performed on the wavelet pyramid decomposition of the Radon transform by detecting the most likely positions of lines in the transform and then by convolving the local area with the appropriate response and zeroing the pyramid coefficients outside of the response area. The response area is defined to contain 95% of the total
Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform
Wu, Zhi-guo; Wang, Ming-jia; Han, Guang-liang
2011-08-01
Being an efficient method of information fusion, image fusion has been used in many fields such as machine vision, medical diagnosis, military applications and remote sensing. In this paper, Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing, including segmentation, target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First, the two original images are decomposed by wavelet transform. Then, based on the PCNN, a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength, so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So, the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment, the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range, which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore, by this algorithm, the threshold adjusting constant is estimated by appointed iteration number. Furthermore, In order to sufficient reflect order of the firing time, the threshold adjusting constant αΘ is estimated by appointed iteration number. So after the iteration achieved, each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules, the experiments upon Multi-focus image are done. Moreover
Continuous wavelet transform for non-stationary vibration detection with phase-OTDR.
Qin, Zengguang; Chen, Liang; Bao, Xiaoyi
2012-08-27
We propose the continuous wavelet transform for non-stationary vibration measurement by distributed vibration sensor based on phase optical time-domain reflectometry (OTDR). The continuous wavelet transform approach can give simultaneously the frequency and time information of the vibration event. Frequency evolution is obtained by the wavelet ridge detection method from the scalogram of the continuous wavelet transform. In addition, a novel signal processing algorithm based on the global wavelet spectrum is used to determine the location of vibration. Distributed vibration measurements of 500 Hz and 500 Hz to 1 kHz sweep events over 20 cm fiber length are demonstrated using a single mode fiber.
Wavelet Transform and Its Application in Stock Market Data Analysis%子波变换及其在股市数据分析中的应用
Institute of Scientific and Technical Information of China (English)
向小东; 王青; 郭耀煌
2001-01-01
把股票日收益率看作一维时间信号，通过子波变换与多尺度分析，求出了体现股市数据奇异性的Lipschitz指数α。α为负表明在奇异点比不连续更加奇异，证明了股票价格的变化是分形的。同时，由文中图示可知，在尺度s很大时，子波变换和多尺度分析可以将股市数据中偶然因素造成的涨跌消除，具有突出主要因素和宏观突变点的特点，这一点对于从宏观上预测股价的走势有重要意义。%A lipschitz exponent α, which refle cts the singlarity nature ofstock data, is obtained with wavelet trans form and muti-scale analysis by regarding stock day profit ratio as a one -dimentional time signal. Α in this paper is negative, showing that the singul arity is more singular than non-continuum. This proves that the variation of st ock prices is fractal. At the sametime, it is pointed out that when scales is very big, wavelet transform and multi-scale analysis can remove the up-an d-down of stock market data caused by accidental factors and give prominence to primary factors and macroscopic sudden change points. This is important in predicting the variat ion trend of stock prices from macroscopic aspect.
Matsuyama, Eri; Tsai, Du-Yih; Lee, Yongbum; Takahashi, Noriyuki
2013-01-01
The purpose of this study was to evaluate the performance of a conventional discrete wavelet transform (DWT) method and a modified undecimated discrete wavelet transform (M-UDWT) method applied to mammographic image denoising. Mutual information, mean square error, and signal to noise ratio were used as image quality measures of images processed by the two methods. We examined the performance of the two methods with visual perceptual evaluation. A two-tailed F test was used to measure statistical significance. The difference between the M-UDWT processed images and the conventional DWT-method processed images was statistically significant (P<0.01). The authors confirmed the superiority and effectiveness of the M-UDWT method. The results of this study suggest the M-UDWT method may provide better image quality as compared to the conventional DWT.
An Application of Continuous Wavelet Transform in Function Spaces%连续小波变换在函数空间中的应用
Institute of Scientific and Technical Information of China (English)
屈汉章; 宋国乡
2003-01-01
某些微分方程和相应的积分方程之间的关系被讨论;这些微分方程通过连续小波变换可被转换成相应的积分方程;它们不仅在弱收敛意义下而且在范数收敛意义下是等价的;关于这些微分方程的讨论就与相应的积分方程的讨论联系起来.%The relation between some differential equations and the integral equations is discussed. The differential equations can be transformed into the integral equations by using the continuous wavelet transform. The differential equations and the integral equations are equivalent not only in the weak topology but also in the strong topology. The discussion on the differential equations can be connected with the discussion on the integral equations.
Singularity detection of the thin bed seismic signals with wavelet transform
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The location of singularities may be detected by local maxima of the wavelet transform modulus. The digital modeling and focusing process to wavelet transform of the reflecting seismic signals have been done. It has been found that the locations of singularities after wavelet transform are only affected by two factors, their original locations and the seismic wavelet length, which says it does not matter with what shape the wavelet will be. The wavelet length can be determined according to the wavelet transform results and be eliminated thereafter so that we are able to detect thin bed seismic signal with resolution of 1/32 wavelength. The singularities have been recovered with improved resolution of the seismic section by real data processing.
Discrete Meyer Wavelet Transform Features For online Hangul Script Recognition
Directory of Open Access Journals (Sweden)
Jing Lu
2012-09-01
Full Text Available Online hangul script recognition is important when writers input characters into computer and communication apparatus (such as PDA, Mobile Phone. In this study, a Wavelet Transform Features-based method for performance improvement of online handwritten hangul character recognition is proposed. The main idea is applying the Discrete Wavelet Transform (DWT spectral analysis to the recognition of online hangul script. This method is based on the fact that online scripts offer space and time information. Locations of sample points belonging to a script give only space information and the order of occurrences of sample points provides time information. Given an online handwritten character sample, after a series of preprocessing, we obtain a 64×64 normalized online hangul handwritten script with the time information. The order of sample points can be the index of sequences. One sequence is the vertical coordinate of sample points. The second sequence is the horizontal coordinate of sample points. The third sequence is the product of the vertical coordinate and horizontal coordinate of sample points. The fourth sequence is the ratio between the vertical coordinate difference and horizontal coordinate difference of two sample points. The four sequences are combined as a vector whose size is 512. The vector is convoluted with the Meyer Wavelet and its dimension is reduced from 512 to 128 by Linear Discriminant Analysis (LDA scheme. Modified Quadratic Discriminant Functions (MQDF is utilized as the classifier for charter recognition. The Experiment results demonstrate that the method can improve the accuracy of character recognition.
Abibullaev, Berdakh; An, Jinung
2012-12-01
Recent advances in neuroimaging demonstrate the potential of functional near-infrared spectroscopy (fNIRS) for use in brain-computer interfaces (BCIs). fNIRS uses light in the near-infrared range to measure brain surface haemoglobin concentrations and thus determine human neural activity. Our primary goal in this study is to analyse brain haemodynamic responses for application in a BCI. Specifically, we develop an efficient signal processing algorithm to extract important mental-task-relevant neural features and obtain the best possible classification performance. We recorded brain haemodynamic responses due to frontal cortex brain activity from nine subjects using a 19-channel fNIRS system. Our algorithm is based on continuous wavelet transforms (CWTs) for multi-scale decomposition and a soft thresholding algorithm for de-noising. We adopted three machine learning algorithms and compared their performance. Good performance can be achieved by using the de-noised wavelet coefficients as input features for the classifier. Moreover, the classifier performance varied depending on the type of mother wavelet used for wavelet decomposition. Our quantitative results showed that CWTs can be used efficiently to extract important brain haemodynamic features at multiple frequencies if an appropriate mother wavelet function is chosen. The best classification results were obtained by a specific combination of input feature type and classifier.
Three-Dimensional Image Compression With Integer Wavelet Transforms
Bilgin, Ali; Zweig, George; Marcellin, Michael W.
2000-04-01
A three-dimensional (3-D) image-compression algorithm based on integer wavelet transforms and zerotree coding is presented. The embedded coding of zerotrees of wavelet coefficients (EZW) algorithm is extended to three dimensions, and context-based adaptive arithmetic coding is used to improve its performance. The resultant algorithm, 3-D CB-EZW, efficiently encodes 3-D image data by the exploitation of the dependencies in all dimensions, while enabling lossy and lossless decompression from the same bit stream. Compared with the best available two-dimensional lossless compression techniques, the 3-D CB-EZW algorithm produced averages of 22%, 25%, and 20% decreases in compressed file sizes for computed tomography, magnetic resonance, and Airborne Visible Infrared Imaging Spectrometer images, respectively. The progressive performance of the algorithm is also compared with other lossy progressive-coding algorithms.
A Steganographic Method Based on Integer Wavelet Transform & Genatic Algorithm
Directory of Open Access Journals (Sweden)
Preeti Arora
2014-05-01
Full Text Available The proposed system presents a novel approach of building a secure data hiding technique of steganography using inverse wavelet transform along with Genetic algorithm. The prominent focus of the proposed work is to develop RS-analysis proof design with higest imperceptibility. Optimal Pixal Adjustment process is also adopted to minimize the difference error between the input cover image and the embedded-image and in order to maximize the hiding capacity with low distortions respectively. The analysis is done for mapping function, PSNR, image histogram, and parameter of RS analysis. The simulation results highlights that the proposed security measure basically gives better and optimal results in comparison to prior research work conducted using wavelets and genetic algorithm.
Remote Sensing Image Resolution Enlargement Algorithm Based on Wavelet Transformation
Directory of Open Access Journals (Sweden)
Samiul Azam
2014-05-01
Full Text Available In this paper, we present a new image resolution enhancement algorithm based on cycle spinning and stationary wavelet subband padding. The proposed technique or algorithm uses stationary wavelet transformation (SWT to decompose the low resolution (LR image into frequency subbands. All these frequency subbands are interpolated using either bicubic or lanczos interpolation, and these interpolated subbands are put into inverse SWT process for generating intermediate high resolution (HR image. Finally, cycle spinning (CS is applied on this intermediate high resolution image for reducing blocking artifacts, followed by, traditional Laplacian sharpening filter is used to make the generated high resolution image sharper. This new technique has been tested on several satellite images. Experimental result shows that the proposed technique outperforms the conventional and the state-of-the-art techniques in terms of peak signal to noise ratio, root mean square error, entropy, as well as, visual perspective.
A New Shape-Coding Algorithm by Using Wavelet Transform
Institute of Scientific and Technical Information of China (English)
石旭利; 张兆杨
2003-01-01
In this paper, we propose a new shape-coding algorithm called wavelet-based shape coding (WBSC). Performing wavelet transform on the orientation of original planar curve gives the corners called corner-1 points and end of arcs that belong to the original curve. Each arc is represented by a broken line and the corners called corner-2 points of the broken line are extracted. A polygonal approximation of a contour is an ordered list of corner-1 points, ends of arcs and corner-2 points which are extracted by using the above algorithm. All of the points are called polygonal vertices which will be compressed by our adaptive arithmetic encoding. Experimental results show that our method reduces code bits by about 26% compared with the context-based arithmetic encoding (CAE) of MPEG-4, and the subjective quality of the reconstructed shape is better than that of CAE at the same Dn.
Grating geophone signal processing based on wavelet transform
Li, Shuqing; Zhang, Huan; Tao, Zhifei
2008-12-01
Grating digital geophone is designed based on grating measurement technique benefiting averaging-error effect and wide dynamic range to improve weak signal detected precision. This paper introduced the principle of grating digital geophone and its post signal processing system. The signal acquisition circuit use Atmega 32 chip as core part and display the waveform on the Labwindows through the RS232 data link. Wavelet transform is adopted this paper to filter the grating digital geophone' output signal since the signal is unstable. This data processing method is compared with the FIR filter that widespread use in current domestic. The result indicates that the wavelet algorithm has more advantages and the SNR of seismic signal improve obviously.
Wavelet packet transform-based robust video watermarking technique
Indian Academy of Sciences (India)
Gaurav Bhatnagar; Balasubrmanian Raman
2012-06-01
In this paper, a wavelet packet transform (WPT)-based robust video watermarking algorithm is proposed. A visible meaningful binary image is used as the watermark. First, sequent frames are extracted from the video clip. Then, WPT is applied on each frame and from each orientation one sub-band is selected based on block mean intensity value called robust sub-band. Watermark is embedded in the robust sub-bands based on the relationship between wavelet packet coefﬁcient and its 8-neighbour $(D_8)$ coefﬁcients considering the robustness and invisibility. Experimental results and comparison with existing algorithms show the robustness and the better performance of the proposed algorithm.
SVD-based digital image watermarking using complex wavelet transform
Indian Academy of Sciences (India)
A Mansouri; A Mahmoudi Aznaveh; F Torkamani Azar
2009-06-01
A new robust method of non-blind image watermarking is proposed in this paper. The suggested method is performed by modiﬁcation on singular value decomposition (SVD) of images in Complex Wavelet Transform (CWT) domain while CWT provides higher capacity than the real wavelet domain. Modiﬁcation of the appropriate sub-bands leads to a watermarking scheme which favourably preserves the quality. The additional advantage of the proposed technique is its robustness against the most of common attacks. Analysis and experimental results show much improved performance of the proposed method in comparison with the pure SVD-based as well as hybrid methods (e.g. DWT-SVD as the recent best SVD-based scheme).
Frequency domain volume rendering by the wavelet X-ray transform
Westenberg, Michel A.; Roerdink, Jos B.T.M.
2000-01-01
We describe a wavelet-based X-ray rendering method in the frequency domain with a smaller time complexity than wavelet splatting. Standard Fourier volume rendering is summarized and interpolation and accuracy issues are briefly discussed. We review the implementation of the fast wavelet transform in
Hu, Li-yun
2009-01-01
In a preceding Letter (Opt. Lett. 32, 554 (2007)) we have proposed complex continuous wavelet transforms (CCWTs) and found Laguerre--Gaussian mother wavelets family. In this work we present the inversion formula and Parsval theorem for CCWT by virtue of the entangled state representation, which makes the CCWT theory complete. A new orthogonal property of mother wavelet in parameter space is revealed.
Institute of Scientific and Technical Information of China (English)
Changjiang Zhang; Xiaodong Wang; Haoran Zhang
2005-01-01
A new contrast enhancement algorithm for image is proposed employing wavelet neural network (WNN)and stationary wavelet transform (SWT). Incomplete Beta transform (IBT) is used to enhance the global contrast for image. In order to avoid the expensive time for traditional contrast enhancement algorithms,which search optimal gray transform parameters in the whole gray transform parameter space, a new criterion is proposed with gray level histogram. Contrast type for original image is determined employing the new criterion. Gray transform parameter space is given respectively according to different contrast types,which shrinks the parameter space greatly. Nonlinear transform parameters are searched by simulated annealing algorithm (SA) so as to obtain optimal gray transform parameters. Thus the searching direction and selection of initial values of simulated annealing is guided by the new parameter space. In order to calculate IBT in the whole image, a kind of WNN is proposed to approximate the IBT. Having enhanced the global contrast to input image, discrete SWT is done to the image which has been processed by previous global enhancement method, local contrast enhancement is implemented by a kind of nonlinear operator in the high frequency sub-band images of each decomposition level respectively. Experimental results show that the new algorithm is able to adaptively enhance the global contrast for the original image while it also extrudes the detail of the targets in the original image well. The computation complexity for the new algorithm is O(MN) log(MN), where M and N are width and height of the original image, respectively.
Efficient local statistical analysis via integral histograms with discrete wavelet transform.
Lee, Teng-Yok; Shen, Han-Wei
2013-12-01
Histograms computed from local regions are commonly used in many visualization applications, and allowing the user to query histograms interactively in regions of arbitrary locations and sizes plays an important role in feature identification and tracking. Computing histograms in regions with arbitrary location and size, nevertheless, can be time consuming for large data sets since it involves expensive I/O and scan of data elements. To achieve both performance- and storage-efficient query of local histograms, we present a new algorithm called WaveletSAT, which utilizes integral histograms, an extension of the summed area tables (SAT), and discrete wavelet transform (DWT). Similar to SAT, an integral histogram is the histogram computed from the area between each grid point and the grid origin, which can be be pre-computed to support fast query. Nevertheless, because one histogram contains multiple bins, it will be very expensive to store one integral histogram at each grid point. To reduce the storage cost for large integral histograms, WaveletSAT treats the integral histograms of all grid points as multiple SATs, each of which can be converted into a sparse representation via DWT, allowing the reconstruction of axis-aligned region histograms of arbitrary sizes from a limited number of wavelet coefficients. Besides, we present an efficient wavelet transform algorithm for SATs that can operate on each grid point separately in logarithmic time complexity, which can be extended to parallel GPU-based implementation. With theoretical and empirical demonstration, we show that WaveletSAT can achieve fast preprocessing and smaller storage overhead than the conventional integral histogram approach with close query performance.
Integral transforms and their applications
Debnath, Lokenath
2014-01-01
Integral Transforms and Their Applications, Third Edition covers advanced mathematical methods for many applications in science and engineering. The book is suitable as a textbook for senior undergraduate and first-year graduate students and as a reference for professionals in mathematics, engineering, and applied sciences. It presents a systematic development of the underlying theory as well as a modern approach to Fourier, Laplace, Hankel, Mellin, Radon, Gabor, wavelet, and Z transforms and their applications. New to the Third Edition New material on the historical development of classical a
A primer on wavelets and their scientific applications
Walker, James S
2008-01-01
In the first edition of his seminal introduction to wavelets, James S. Walker informed us that the potential applications for wavelets were virtually unlimited. Since that time thousands of published papers have proven him true, while also necessitating the creation of a new edition of his bestselling primer. Updated and fully revised to include the latest developments, this second edition of A Primer on Wavelets and Their Scientific Applications guides readers through the main ideas of wavelet analysis in order to develop a thorough appreciation of wavelet applications. Ingeniously relying o
Signal Processing of Radar Echoes Using Wavelets and Hilbert Huang Transform
Directory of Open Access Journals (Sweden)
N.Padmaja
2011-09-01
Full Text Available Atmospheric Radar Signal Processing is one field of Signal Processing where there is a lot of scope for development of new and efficient tools for spectrum cleaning, detection and estimation of desired parameters. The wavelet transform and HHT (Hilbert-Huang transform are both signal processing methods. This paper is based on comparing HHT and Wavelet transform applied to Radar signals. Wavelet analysis is one of the most important methods for removing noise and extracting signal from any data. The de-noising application of the wavelets has been used in spectrum cleaning of the atmospheric radar signals. HHT can be used for processing non-stationary and nonlinear signals. HHT is one of the time-frequency analysis techniques which consists of two parts: Empirical Mode Decomposition (EMD and instantaneous frequency solution. EMD is a numerical sifting process to decompose a signal into its fundamental intrinsic oscillatory modes, namely intrinsic mode functions (IMFs. A series of IMFs can be obtained after the application of EMD. In this paper wavelets and EMD has been applied to the time series data obtained from the mesosphere-stratosphere-troposphere (MST region near Gadanki, Tirupati for 6 beam directions. The Algorithm is developed and tested using Matlab. Moments were estimated and analysis has brought out improvement in some of the characteristic features like SNR, Doppler width, Noise power of the atmospheric signals. The results showed that the proposed algorithm is efficient for dealing non-linear and non- stationary signals contaminated with noise. The results were compared using ADP (Atmospheric Data Processor and plotted for validation of the proposed algorithm.
SIGNAL PROCESSING OF RADAR ECHOES USING WAVELETS AND HILBERT HUANG TRANSFORM
Directory of Open Access Journals (Sweden)
N.Padmaja
2011-10-01
Full Text Available Atmospheric Radar Signal Processing is one field of Signal Processing where there is a lot of scope for development of new and efficient tools for spectrum cleaning, detection and estimation of desired parameters. The wavelet transform and HHT (Hilbert-Huang transform are both signal processing methods. This paper is based on comparing HHT and Wavelet transform applied to Radar signals. Wavelet analysis is one of the most important methods for removing noise and extracting signal from any data. The de-noising application of the wavelets has been used in spectrum cleaning of the atmospheric radar signals. HHT can be used for processing non-stationary and nonlinear signals. HHT is one of the time-frequency analysis techniques which consists of two parts: Empirical Mode Decomposition (EMD and instantaneous frequency solution. EMD is a numerical sifting process to decompose a signal into its fundamental intrinsic oscillatory modes, namely intrinsic mode functions (IMFs. A series of IMFs can be obtained after the application of EMD. In this paper wavelets and EMD has been applied to the time series data obtained from the mesosphere-stratosphere-troposphere (MST region near Gadanki, Tirupati for 6 beam directions. The Algorithm is developed and tested using Matlab. Moments were estimated and analysis has brought out improvement in some of the characteristic features like SNR, Doppler width, Noise power of the atmospheric signals. The results showed that the proposed algorithm is efficient for dealing non-linear and non- stationary signals contaminated with noise. The results were compared using ADP (Atmospheric Data Processor and plotted for validation of the proposed algorithm.
PALMPRINT VERIFICATION USING INVARIANT MOMENTS BASED ON WAVELET TRANSFORM
Directory of Open Access Journals (Sweden)
Inass SH. Hussein
2014-01-01
Full Text Available Data security is one of the important issues among computer users. Data security can prevent fraudulent users from accessing an individual’s personal data. The biometrics recognition as one of the most important parts in the security of the data and the application of computer vision. The biometrics is the authentication method used in a wide variety of applications such as e-banking, e-commerce, e-government and many others. A biometric system is one which requires the recognition of a pattern, whereby it enables the differentiation of features from one individual to another. Biometric technologies, thus may be defined as the automated methods of identifying, or authenticating, the identity of a living person based on physiological or behavioral traits. This study emphasizes palmprint recognition, which provides a wide deployment range of authentication methods. The palmprint contains principal lines, wrinkles, fine lines, ridges and surface area; thus the palmprint of person differs from one to another. Previous researchers have difficulty extracting the features of a palm print, because of the effects of rotation, translation and scaling changes and the accuracy rate of verification performance needs to be improved. The aim of this study is to extract shape features using an invariant moments algorithm based on wavelet transform and identify the person’s verification. This model has shown a promising results without the effects of rotation, translation and scaling of objects, because it is associated with the use of a good description of shape features. This system has been tested using databases from the Indian Institute of Technology, Kanpur (IITK, by using the False Rejection Rate (FRR and False Acceptance Rate (FAR, we may calculate the accuracy rate of verification. The experiment shows a 97.99% accuracy rate of verification.
Wavelet Transform of Super-Resolutions Based on Radar and Infrared Sensor Fusion
1998-05-01
0I Q’UAL1 INwPO¶= I VI STATEMB r AApproved for public release; Distribution Unlimited NAVY CASE 77545 WAVELET TRANSFORM OF SUPER-RESOLUTIONS BASED ON...INVENTION It is, therefore, an object of the present invention to provide a structure and method for applying the forward and reverse Wavelet Transform (WT...invention, the noisy super- 10 resolution of infrared imaging is combined with the Wavelet transform for radar corner back-scattering size information
Redundant Discrete Wavelet Transform Based Super-Resolution Using Sub-Pixel Image Registration
2003-03-01
AFIT/GE/ENG/03-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION THESIS Daniel L. Ward Second...position of the United States Air Force, Department of Defense, or the United States Government. AFIT/GE/ENG/03-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED...O3-18 REDUNDANT DISCRETE WAVELET TRANSFORM BASED SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION THESIS Daniel Lee Ward, B.S.E.E. Second
Model Based Ceramic tile inspection using Discrete Wavelet Transform and Euclidean Distance
Ibrahim El-Henawy; Samir Elmougy; Ahmed El-Azab
2010-01-01
Visual inspection of industrial products is used to determine the control quality for these products. This paper deals with the problem of visual inspection of ceramic tiles industry using Wavelet Transform. The third level the coefficients of two dimensions Haar Discrete Wavelet Transform (HDWT) is used in this paper to process the images and feature extraction. The proposed algorithm consists of two main phases. The first phase is to compute the wavelet transform for an image free of defect...
Very Low Bit-Rate Video Coding Using Motion ompensated 3-D Wavelet Transform
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
A new motion-compensated 3-D wavelet transform (MC-3DWT) video coding scheme is presented in thispaper. The new coding scheme has a good performance in average PSNR, compression ratio and visual quality of re-constructions compared with the existing 3-D wavelet transform (3DWT) coding methods and motion-compensated2-D wavelet transform (MC-WT) coding method. The new MC-3DWT coding scheme is suitable for very low bit-rate video coding.
Wavelet transform in similarity paradigm II
Z.R. Struzik; A.P.J.M. Siebes (Arno)
1998-01-01
htmlabstractFor the majority of data mining applications, there are no models of data which would facilitate the tasks of comparing records of time series, thus leaving one with `noise' as the only description. We propose a generic approach to comparing noise time series using the largest deviations
Application of Wavelet Transform in Image Matching Technology%小波变换在图像匹配技术中的应用研究
Institute of Scientific and Technical Information of China (English)
白骅; 方萌
2014-01-01
针对单一图像匹配算法抗噪声能力和抗几何形变能力差、以及计算量较大等问题，提出一种基于小波变换后图像统计特征的图像匹配识别算法。利用小波对图像进行多个尺度的二维小波变换，分析反映图像在不同尺度和不同方向上能量分布情况，通过计算统计特征量和标准图库中图像统计特征量之间的夹角，确定待识别目标，利用该方法对图书条形码进行识别。研究结果表明：采用小波变时频特性对图像进行去噪处理以及边缘检测，能够剔除图像噪声干扰并充分保留原始图像信息；将小波变换后的近似系数、水平、垂直和对角部分的细节系数作为统计特征量，提取的特征量跟模板图像的统计特征量进行相似度匹配，将两个特征向量的夹角余弦作为相似度的衡量指标，根据夹角余弦的大小确定该区域是否目标区域。%T he anti-noise and resistance to geometric deformation ability of a single image matching algorithm is poor .When the color difference between the image background and target area is very small ,the matching algorithm based on gray can not effectively distinguish between background area and the target area .Above all ,its calculation amount is large and it has lower accuracy .Therefore ,a kind of image matching recognition algorithm based on statistical characteristics of the image after the wavelet transform is proposed .This algorithm adopts wavelet to perform multiple scale two-dimensional wavelet transform for the image .The corresponding progeny image energy distribution in different direction and different scale will be taken as statistical characteristics .The targets to be recognized are identified through the angle's cosine value between the extracted statistical features from the targets and the statistical characteristics of the standard library image .Finally ,the bar codes of books are adopted to verify this method
Barrie, Alexander C.; Yeh, Penshu; Dorelli, John C.; Clark, George B.; Paterson, William R.; Adrian, Mark L.; Holland, Matthew P.; Lobell, James V.; Simpson, David G.; Pollock, Craig J.;
2015-01-01
Plasma measurements in space are becoming increasingly faster, higher resolution, and distributed over multiple instruments. As raw data generation rates can exceed available data transfer bandwidth, data compression is becoming a critical design component. Data compression has been a staple of imaging instruments for years, but only recently have plasma measurement designers become interested in high performance data compression. Missions will often use a simple lossless compression technique yielding compression ratios of approximately 2:1, however future missions may require compression ratios upwards of 10:1. This study aims to explore how a Discrete Wavelet Transform combined with a Bit Plane Encoder (DWT/BPE), implemented via a CCSDS standard, can be used effectively to compress count information common to plasma measurements to high compression ratios while maintaining little or no compression error. The compression ASIC used for the Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale mission (MMS) is used for this study. Plasma count data from multiple sources is examined: resampled data from previous missions, randomly generated data from distribution functions, and simulations of expected regimes. These are run through the compression routines with various parameters to yield the greatest possible compression ratio while maintaining little or no error, the latter indicates that fully lossless compression is obtained. Finally, recommendations are made for future missions as to what can be achieved when compressing plasma count data and how best to do so.
Multiresolution signal decomposition transforms, subbands, and wavelets
Akansu, Ali N
1992-01-01
This book provides an in-depth, integrated, and up-to-date exposition of the topic of signal decomposition techniques. Application areas of these techniques include speech and image processing, machine vision, information engineering, High-Definition Television, and telecommunications. The book will serve as the major reference for those entering the field, instructors teaching some or all of the topics in an advanced graduate course and researchers needing to consult an authoritative source.n The first book to give a unified and coherent exposition of multiresolutional signal decompos
Directory of Open Access Journals (Sweden)
Lixiang Duan
2016-01-01
Full Text Available Effective signal processing in fault detection and diagnosis (FDD is an important measure to prevent failure and accidents of machinery. To address the end distortion and frequency aliasing issues in conventional lifting wavelet transform, a Volterra series assisted undecimated lifting wavelet packet transform (ULWPT is investigated for machinery incipient fault diagnosis. Undecimated lifting wavelet packet transform is firstly formulated to eliminate the frequency aliasing issue in traditional lifting wavelet packet transform. Next, Volterra series, as a boundary treatment method, is used to preprocess the signal to suppress the end distortion in undecimated lifting wavelet packet transform. Finally, the decomposed wavelet coefficients are trimmed to the original length as the signal of interest for machinery incipient fault detection. Experimental study on a reciprocating compressor is performed to demonstrate the effectiveness of the presented method. The results show that the presented method outperforms the conventional approach by dramatically enhancing the weak defect feature extraction for reciprocating compressor valve fault diagnosis.
RAINFALL ANALYSIS IN KLANG RIVER BASIN USING CONTINUOUS WAVELET TRANSFORM
Directory of Open Access Journals (Sweden)
Celso A. G. Santos
2016-01-01
Full Text Available The rainfall characteristics within Klang River basin is analyzed by the continuous wavelet transform using monthly rainfall data (1997–2009 from a raingauge and also using daily rainfall data (1998–2013 from the Tropical Rainfall Measuring Mission (TRMM. The wavelet power spectrum showed that some frequency components were presented within the rainfall time series, but the observed time series is short to provide accurate information, thus the daily TRMM rainfall data were used. In such analysis, two main frequency components, i.e., 6 and 12 months, showed to be present during the entire period of 16 years. Such semiannual and annual frequencies were confirmed by the global wavelet power spectra. Finally, the modulation in the 8–16-month and 256– 512-day bands were examined by an average of all scales between 8 and 16 months, and 256 and 512 days, respectively, giving a measure of the average monthly/daily variance versus time, where the periods with low or high variance could be identified.
Robust GPS Satellite Signal Acquisition Using Lifting Wavelet Transform
Directory of Open Access Journals (Sweden)
M. Djebbouri
2006-04-01
Full Text Available A novel GPS satellite signal acquisition scheme that utilizes lifting wavelet to improve acquisition performance is proposed. Acquisition in GPS system is used to calculate the code phase (or shift and find the pseudo-range, which is used to calculate the position. The performance of a GPS receiver is assessed by its ability to precisely measure the pseudo-range, which depends on noise linked to the signals in the receiverÃ¢Â€Â™s tracking loops. The level of GPS receiving equipment system noise determines in part how precisely pseudo-range can be measured. Our objective, in this paper, is to achieve robust real-time positioning with maximum of accuracy in the presence of noise. Robust positioning describes a positioning system's ability to maintain position data continuity and accuracy through most or all anticipated operational conditions. In order to carry out a robust less complex GPS signals acquisition system and to facilitate its implementation, a substitute algorithm for calculating the convolution by using lifting wavelet decomposition is proposed. Simulation is used for verifying the performance which shows that the proposed scheme based lifting wavelet transform outperforms both FFT search and signal decimation schemes in the presence of a hostile environment.
Evaluation of earthquake-induced structural damages by wavelet transform
Institute of Scientific and Technical Information of China (English)
Hongnan Li; Tinghua Yi; Ming Gu; Linsheng Huo
2009-01-01
The dynamic behavior of inelastic structures during an earthquake is a complicated non-stationary process that is affected by the random characteristics of seismic ground motions.The conventional Fourier analysis describes the feature of a dynamic process by decomposing the signal into infinitely long sine and cosine series,which loses all time-located information.However,both time and frequency localizations are necessary for the analysis of an evolutionary spectrum of non-stationary processes.In this paper,an analytical approach for seismic ground motions is developed by applying the wavelet transform,which focuses on the energy input to the structure.The procedure of identification of the instantaneous modal parameters based on the continuous wavelet transform (CWT) is given in detail.And then,a novel method using the auto-regressive moving average (ARMA),called "prediction extension",is presented to remedy the edge effect during the numerical computation of the CWT.The effectiveness of the method is verified by the use of the benchmark model developed by the American Society of Civil Engineers (ASCE).Finally,a scale modal with three-storey reinforced concrete frame-share wall structure is made and tested on a shaking table to investigate the relation between the dynamic properties of structures and energy accumulation and its change rates during the earthquake.The results have shown that the wavelet transform is able to provide a deep insight into the identity of transient signals through time-frequency maps of the time variant spectral decomposition.
Integer wavelet transform for embedded lossy to lossless image compression.
Reichel, J; Menegaz, G; Nadenau, M J; Kunt, M
2001-01-01
The use of the discrete wavelet transform (DWT) for embedded lossy image compression is now well established. One of the possible implementations of the DWT is the lifting scheme (LS). Because perfect reconstruction is granted by the structure of the LS, nonlinear transforms can be used, allowing efficient lossless compression as well. The integer wavelet transform (IWT) is one of them. This is an interesting alternative to the DWT because its rate-distortion performance is similar and the differences can be predicted. This topic is investigated in a theoretical framework. A model of the degradations caused by the use of the IWT instead of the DWT for lossy compression is presented. The rounding operations are modeled as additive noise. The noise are then propagated through the LS structure to measure their impact on the reconstructed pixels. This methodology is verified using simulations with random noise as input. It predicts accurately the results obtained using images compressed by the well-known EZW algorithm. Experiment are also performed to measure the difference in terms of bit rate and visual quality. This allows to a better understanding of the impact of the IWT when applied to lossy image compression.
Multi-sensor image fusion using discrete wavelet frame transform
Institute of Scientific and Technical Information of China (English)
Zhenhua Li(李振华); Zhongliang Jing(敬忠良); Shaoyuan Sun(孙韶媛)
2004-01-01
An algorithm is presented for multi-sensor image fusion using discrete wavelet frame transform (DWFT).The source images to be fused are firstly decomposed by DWFT. The fusion process is the combining of the source coefficients. Before the image fusion process, image segmentation is performed on each source image in order to obtain the region representation of each source image. For each source image, the salience of each region in its region representation is calculated. By overlapping all these region representations of all the source images, we produce a shared region representation to label all the input images. The fusion process is guided by these region representations. Region match measure of the source images is calculated for each region in the shared region representation. When fusing the similar regions, weighted averaging mode is performed; otherwise selection mode is performed. Experimental results using real data show that the proposed algorithm outperforms the traditional pyramid transform based or discrete wavelet transform (DWT) based algorithms in multi-sensor image fusion.
Blind component separation in wavelet space. Application to CMB analysis
Moudden, Y; Starck, J L; Delabrouille, J
2004-01-01
It is a recurrent issue in astronomical data analysis that observations are unevenly sampled or incomplete maps with missing patches or intentionaly masked parts. In addition, many astrophysical emissions are non stationary processes over the sky. Hence spectral estimation using standard Fourier transforms is no longer reliable. Spectral matching ICA (SMICA) is a source separation method based on covariance matching in Fourier space which is successfully used for the separation of diffuse astrophysical emissions in Cosmic Microwave Background observations. We show here that wavelets, which are standard tools in processing non stationary data, can profitably be used to extend SMICA. Among possible applications, it is shown that gaps in data are dealt with more conveniently and with better results using this extension, wSMICA, in place of the original SMICA. The performances of these two methods are compared on simulated CMB data sets, demonstrating the advantageous use of wavelets.
Efficient Reversible Watermarking Using Differential Expansible Integer Wavelet Transform
Directory of Open Access Journals (Sweden)
Sanjay Patel
2016-07-01
Full Text Available Digital watermarking has been utilized widely to claim the ownership and to protect images from alternation. Reversible watermarking is having great importance as it provided original image and the embedded logo without any loss. This paper proposed reversible watermarking algorithm using integer wavelet transform to satisfy the reversibility requirement. Further difference expansion based lifting scheme is used to make algorithm fast. To show the robustness of algorithm, various attacks like noise, rotating/scaling an image and filtering to the watermarked image is employed. The extraction of original image against such attacks is quantified in terms of peak signal to noise ratio (PSNR
Chaotic Synchronization with Filter Based on Wavelet Transformation
Institute of Scientific and Technical Information of China (English)
XiaoanZHOU; JunfengLAN; 等
1999-01-01
A kind of chaotic synchronization method is presented in the paper,In the transmitter,part signals are transformed by wavelet and the detail information is removed.In the receiver.the component with low frequency is reconstructed and discrete feedback is used,we show that synchronization of two identical structure chaotic systems is attained.The effect of feedback on chaotic synchronization is discussed.Using the synchronous method,the transmitting signal is transported in compressible way system resource is saved,the component with high frequency is filtered and the effect of disturbance on synchronization is reduced.The synchronization method is illustrated by numerical simulation experiment.
Field programmable gate arrays implementation of Dual Tree Complex Wavelet Transform.
Canbay, Ferhat; Levent, Vecdi Emre; Serbes, Gorkem; Goren, Sezer; Aydin, Nizamettin
2015-01-01
Due to the inherent time-varying characteristics of physiological systems, most biomedical signals (BSs) are expected to have non-stationary character. Therefore, any appropriate analysis method for dealing with BSs should exhibit adjustable time-frequency (TF) resolution. The wavelet transform (WT) provides a TF representation of signals, which has good frequency resolution at low frequencies and good time resolution at high frequencies, resulting in an optimized TF resolution. Discrete wavelet transform (DWT), which is used in various medical signal processing applications such as denoising and feature extraction, is a fast and discretized algorithm for classical WT. However, the DWT has some very important drawbacks such as aliasing, lack of directionality, and shift-variance. To overcome these drawbacks, a new improved discrete transform named as Dual Tree Complex Wavelet Transform (DTCWT) can be used. Nowadays, with the improvements in embedded system technology, portable real-time medical devices are frequently used for rapid diagnosis in patients. In this study, in order to implement DTCWT algorithm in FPGAs, which can be used as real-time feature extraction or denoising operator for biomedical signals, a novel hardware architecture is proposed. In proposed architecture, DTCWT is implemented with only one adder and one multiplier. Additionally, considering the multi-channel outputs of biomedical data acquisition systems, this architecture is capable of running N channels in parallel.
SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES
Directory of Open Access Journals (Sweden)
A. Rezaeian
2015-12-01
Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Shannon entropy in time domain is a measure of signal or system uncertainty. When based on spectrum entropy, Shannon entropy can be taken as a measure of signal or system complexity.Therefore, wavelet analysis based on wavelet entropy measure can signify the complexity of non-steady signal or system in both time and frequency domain. In this paper, in order to meet the requirements of post-analysis on abundant wavelet transform result data and the need of information mergence, the basic definition of wavelet entropy measure is proposed, corresponding algorithms of several wavelet entropies, such as wavelet average entropy, wavelet time-frequency entropy, wavelet distance entropy,etc. are put forward, and the physical meanings of these entropies are analyzed as well. The application principle of wavelet entropy measure in ElectroEncephaloGraphy (EEG) signal analysis, mechanical fault diagnosis, fault detection and classification in power system are analyzed. Finally, take the transmission line fault detection in power system for example, simulations in two different systems, a 10kV automatic blocking and continuous power transmission line and a 500kV Extra High Voltage (EHV) transmission line, are carried out, and the two methods, wavelet entropy and wavelet modulus maxima, are compared, the results show feasibility and application prospect of the six wavelet entropies.
Implementation of Time-Scale Transformation Based on Continuous Wavelet Theory
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
The basic objective of time-scale transformation is to compress or expand the signal in time field while keeping the same spectral properties.This paper presents two methods to derive time-scale transformation formula based on continuous wavelet transform.For an arbitrary given square-integrable function f(t),g(t) = f(t/λ) is derived by continuous wavelet transform and its inverse transform.The result shows that time-scale transformation may be obtained through the modification of the time-scale of wavelet function filter using equivalent substitution. The paper demonstrates the result by theoretic derivations and experimental simulation.
Singh, Ram Chandra; Bhatla, Rajeev
2012-07-01
This paper deals with the meteorological applications of wavelets and fuzzy logics and a hybrid of wavelets and fuzzy logics. The wavelet transform has emerged over recent years as a powerful time-frequency analysis and signal coding tool favoured for the interrogation of complex non-stationary signals. It has been shown that the wavelet transform is a flexible time-frequency decomposition tool which can form the basis of useful time series analysis. It is expected to see an increased amount of research and technology development work in the coming years employing wavelets for various scientific and engineering applications.
Frequency domain volume rendering by the wavelet X-ray transform.
Westenberg, M A; Roerdink, J M
2000-01-01
We describe a wavelet based X-ray rendering method in the frequency domain with a smaller time complexity than wavelet splatting. Standard Fourier volume rendering is summarized and interpolation and accuracy issues are briefly discussed. We review the implementation of the fast wavelet transform in the frequency domain. The wavelet X-ray transform is derived, and the corresponding Fourier-wavelet volume rendering algorithm (FWVR) is introduced, FWVR uses Haar or B-spline wavelets and linear or cubic spline interpolation. Various combinations are tested and compared with wavelet splatting (WS). We use medical MR and CT scan data, as well as a 3-D analytical phantom to assess the accuracy, time complexity, and memory cost of both FWVR and WS. The differences between both methods are enumerated.
Lossless image compression with projection-based and adaptive reversible integer wavelet transforms.
Deever, Aaron T; Hemami, Sheila S
2003-01-01
Reversible integer wavelet transforms are increasingly popular in lossless image compression, as evidenced by their use in the recently developed JPEG2000 image coding standard. In this paper, a projection-based technique is presented for decreasing the first-order entropy of transform coefficients and improving the lossless compression performance of reversible integer wavelet transforms. The projection technique is developed and used to predict a wavelet transform coefficient as a linear combination of other wavelet transform coefficients. It yields optimal fixed prediction steps for lifting-based wavelet transforms and unifies many wavelet-based lossless image compression results found in the literature. Additionally, the projection technique is used in an adaptive prediction scheme that varies the final prediction step of the lifting-based transform based on a modeling context. Compared to current fixed and adaptive lifting-based transforms, the projection technique produces improved reversible integer wavelet transforms with superior lossless compression performance. It also provides a generalized framework that explains and unifies many previous results in wavelet-based lossless image compression.
The applications of wavelet transform in motor imagery EEG classification%小波变换在运动想象脑电分类中的应用
Institute of Scientific and Technical Information of China (English)
张俊伟; 刘建平
2013-01-01
Brain-computer interface(BCI)technology is an interactive communication technology which is realized without depending on humans′ peripheral nerves and muscles. The technology provides human a man-machine communication and con-trol channel without the communication between muscular tissue and outside world. On the basis of the pervious research re-sults,the Mallat algorithm of wavelet transform is used in the feature extraction of the experiment data. The time window selec-tion and useful signal choosing with the frequency range is focused on. The classification results for accuracy of 84.285 6%,pre-cision of 85.272 1% and sensitivity of 92.000 6% were achieved by SVM.%脑机接口技术是一项不依赖人的外周神经和肌肉组织而实现人机交互通信的技术，使人类可以拥有一条不通过肌肉组织与外界交流而实现人机通信及控制的通道。在总结前人研究成果的基础上，采用了小波变换Mallat算法对实验数据进行特征提取，重点研究了时间窗的选取和利用频率范围选取有用信号的问题。通过SVM的分类结果为准确率84.2856%，精密度85.2721%和灵敏度92.0006%。
Galiana-Merino, J.; Parolai, S.
2005-12-01
The Horizontal-to-Vertical (H/V) spectral ratio of seismic noise has become a widely used tool in microzonation, although it has not yet been clearly established whether or not only the stationary part of the recorded signal may be used. In fact, while some studies have suggested the use of only stationary signals others have shown that including transients may improve the results. In this study, we have employed a filtering method based on the wavelet packet transform for removing the stationary part of the noise recordings in the frequency band of interest for the H/V spectral ratio. In this way, we have obtained filtered seismograms with only transients, which have been used for performing the H/V spectral ratio calculation. Moreover, we have also calculated the H/V spectral ratio selecting only stationary noise windows from the seismograms and without making any a priori selection on them. Finally, we have compared the results and analysed the influence of transient noise on the shape of the H/V spectral ratio. The analysis has been carried out on noise recordings collected at 7 stations installed in the Cologne-Bonn region (Germany). Results show that the H/V spectral ratios calculated using only stationary noise do not significantly differ from those obtained without performing any data selection, independent of the site resonance frequency and of the frequency content of the transient. On the contrary, H/V spectral ratios obtained using only transients show a large variability that may be attributed to the kind of source and the source to receiver distance. These results indicate that the effect of transient noise is negligible when the H/V spectral ratios are calculated without performing any data selection, making the H/V spectral ratio technique more attractive for urban area measurements.
Analysis of Acoustic Emission Signals using WaveletTransformation Technique
Directory of Open Access Journals (Sweden)
S.V. Subba Rao
2008-07-01
Full Text Available Acoustic emission (AE monitoring is carried out during proof pressure testing of pressurevessels to find the occurrence of any crack growth-related phenomenon. While carrying out AEmonitoring, it is often found that the background noise is very high. Along with the noise, thesignal includes various phenomena related to crack growth, rubbing of fasteners, leaks, etc. Dueto the presence of noise, it becomes difficult to identify signature of the original signals related to the above phenomenon. Through various filtering/ thresholding techniques, it was found that the original signals were getting filtered out along with noise. Wavelet transformation technique is found to be more appropriate to analyse the AE signals under such situations. Wavelet transformation technique is used to de-noise the AE data. The de-noised signal is classified to identify a signature based on the type of phenomena.Defence Science Journal, 2008, 58(4, pp.559-564, DOI:http://dx.doi.org/10.14429/dsj.58.1677
Chandler Wobble Period and Q Derived by Wavelet Transform
Institute of Scientific and Technical Information of China (English)
De-Chun Liao; Yong-Hong Zhou
2004-01-01
We apply complex Morlet wavelet transform to three polar motion data series,and derive quasi-instantaneous periods of the Chandler and annual wobble by differencing the wavelet transform results versus the scale factor,and then find their zero points.The results show that the mean periods of the Chandler(annual)wobble are 430.71±1.07(365.24±0.11)and 432.71±0.42(365.23±0.18)mean solar days for the data sets of 1900-2001 and 1940-2001,respectively.The maximum relative variation of the quasi-instantaneous period to the mean of the Chandler wobble is less than 1.5% during 1900-2001(3%-5% during 1920-1940),and that of the annual wobble is less than 1.6% during 1900-2001.Quasi-instantaneous and mean values of Q are also derived by using the energy density-period profile of the Chandler wobble.An asymptotic value of Q = 36.7 is obtained by fitting polynomial of exponential of σ-2 to the relationship between Q and σ during 1940-2001.
Dynamic Bayesian wavelet transform: New methodology for extraction of repetitive transients
Wang, Dong; Tsui, Kwok-Leung
2017-05-01
Thanks to some recent research works, dynamic Bayesian wavelet transform as new methodology for extraction of repetitive transients is proposed in this short communication to reveal fault signatures hidden in rotating machine. The main idea of the dynamic Bayesian wavelet transform is to iteratively estimate posterior parameters of wavelet transform via artificial observations and dynamic Bayesian inference. First, a prior wavelet parameter distribution can be established by one of many fast detection algorithms, such as the fast kurtogram, the improved kurtogram, the enhanced kurtogram, the sparsogram, the infogram, continuous wavelet transform, discrete wavelet transform, wavelet packets, multiwavelets, empirical wavelet transform, empirical mode decomposition, local mean decomposition, etc.. Second, artificial observations can be constructed based on one of many metrics, such as kurtosis, the sparsity measurement, entropy, approximate entropy, the smoothness index, a synthesized criterion, etc., which are able to quantify repetitive transients. Finally, given artificial observations, the prior wavelet parameter distribution can be posteriorly updated over iterations by using dynamic Bayesian inference. More importantly, the proposed new methodology can be extended to establish the optimal parameters required by many other signal processing methods for extraction of repetitive transients.
Li, Hong; Ding, Xue
2017-03-01
This paper combines wavelet analysis and wavelet transform theory with artificial neural network, through the pretreatment on point feature attributes before in intrusion detection, to make them suitable for improvement of wavelet neural network. The whole intrusion classification model gets the better adaptability, self-learning ability, greatly enhances the wavelet neural network for solving the problem of field detection invasion, reduces storage space, contributes to improve the performance of the constructed neural network, and reduces the training time. Finally the results of the KDDCup99 data set simulation experiment shows that, this method reduces the complexity of constructing wavelet neural network, but also ensures the accuracy of the intrusion classification.
Analytic discrete cosine harmonic wavelet transform based OFDM system
Indian Academy of Sciences (India)
M N Suma; S V Narasimhan; B Kanmani
2015-02-01
An OFDM based on Analytic Discrete Cosine HarmonicWavelet Transform (ADCHWT_OFDM) has been proposed in this paper. Analytic DCHWT has been realized by applying DCHWT to the original signal and to its Hilbert transform. ADCHWT has been found to be computationally efficient and very effective in improving Bit Error Rate (BER) and Peak to Average Power Ratio (PAPR) performance. Improvement compared to that of Haar-WT OFDM and DFT OFDM is achieved without employing Cyclic Prefix BER is 0.002 for ADCHWT OFDM compared to Haar WT, DFT OFDM which have BER of 0.06 and 0.4, respectively, at 15 dB SNR. PAPR is also reduced by 3 dB compared to DFT OFDM and 0.3 dB reduction compared to Haar WT OFDM.
Remotely sensed image compression based on wavelet transform
Kim, Seong W.; Lee, Heung K.; Kim, Kyung S.; Choi, Soon D.
1995-01-01
In this paper, we present an image compression algorithm that is capable of significantly reducing the vast amount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet transform to remove the spatial redundancy. the transformed images are then encoded by Hilbert-curve scanning and run-length-encoding, followed by Huffman coding. We also present the performance of the proposed algorithm with the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by PSNR (peak signal to noise ratio) and classification capability.
Optimization of integer wavelet transforms based on difference correlation structures.
Li, Hongliang; Liu, Guizhong; Zhang, Zhongwei
2005-11-01
In this paper, a novel lifting integer wavelet transform based on difference correlation structure (DCCS-LIWT) is proposed. First, we establish a relationship between the performance of a linear predictor and the difference correlations of an image. The obtained results provide a theoretical foundation for the following construction of the optimal lifting filters. Then, the optimal prediction lifting coefficients in the sense of least-square prediction error are derived. DCCS-LIWT puts heavy emphasis on image inherent dependence. A distinct feature of this method is the use of the variance-normalized autocorrelation function of the difference image to construct a linear predictor and adapt the predictor to varying image sources. The proposed scheme also allows respective calculations of the lifting filters for the horizontal and vertical orientations. Experimental evaluation shows that the proposed method produces better results than the other well-known integer transforms for the lossless image compression.
Time-frequency analysis of spike-wave discharges using a modified wavelet transform
Bosnyakova, D.Y.; Gabova, A.; Kuznetsova, G.D.; Obukhov, Y.; Midzyanovskaya, I.S.; Salonin, D.V.; Rijn, C.M. van; Coenen, A.M.L.; Tuomisto, L.; Luijtelaar, E.L.J.M. van
2006-01-01
The continuous Morlet wavelet transform was used for the analysis of the time-frequency pattern of spike-wave discharges (SWD) as can be recorded in a genetic animal model of absence epilepsy (rats of the WAG/Rij strain). We developed a new wavelet transform that allows to obtain the time-frequency
Dating the age of admixture via wavelet transform analysis of genome-wide data
I. Pugach (Irina); R. Matveyev (Rostislav); A. Wollstein (Andreas); M.H. Kayser (Manfred); M. Stoneking (Mark)
2011-01-01
textabstractWe describe a PCA-based genome scan approach to analyze genome-wide admixture structure, and introduce wavelet transform analysis as a method for estimating the time of admixture. We test the wavelet transform method with simulations and apply it to genome-wide SNP data from eight admixe
Continuous wavelet transform of wind and wind-induced pressures on a building in suburban terrain
Geurts, C.P.W.; Hajj, M.R.; Tieleman, H.W.
1998-01-01
The wavelet transform is a promising tool for the analysis of incident wind and wind loading on structures. The continuous wavelet transform is applied to full-scale velocity and pressure measurements, taken at the main building of Eindhoven University of Technology. Initial results indicate that th
A New Approach for Diagnosing Epilepsy by Using Wavelet Transform and Neural Networks
2001-10-25
by using wavelet transform and an artificial neural network model. EEG signals are separated into delta, theta, alpha, and beta spectral components...by using wavelet transform . These spectral components are applied to the inputs of the neural network. Then, neural network is trained to give three outputs to signify the health situation of the patients
Evaluation of Heart Rate Variability by Using Wavelet Transform and a Recurrent Neural Network
2007-11-02
variability is proposed. This method combines the wavelet transform with a recurrent neural network. The features of the proposed method are as follows...1. The wavelet transform is utilized for the feature extraction so that the local change of heart rate variability in the time-frequency domain can
Denoising embolic Doppler ultrasound signals using Dual Tree Complex Discrete Wavelet Transform.
Serbes, Gorkem; Aydin, Nizamettin
2010-01-01
Early and accurate detection of asymptomatic emboli is important for monitoring of preventive therapy in stroke-prone patients. One of the problems in detection of emboli is the identification of an embolic signal caused by very small emboli. The amplitude of the embolic signal may be so small that advanced processing methods are required to distinguish these signals from Doppler signals arising from red blood cells. In this study instead of conventional discrete wavelet transform, the Dual Tree Complex Discrete Wavelet Transform was used for denoising embolic signals. Performances of both approaches were compared. Unlike the conventional discrete wavelet transform discrete complex wavelet transform is a shift invariant transform with limited redundancy. Results demonstrate that the Dual Tree Complex Discrete Wavelet Transform based denoising outperforms conventional discrete wavelet denoising. Approximately 8 dB improvement is obtained by using the Dual Tree Complex Discrete Wavelet Transform compared to the improvement provided by the conventional Discrete Wavelet Transform (less than 5 dB).
Contour Extraction in Prostate Ultrasound Images Using the Wavelet Transform and Snakes
2007-11-02
signal noise levels. In this paper we present a semi-automatic prostate contour extraction scheme, which is based on the wavelet transform and active...contour models, or snakes. The ultrasound image is first decomposed into edge naps at different resolutions via the wavelet transform . Seed points are
Energy Technology Data Exchange (ETDEWEB)
Bartosch, T. [Erlanger-Nuernberg Univ., Erlanger (Germany). Lehrstul fuer Nachrichtentechnik I; Seidl, D. [Seismologisches Zentralobservatorium Graefenberg, Erlanegen (Greece). Bundesanstalt fuer Geiwissenschaften und Rohstoffe
1999-06-01
Among a variety of spectrogram methods short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were selected to analyse transients in non-stationary signals. Depending on the properties of the tremor signals from the volcanos Mt. Stromboli, Mt. Semeru and Mt. Pinatubo were analyzed using both methods. The CWT can also be used to extend the definition of coherency into a time-varying coherency spectrogram. An example is given using array data from the volcano Mt. Stromboli (Italy).
ECG signal compression using combined modified discrete cosine and discrete wavelet transforms.
Ahmed, S M; Al-Ajlouni, A F; Abo-Zahhad, M; Harb, B
2009-01-01
A new hybrid two-stage electrocardiogram (ECG) signal compression method based on the modified discrete cosine transform (MDCT) and discrete wavelet transform (DWT) is proposed. The ECG signal is partitioned into blocks and the MDCT is applied to each block to decorrelate the spectral information. Then, the DWT is applied to the resulting MDCT coefficients. Removing spectral redundancy is achieved by compressing the subordinate components more than the dominant components. The resulting wavelet coefficients are then thresholded and compressed using energy packing and binary-significant map coding technique for storage space saving. Experiments on ECG records from the MIT-BIH database are performed with various combinations of MDCT and wavelet filters at different transformation levels, and quantization intervals. The decompressed signals are evaluated using percentage rms error (PRD) and zero-mean rms error (PRD(1)) measures. The results showed that the proposed method provides low bit-rate and high quality of the reconstructed signal. It offers average compression ratio (CR) of 21.5 and PRD of 5.89%, which would be suitable for most monitoring and diagnoses applications. Simulation results show that the proposed method compares favourably with various state-of-the-art ECG compressors.
Zhao, Bin
2015-02-01
Temperature-pressure coupled field analysis of liquefied petroleum gas (LPG) tank under jet fire can offer theoretical guidance for preventing the fire accidents of LPG tank, the application of super wavelet finite element on it is studied in depth. First, review of related researches on heat transfer analysis of LPG tank under fire and super wavelet are carried out. Second, basic theory of super wavelet transform is studied. Third, the temperature-pressure coupled model of gas phase and liquid LPG under jet fire is established based on the equation of state, the VOF model and the RNG k-ɛ model. Then the super wavelet finite element formulation is constructed using the super wavelet scale function as interpolating function. Finally, the simulation is carried out, and results show that the super wavelet finite element method has higher computing precision than wavelet finite element method.
Damage Detection Methods for Offshore Platforms Based on Wavelet Packet Transform
Institute of Scientific and Technical Information of China (English)
LI Dong-sheng; ZHANG Zhao-de; WANG De-yu
2005-01-01
The wavelet packet transform is used for the damage detection of offshore platforms. When some damage occurs, the dynamic response parameters of the structure will shift subtly. However, in some cases, the dynamic parameters, such as dynamic response, are not sensitive, and it is very difficult to predict the existence of damage. The present paper aims to describe how to find small damage by the use of wavelet packet transform. As the wavelet packet transform can be used to quickly find the singularity of the response signal on different scales, the acceleration signal of a damaged offshore platform in the time domain is transformed through the wavelet packet. Experimental results show that the Daubechies 4 wavelet transform can be used to detect damage.
Wavelet transform based on inner product in fault diagnosis of rotating machinery: A review
Chen, Jinglong; Li, Zipeng; Pan, Jun; Chen, Gaige; Zi, Yanyang; Yuan, Jing; Chen, Binqiang; He, Zhengjia
2016-03-01
As a significant role in industrial equipment, rotating machinery fault diagnosis (RMFD) always draws lots of attention for guaranteeing product quality and improving economic benefit. But non-stationary vibration signal with a large amount of noise on abnormal condition of weak fault or compound fault in many cases would lead to this task challenging. As one of the most powerful non-stationary signal processing techniques, wavelet transform (WT) has been extensively studied and widely applied in RMFD. Numerous publications about the study and applications of WT for RMFD have been presented to academic journals, technical reports and conference proceedings. Many previous publications admit that WT can be realized by means of inner product principle of signal and wavelet base. This paper verifies the essence on inner product operation of WT by simulation and field experiments. Then the development process of WT based on inner product is concluded and the applications of major developments in RMFD are also summarized. Finally, super wavelet transform as an important prospect of WT based on inner product are presented and discussed. It is expected that this paper can offer an in-depth and comprehensive references for researchers and help them with finding out further research topics.
The use of wavelet transforms in the solution of two-phase flow problems
Energy Technology Data Exchange (ETDEWEB)
Moridis, G.J. [Lawrence Berkeley Lab., CA (United States); Nikolaou, M.; You, Yong [Texas A& M Univ., College Station, TX (United States). Dept. of Chemical Engineering
1994-10-01
In this paper we present the use of wavelets to solve the nonlinear Partial Differential.Equation (PDE) of two-phase flow in one dimension. The wavelet transforms allow a drastically different approach in the discretization of space. In contrast to the traditional trigonometric basis functions, wavelets approximate a function not by cancellation but by placement of wavelets at appropriate locations. When an abrupt chance, such as a shock wave or a spike, occurs in a function, only local coefficients in a wavelet approximation will be affected. The unique feature of wavelets is their Multi-Resolution Analysis (MRA) property, which allows seamless investigational any spatial resolution. The use of wavelets is tested in the solution of the one-dimensional Buckley-Leverett problem against analytical solutions and solutions obtained from standard numerical models. Two classes of wavelet bases (Daubechies and Chui-Wang) and two methods (Galerkin and collocation) are investigated. We determine that the Chui-Wang, wavelets and a collocation method provide the optimum wavelet solution for this type of problem. Increasing the resolution level improves the accuracy of the solution, but the order of the basis function seems to be far less important. Our results indicate that wavelet transforms are an effective and accurate method which does not suffer from oscillations or numerical smearing in the presence of steep fronts.
Comparative study of wavelet denoising in myoelectric control applications.
Sharma, Tanu; Veer, Karan
2016-01-01
Here, the wavelet analysis has been investigated to improve the quality of myoelectric signal before use in prosthetic design. Effective Surface Electromyogram (SEMG) signals were estimated by first decomposing the obtained signal using wavelet transform and then analysing the decomposed coefficients by threshold methods. With the appropriate choice of wavelet, it is possible to reduce interference noise effectively in the SEMG signal. However, the most effective wavelet for SEMG denoising is chosen by calculating the root mean square value and signal power values. The combined results of root mean square value and signal power shows that wavelet db4 performs the best denoising among the wavelets. Furthermore, time domain and frequency domain methods were applied for SEMG signal analysis to investigate the effect of muscle-force contraction on the signal. It was found that, during sustained contractions, the mean frequency (MNF) and median frequency (MDF) increase as muscle force levels increase.
Discrete directional wavelet bases and frames: analysis and applications
Dragotti, Pier Luigi; Velisavljevic, Vladan; Vetterli, Martin; Beferull-Lozano, Baltasar
2003-11-01
The application of the wavelet transform in image processing is most frequently based on a separable construction. Lines and columns in an image are treated independently and the basis functions are simply products of the corresponding one dimensional functions. Such method keeps simplicity in design and computation, but is not capable of capturing properly all the properties of an image. In this paper, a new truly separable discrete multi-directional transform is proposed with a subsampling method based on lattice theory. Alternatively, the subsampling can be omitted and this leads to a multi-directional frame. This transform can be applied in many areas like denoising, non-linear approximation and compression. The results on non-linear approximation and denoising show interesting gains compared to the standard two-dimensional analysis.
Extraction of Partial Discharge Acoustic Signal by Wavelet Transform with Teager's Energy Operator
Institute of Scientific and Technical Information of China (English)
DU Boxue; OUYANG Mingjian; WU Yuan; WEI Guozhong
2005-01-01
To develop a measurement system for monitoring partial discharge (PD) without the effect of external interferences,an algorithm of PD signal extraction based on wavelet transform with Teager's energy operators was presented.Acoustic signal generated by PD was selected to remove excessive interfering signals and electromagnetic interferences.Acoustic signals were collected and decomposed into 10 levels by wavelet transform into approximation and detail components."Daubechies 25"was proved to be the most suitable mother wavelet for the extraction of PD acoustic signals.Compared with conventional wavelet denoising method,Teager's energy operators were adopted to the PD signal reconstruction and the signal to noise ratio was pulse amplitude.
Spline and spline wavelet methods with applications to signal and image processing
Averbuch, Amir Z; Zheludev, Valery A
This volume provides universal methodologies accompanied by Matlab software to manipulate numerous signal and image processing applications. It is done with discrete and polynomial periodic splines. Various contributions of splines to signal and image processing from a unified perspective are presented. This presentation is based on Zak transform and on Spline Harmonic Analysis (SHA) methodology. SHA combines approximation capabilities of splines with the computational efficiency of the Fast Fourier transform. SHA reduces the design of different spline types such as splines, spline wavelets (SW), wavelet frames (SWF) and wavelet packets (SWP) and their manipulations by simple operations. Digital filters, produced by wavelets design process, give birth to subdivision schemes. Subdivision schemes enable to perform fast explicit computation of splines' values at dyadic and triadic rational points. This is used for signals and images upsampling. In addition to the design of a diverse library of splines, SW, SWP a...
Full-frame compression of discrete wavelet and cosine transforms
Lo, Shih-Chung B.; Li, Huai; Krasner, Brian; Freedman, Matthew T.; Mun, Seong K.
1995-04-01
At the foreground of computerized radiology and the filmless hospital are the possibilities for easy image retrieval, efficient storage, and rapid image communication. This paper represents the authors' continuous efforts in compression research on full-frame discrete wavelet (FFDWT) and full-frame discrete cosine transforms (FFDCT) for medical image compression. Prior to the coding, it is important to evaluate the global entropy in the decomposed space. It is because of the minimum entropy, that a maximum compression efficiency can be achieved. In this study, each image was split into the top three most significant bit (MSB) and the remaining remapped least significant bit (RLSB) images. The 3MSB image was compressed by an error-free contour coding and received an average of 0.1 bit/pixel. The RLSB image was either transformed to a multi-channel wavelet or the cosine transform domain for entropy evaluation. Ten x-ray chest radiographs and ten mammograms were randomly selected from our clinical database and were used for the study. Our results indicated that the coding scheme in the FFDCT domain performed better than in FFDWT domain for high-resolution digital chest radiographs and mammograms. From this study, we found that decomposition efficiency in the DCT domain for relatively smooth images is higher than that in the DWT. However, both schemes worked just as well for low resolution digital images. We also found that the image characteristics of the `Lena' image commonly used in the compression literature are very different from those of radiological images. The compression outcome of the radiological images can not be extrapolated from the compression result based on the `Lena.'
Jiang, Hua; Lu, Wenke; Zhang, Guoan
2013-07-01
In this paper, we propose a low insertion loss and miniaturization wavelet transform and inverse transform processor using surface acoustic wave (SAW) devices. The new SAW wavelet transform devices (WTDs) use the structure with two electrode-widths-controlled (EWC) single phase unidirectional transducers (SPUDT-SPUDT). This structure consists of the input withdrawal weighting interdigital transducer (IDT) and the output overlap weighting IDT. Three experimental devices for different scales 2(-1), 2(-2), and 2(-3) are designed and measured. The minimum insertion loss of the three devices reaches 5.49dB, 4.81dB, and 5.38dB respectively which are lower than the early results. Both the electrode width and the number of electrode pairs are reduced, thus making the three devices much smaller than the early devices. Therefore, the method described in this paper is suitable for implementing an arbitrary multi-scale low insertion loss and miniaturization wavelet transform and inverse transform processor using SAW devices.
ECG signals denoising using wavelet transform and independent component analysis
Liu, Manjin; Hui, Mei; Liu, Ming; Dong, Liquan; Zhao, Zhu; Zhao, Yuejin
2015-08-01
A method of two channel exercise electrocardiograms (ECG) signals denoising based on wavelet transform and independent component analysis is proposed in this paper. First of all, two channel exercise ECG signals are acquired. We decompose these two channel ECG signals into eight layers and add up the useful wavelet coefficients separately, getting two channel ECG signals with no baseline drift and other interference components. However, it still contains electrode movement noise, power frequency interference and other interferences. Secondly, we use these two channel ECG signals processed and one channel signal constructed manually to make further process with independent component analysis, getting the separated ECG signal. We can see the residual noises are removed effectively. Finally, comparative experiment is made with two same channel exercise ECG signals processed directly with independent component analysis and the method this paper proposed, which shows the indexes of signal to noise ratio (SNR) increases 21.916 and the root mean square error (MSE) decreases 2.522, proving the method this paper proposed has high reliability.
Background Subtraction Based on Three-Dimensional Discrete Wavelet Transform.
Han, Guang; Wang, Jinkuan; Cai, Xi
2016-03-30
Background subtraction without a separate training phase has become a critical task, because a sufficiently long and clean training sequence is usually unavailable, and people generally thirst for immediate detection results from the first frame of a video. Without a training phase, we propose a background subtraction method based on three-dimensional (3D) discrete wavelet transform (DWT). Static backgrounds with few variations along the time axis are characterized by intensity temporal consistency in the 3D space-time domain and, hence, correspond to low-frequency components in the 3D frequency domain. Enlightened by this, we eliminate low-frequency components that correspond to static backgrounds using the 3D DWT in order to extract moving objects. Owing to the multiscale analysis property of the 3D DWT, the elimination of low-frequency components in sub-bands of the 3D DWT is equivalent to performing a pyramidal 3D filter. This 3D filter brings advantages to our method in reserving the inner parts of detected objects and reducing the ringing around object boundaries. Moreover, we make use of wavelet shrinkage to remove disturbance of intensity temporal consistency and introduce an adaptive threshold based on the entropy of the histogram to obtain optimal detection results. Experimental results show that our method works effectively in situations lacking training opportunities and outperforms several popular techniques.
Cavalier, Paul; Baghai-Wadji, Alireza; Poprawski, Yohann; Inggs, Michael
2016-11-01
Wavelet methods have been used in potential fields study to estimate source properties such as depth or structural index, through the analysis of Wavelet Transform Modulus Maxima Lines (WTMML) intersections and slopes at high scales. Little has been done on the study of maximum points of the wavelet diagram, that we call here Maximum Wavelet Coefficient Scales (MWCS). Previous works have shown interesting correlations between MWCS and source depths, depending on the wavelet used in regards to the source nature and the data derivative order. In this paper, we introduce an empirical law involving spectral parameters that have not been studied so far, which allows analytical calculation of the MWCS, knowing the source characteristics and using certain wavelets. In return, the study of MWCS allows recovering source characteristics from the use of a single wavelet, without prior knowledge on the source. We demonstrate through synthetic models that the new capability of predicting the source type and depth according to the wavelet coefficient behaviour allows new ways of potential fields' sources characterization and identification. We show an application of the formula on a real case example in the Uinta Mountains (Utah, USA).
Medical image denoising using dual tree complex thresholding wavelet transform and Wiener filter
Directory of Open Access Journals (Sweden)
Hilal Naimi
2015-01-01
Full Text Available Image denoising is the process to remove the noise from the image naturally corrupted by the noise. The wavelet method is one among various methods for recovering infinite dimensional objects like curves, densities, images, etc. The wavelet techniques are very effective to remove the noise because of their ability to capture the energy of a signal in few energy transform values. The wavelet methods are based on shrinking the wavelet coefficients in the wavelet domain. We propose in this paper, a denoising approach basing on dual tree complex wavelet and shrinkage with the Wiener filter technique (where either hard or soft thresholding operators of dual tree complex wavelet transform for the denoising of medical images are used. The results proved that the denoised images using DTCWT (Dual Tree Complex Wavelet Transform with Wiener filter have a better balance between smoothness and accuracy than the DWT and are less redundant than SWT (StationaryWavelet Transform. We used the SSIM (Structural Similarity Index Measure along with PSNR (Peak Signal to Noise Ratio and SSIM map to assess the quality of denoised images.
An Analysis of 2D Bi-Orthogonal Wavelet Transform Based On Fixed Point Approximation
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P. Vijayalakshmi
2014-04-01
Full Text Available As the world advances with technology and research, images are being widely used in many fields such as biometrics, remote sensing, reconstruction etc. This tremendous growth in image processing applications, demands majorly for low power consumption, low cost and small chip area. In this paper we analyzed 2D bi-orthogonal wavelet transform based on Fixed point approximation. Filter coefficients of the bi-orthogonal wavelet filters are quantized before implementation. The efficiency of the results is measured for some standard gray scale images by comparing the original input images and the reconstructed images. SNR and PSNR value shows that this implementation is performed effectively without any loss in image quality.
Digital Watermarks Using Discrete Wavelet Transformation and Spectrum Spreading
Directory of Open Access Journals (Sweden)
Ryousuke Takai
2003-12-01
Full Text Available In recent tears, digital media makes rapid progress through the development of digital technology. Digital media normally assures fairly high quality, nevertheless can be easily reproduced in a perfect form. This perfect reproducibility takes and advantage from a certain point of view, while it produces an essential disadvantage, since digital media is frequently copied illegally. Thus the problem of the copyright protection becomes a very important issue. A solution of this problem is to embed digital watermarks that is not perceived clearly by usual people, but represents the proper right of original product. In our method, the images data in the frequency domain are transformed by the Discrete Wavelet Transform and analyzed by the multi resolution approximation, [1]. Further, the spectrum spreading is executed by using PN-sequences. Choi and Aizawa [7] embed watermarks by using block correlation of DCT coefficients. Thus, we apply Discrete Cosine Transformation, abbreviated to DCT, instead of the Fourier transformation in order to embed watermarks.If the value of this variance is high then we decide that the block has bigger magnitude for visual fluctuations. Henceforth, we may embed stronger watermarks, which gives resistance for images processing, such as attacks and/or compressions.
Digital Watermarks Using Discrete Wavelet Transformation and Spectrum Spreading
Directory of Open Access Journals (Sweden)
Ryousuke Takai
2003-12-01
Full Text Available In recent tears, digital media makes rapid progress through the development of digital technology. Digital media normally assures fairly high quality, nevertheless can be easily reproduced in a perfect form. This perfect reproducibility takes and advantage from a certain point of view, while it produces an essential disadvantage, since digital media is frequently copied illegally. Thus the problem of the copyright protection becomes a very important issue. A solution of this problem is to embed digital watermarks that is not perceived clearly by usual people, but represents the proper right of original product. In our method, the images data in the frequency domain are transformed by the Discrete Wavelet Transform and analyzed by the multi resolution approximation, [1]. Further, the spectrum spreading is executed by using PN-sequences. Choi and Aizawa [7] embed watermarks by using block correlation of DCT coefficients. Thus, we apply Discrete Cosine Transformation, abbreviated to DCT, instead of the Fourier transformation in order to embed watermarks.If the value of this variance is high then we decide that the block has bigger magnitude for visual fluctuations. Henceforth, we may embed stronger watermarks, which gives resistance for images processing, such as attacks and/or compressions.
PERFORMANCE EVALUATION OF KEY FOR WATERMARKING USING 2-D WAVELET TRANSFORMATIONS
Directory of Open Access Journals (Sweden)
D.MATHIVADHANI,
2011-03-01
Full Text Available The digital watermark technology is now drawing attention as a useful method of protecting copyrights of digital contents such as audio, image, and video. Especially, efficient image watermarking methods have been developed in the DWT (discrete wavelet transform domain. With the rapid development of ecommerce and internet technology, the applications of multimedia products (image, video and audio, etc.are widely spread. Meanwhile the issue on the security of the copyright has been receiving more and more attention recently. Watermarking technology is an effective way to protect digital ultimedia products by embedding a watermark into the target product to prove the owner’s right on the product. In this paper, the digital watermarking algorithm is explained. This algorithm uses images and different types of noise are also added. The PSNR for each image is used to measure the efficacy of the algorithm. This objective measure is also used to determine the influence of the better type of noise. In summary, the results support the concept that the simpler wavelet transforms and add noise to a signal. , e.g. the Haar wavelet and add white Gaussian noise to a signal. Consistently outperform the more complex ones when using a watermark.
Multidimensional filter banks and wavelets research developments and applications
Levy, Bernard
1997-01-01
Multidimensional Filter Banks and Wavelets: Reserach Developments and Applications brings together in one place important contributions and up-to-date research results in this important area. Multidimensional Filter Banks and Wavelets: Research Developments and Applications serves as an excellent reference, providing insight into some of the most important research issues in the field.
A new phase comparison pilot protection based on wavelet transform
Institute of Scientific and Technical Information of China (English)
YANG Ying; TAI Neng-ling; YU Wei-yong
2006-01-01
Current phase comparison based pilot protection had been generally utilized as primary protection of the transmission lines in China from the 1950's to the 1980's. Conventional phase comparison pilot protection has a long phase comparison time, which results in a longer fault-clearing time. This paper proposes a new current phase comparison. pilot protection scheme that is based on non-power frequency fault current component.The phase of the fourth harmonic current of each end of the protected line has been abstracted by utilizing complex wavelet transformation and then compared in order to determine whether the inner fault occurs or not. This way can greatly decrease fault-clearing time and improve performances of this pilot protection when fault occurs under the heavy-load current and asymmetrical operation conditions. Many EMTP simulations have verified theproposed scheme's correctness and effectiveness.
Fingerprint Gender Classification using Wavelet Transform and Singular Value Decomposition
Gnanasivam, P
2012-01-01
A novel method of gender Classification from fingerprint is proposed based on discrete wavelet transform (DWT) and singular value decomposition (SVD). The classification is achieved by extracting the energy computed from all the sub-bands of DWT combined with the spatial features of non-zero singular values obtained from the SVD of fingerprint images. K nearest neighbor (KNN) used as a classifier. This method is experimented with the internal database of 3570 fingerprints finger prints in which 1980 were male fingerprints and 1590 were female fingerprints. Finger-wise gender classification is achieved which is 94.32% for the left hand little fingers of female persons and 95.46% for the left hand index finger of male persons. Gender classification for any finger of male persons tested is attained as 91.67% and 84.69% for female persons respectively. Overall classification rate is 88.28% has been achieved.
Study on Singularity of Chaotic Signal Based on Wavelet Transform
Institute of Scientific and Technical Information of China (English)
YOU Rong-yi
2006-01-01
Based on the variations of wavelet transform modulus maxima at multi-scales,the singularity of chaotic signals are studied,and the singularity of these signals are measured by the Lipschitz exponent.In the meantime,a nonlinear method is proposed based on the higher order statistics,on the other aspect,which characterizes the higher order singular spectrum (HOSS) of chaotic signals.All computations are done with Lorenz attractor,Rossler attractor and EEG (electroencephalogram) time series and the comparisions among these results are made.The experimental results show that the Lipschitz exponents and the higher order singular spectra of these signals are significantly different from each other,which indicates these methods are effective for studing the singularity of chaotic signals.
Psychoacoustic Music Analysis Based on the Discrete Wavelet Packet Transform
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Xing He
2008-01-01
Full Text Available Psychoacoustical computational models are necessary for the perceptual processing of acoustic signals and have contributed significantly in the development of highly efficient audio analysis and coding. In this paper, we present an approach for the psychoacoustic analysis of musical signals based on the discrete wavelet packet transform. The proposed method mimics the multiresolution properties of the human ear closer than other techniques and it includes simultaneous and temporal auditory masking. Experimental results show that this method provides better masking capabilities and it reduces the signal-to-masking ratio substantially more than other approaches, without introducing audible distortion. This model can lead to greater audio compression by permitting further bit rate reduction and more secure watermarking by providing greater signal space for information hiding.
WAVELET TRANSFORM METHOD FOR DERIVING ATMOSPHERIC BOUNDARY LAYER HEIGHT FROM LIDAR SIGNALS
RAJITHA PALETI; Y. Bhavani Kumar; T. Krishna Chaitanya
2013-01-01
Wavelet method of determining the atmospheric boundary layer (ABL) height from lidar signals is presented in this paper. The wavelet covariance transform (WCT) method employed determines the significant gradient in the measured lidar signals. Using this method, the accuracy of ABL height detection enhances with increased dilation length. The developed wavelet algorithm is coded in MATLAB software and has a provision to alter the dilation length in real-time for a given translation estimate.
Investigation of PAPR in Discrete Wavelet Transform based Multi-carrier Systems
Neha S; Thushara S; Ramanathan R
2015-01-01
The objective of the paper is to formulate a measure to reduce PAPR problem in Orthogonal Frequency Division Multiplexing. To mitigate the problem of PAPR, a Discrete Wavelet Transform based system is employed instead of conventional OFDM. For the comparative study, the PAPR in conventional OFDM is analyzed for varying number of subcarriers and for different channel taps. The result of conventional OFDM is compared with wavelet based OFDM, employing wavelets namely - ‘Haar’, ‘Daubechies’, ‘Sy...
AN EFFICIENT HILBERT AND INTEGER WAVELET TRANSFORM BASED VIDEO WATERMARKING
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AGILANDEESWARI L.
2016-03-01
Full Text Available In this paper, an efficient, highly imperceptible, robust, and secure digital video watermarking technique for content authentication based on Hilbert transform in the Integer Wavelet Transform (IWT domain has been introduced. The Hilbert coefficients of gray watermark image are embedded into the cover video frames Hilbert coefficients on the 2-level IWT decomposed selected block on sub-bands using Principal Component Analysis (PCA technique. The authentication is achieved by using the digital signature mechanism. This mechanism is used to generate and embed a digital signature after embedding the watermarks. Since, the embedding process is done in Hilbert transform domain, the imperceptibility and the robustness of the watermark is greatly improved. At the receiver end, prior to the extraction of watermark, the originality of the content is verified through the authentication test. If the generated and received signature matches, it proves that the received content is original and performs the extraction process, otherwise deny the extraction process due to unauthenticated received content. The proposed method avoids typical degradations in the imperceptibility level of watermarked video in terms of Average Peak Signal – to – Noise Ratio (PSNR value of about 48db, while it is still providing better robustness against common video distortions such as frame dropping, averaging, and various image processing attacks such as noise addition, median filtering, contrast adjustment, and geometrical attacks such as, rotation and cropping in terms of Normalized Correlation Coefficient (NCC value of about nearly 1.
Region-based image denoising through wavelet and fast discrete curvelet transform
Gu, Yanfeng; Guo, Yan; Liu, Xing; Zhang, Ye
2008-10-01
Image denoising always is one of important research topics in the image processing field. In this paper, fast discrete curvelet transform (FDCT) and undecimated wavelet transform (UDWT) are proposed for image denoising. A noisy image is first denoised by FDCT and UDWT separately. The whole image space is then divided into edge region and non-edge regions. After that, wavelet transform is performed on the images denoised by FDCT and UDWT respectively. Finally, the resultant image is fused through using both of edge region wavelet cofficients of the image denoised by FDCT and non-edge region wavelet cofficients of the image denoised by UDWT. The proposed method is validated through numerical experiments conducted on standard test images. The experimental results show that the proposed algorithm outperforms wavelet-based and curvelet-based image denoising methods and preserve linear features well.
Institute of Scientific and Technical Information of China (English)
杨会成; 费琛; 王筱薇倩; 杨惠
2012-01-01
The wavelet packet has good time-frequency localization character and adaptive ability, and the aim is to achieve lower image noise and recover the original image in the field of image preprocessing applications. In order to realize the autonomous vehicles for road information and the accurate control of operation, the paper uses the method of the wavelet packet transform and the average filtering to preprocess the collected image data. Finally, through the method of binarization with the maximum variance select threshold, dynamic iterative threshold method, it can p this de ick up the black guide line. Compared with the traditional sign is accurate and complete to extract the black guide lines in the track. A large number of simulation experiment results show that the scheme design in the aspect of gathering information is accurate, simple and effective. In addition, this design has been well validated in the intelligent car platform.%为了实现车辆自主获取道路信息并对行驶状态进行准确控制,采用小波包变换法和均值滤波法相结合的思想,对摄像头采集到的信息进行图像预处理,通过最大方差取阈法二值化提取出黑色引导线。与传统的动态迭代阈值法相比,这种设计方案可以准确并且完整地提取出赛道中的黑色引导线。仿真实验结果表明：该设计方案采集信息准确,简单有效,在智能小车平台上得到了很好的验证。
Institute of Scientific and Technical Information of China (English)
黄建招; 谢建; 李锋; 任建华
2012-01-01
提出基于离散平稳小波的改进自适应降噪方法,并将该方法应用于压力信号消噪,取得了优于传统小波消噪的效果.方法利用平稳小波的冗余特性,解决了传统二进小波变换降噪方法在奇异点存在振荡效应的不足,同时将尺度系数的噪声与各层噪声强度不同纳入分析.利用噪声强度估计各分解层阈值,对尺度和小波系数同时进行自适应降噪.将该方法应用于压力信号消噪,并与传统离散二进小波进行比较,证明了方法的可行性和有效性.%An improved self-adaptive de-noising method based on discrete stationary wavelet transform is put forward. The method is used for pressure signal de-noising and get better effect than the traditional discrete binary wavelet de-noising. In this method, the discrete stationary wavelet transform is used to solve the oscillation effects of singular points in signal de-noising by the discrete binary wavelet transform,and the detail coefficients noise and different noise intensity in different level are taken into consideration. The detail and approximation coefficients in each decomposition level are self-adaptive denoised using the thresholds, which are estimated by the noise intensity accordingly. The pressure signal de-noisong experiment is carried out compared with the traditional discrete binary wavelet transform,the feasibility and validity of the mehtod are proved.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Division of high resolution sequence stratigraphy units based on wavelet transform of logging data is found to be good at identifying subtle cycles of geological process in Kongnan area of Dagang Oilfield. The analysis of multi-scales gyre of formation with 1-D continuous Dmey wavelet transform of log curve (GR) and 1-D discrete Daubechies wavelet transform of log curve (Rt) all make the division of sequence interfaces more objective and precise, which avoids the artificial influence with core analysis and the uncertainty with seismic data and core analysis.
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Wavelet transform is used to analyze the scaling rule convection flow from two aspects. By utilizing the method of extended self similarity (ESS), one can find the obtained scaling exponent agrees well with the one obtained from the temperature data in a experiment of wind tunnel. And then we propose a newly defined formula based on wavelet transform, and can determine the scaling exponent ξ(q) of temperature data. The obtained results demonstrate that we can correctly extract ξ(q) by using the method which is named as wavelet transform maximum modulus (WTMM).``
Blind source separation of multichannel electroencephalogram based on wavelet transform and ICA
Institute of Scientific and Technical Information of China (English)
You Rong-Yi; Chen Zhong
2005-01-01
Combination of the wavelet transform and independent component analysis (ICA) was employed for blind source separation (BSS) of multichannel electroencephalogram (EEG). After denoising the original signals by discrete wavelet transform, high frequency components of some noises and artifacts were removed from the original signals. The denoised signals were reconstructed again for the purpose of ICA, such that the drawback that ICA cannot distinguish noises from source signals can be overcome effectively. The practical processing results showed that this method is an effective way to BSS of multichannel EEG. The method is actually a combination of wavelet transform with adaptive neural network, so it is also useful for BBS of other complex signals.
Blind source separation of multichannel electroencephalogram based on wavelet transform and ICA
You, Rong-Yi; Chen, Zhong
2005-11-01
Combination of the wavelet transform and independent component analysis (ICA) was employed for blind source separation (BSS) of multichannel electroencephalogram (EEG). After denoising the original signals by discrete wavelet transform, high frequency components of some noises and artifacts were removed from the original signals. The denoised signals were reconstructed again for the purpose of ICA, such that the drawback that ICA cannot distinguish noises from source signals can be overcome effectively. The practical processing results showed that this method is an effective way to BSS of multichannel EEG. The method is actually a combination of wavelet transform with adaptive neural network, so it is also useful for BBS of other complex signals.
MULTI-SPECTRAL AND HYPERSPECTRAL IMAGE FUSION USING 3-D WAVELET TRANSFORM
Institute of Scientific and Technical Information of China (English)
Zhang Yifan; He Mingyi
2007-01-01
Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspectral image. According to the characteristics and 3-Dimensional (3-D) feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures: Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling (RIBSR) method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution (A&S) rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A&S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.
Hilbert-Huang transform and wavelet analysis of time history signal
Institute of Scientific and Technical Information of China (English)
石春香; 罗奇峰
2003-01-01
The brief theories of wavelet analysis and Hilbert-Huang transform (HHT) are introduced firstly in the present paper. Then several signal data were analyzed by using wavelet and HHT methods, respectively. The comparison shows that HHT is not only an effective method for analyzing non-stationary data, but also is a useful tool for examining detailed characters of time history signal.
Institute of Scientific and Technical Information of China (English)
Wang Na; Zhang Li; Zhou Xiao'an; Jia Chuanying; Li Xia
2005-01-01
This letter exploits fundamental characteristics of a wavelet transform image to form a progressive octave-based spatial resolution. Each wavelet subband is coded based on zeroblock and quardtree partitioning ordering scheme with memory optimization technique. The method proposed in this letter is of low complexity and efficient for Internet plug-in software.
Damage monitoring of aircraft structures made of composite materials using wavelet transforms
Molchanov, D.; Safin, A.; Luhyna, N.
2016-10-01
The present article is dedicated to the study of the acoustic properties of composite materials and the application of non-destructive testing methods to aircraft components. A mathematical model of a wavelet transformed signal is presented. The main acoustic (vibration) properties of different composite material structures were researched. Multiple vibration parameter dependencies on the noise reduction factor were derived. The main steps of a research procedure and new method algorithm are presented. The data obtained was compared with the data from a three dimensional laser-Doppler scanning vibrometer, to validate the results. The new technique was tested in the laboratory and on civil aircraft at a training airfield.
Fabric defect detection using the wavelet transform in an ARM processor
Fernández, J. A.; Orjuela, S. A.; Álvarez, J.; Philips, W.
2012-01-01
Small devices used in our day life are constructed with powerful architectures that can be used for industrial applications when requiring portability and communication facilities. We present in this paper an example of the use of an embedded system, the Zeus epic 520 single board computer, for defect detection in textiles using image processing. We implement the Haar wavelet transform using the embedded visual C++ 4.0 compiler for Windows CE 5. The algorithm was tested for defect detection using images of fabrics with five types of defects. An average of 95% in terms of correct defect detection was obtained, achieving a similar performance than using processors with float point arithmetic calculations.
Serbes, Gorkem; Aydin, Nizamettin
2014-01-01
Quadrature signals are dual-channel signals obtained from the systems employing quadrature demodulation. Embolic Doppler ultrasound signals obtained from stroke-prone patients by using Doppler ultrasound systems are quadrature signals caused by emboli, which are particles bigger than red blood cells within circulatory system. Detection of emboli is an important step in diagnosing stroke. Most widely used parameter in detection of emboli is embolic signal-to-background signal ratio. Therefore, in order to increase this ratio, denoising techniques are employed in detection systems. Discrete wavelet transform has been used for denoising of embolic signals, but it lacks shift invariance property. Instead, dual-tree complex wavelet transform having near-shift invariance property can be used. However, it is computationally expensive as two wavelet trees are required. Recently proposed modified dual-tree complex wavelet transform, which reduces the computational complexity, can also be used. In this study, the denoising performance of this method is extensively evaluated and compared with the others by using simulated and real quadrature signals. The quantitative results demonstrated that the modified dual-tree-complex-wavelet-transform-based denoising outperforms the conventional discrete wavelet transform with the same level of computational complexity and exhibits almost equal performance to the dual-tree complex wavelet transform with almost half computational cost.
Property study of integer wavelet transform lossless compression coding based on lifting scheme
Xie, Cheng Jun; Yan, Su; Xiang, Yang
2006-01-01
In this paper the algorithms and its improvement of integer wavelet transform combining SPIHT and arithmetic coding in image lossless compression is mainly studied. The experimental result shows that if the order of low-pass filter vanish matrix is fixed, the improvement of compression effect is not evident when invertible integer wavelet transform is satisfied and focusing of energy property monotonic increase with transform scale. For the same wavelet bases, the order of low-pass filter vanish matrix is more important than the order of high-pass filter vanish matrix in improving the property of image compression. Integer wavelet transform lossless compression coding based on lifting scheme has no relation to the entropy of image. The effect of compression is depended on the the focuing of energy property of image transform.
Investigation of PAPR in Discrete Wavelet Transform based Multi-carrier Systems
Directory of Open Access Journals (Sweden)
Neha S
2015-10-01
Full Text Available The objective of the paper is to formulate a measure to reduce PAPR problem in Orthogonal Frequency Division Multiplexing. To mitigate the problem of PAPR, a Discrete Wavelet Transform based system is employed instead of conventional OFDM. For the comparative study, the PAPR in conventional OFDM is analyzed for varying number of subcarriers and for different channel taps. The result of conventional OFDM is compared with wavelet based OFDM, employing wavelets namely - ‘Haar’, ‘Daubechies’, ‘Symlets’ and ‘Biorthogonal’ wavelets. Further the PAPR is analyzed for varying levels and different length of channel impulse response. The simulation results show that wavelet based OFDM has less PAPR than conventional OFDM. With the increase in the number level, the PAPR at the demodulator side decreases in the wavelet based OFDM.
Hybrid discrete cosine transform-discrete wavelet transform for progressive image compression
Boukaache, Abdennour; Doghmane, Noureddine
2012-01-01
In this paper, we propose an image compression algorithm that uses a hybrid transform and an improved modified set partitioning in hierarchical trees (SPIHT) coding algorithm. The proposed transform uses the subband discrete cosine transform to decompose the image into multiresolution subbands where the discrete wavelet transform is then used to code the low frequencies. Then, we use the SPIHT coding method to code the transformed coefficients. For the SPIHT algorithm, we have proposed a method to reduce the distortion introduced by the SPIHT technique between the original and reconstructed images. The obtained results show the efficiency of the proposed hybrid method in terms of peak signal-to-noise ratio and visual quality.
R-peaks detection based on stationary wavelet transform.
Merah, M; Abdelmalik, T A; Larbi, B H
2015-10-01
Automatic detection of the QRS complexes/R-peaks in an electrocardiogram (ECG) signal is the most important step preceding any kind of ECG processing and analysis. The performance of these systems heavily relies on the accuracy of the QRS detector. The objective of present work is to drive a new robust method based on stationary wavelet transform (SWT) for R-peaks detection. The decimation of the coefficients at each level of the transformation algorithm is omitted, more samples in the coefficient sequences are available and hence a better outlier detection can be performed. Using the information of local maxima, minima and zero crossings of the fourth SWT coefficient detail, the proposed algorithm identifies the significant points for detection and delineation of the QRS complexes, as well as detection and identification of the QRS individual waves peaks of the pre-processed ECG signal. Various experimental results show that the proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, achieving excellent performance on different databases, on the MIT-BIH database (Se=99.84%, P=99.88%), on the QT Database (Se=99.94%, P=99.89%) and on MIT-BIH Noise Stress Test Database, (Se=95.30%, P=93.98%). Reliability and accuracy are close to the highest among the ones obtained in other studies. Experiments results being satisfactory, the SWT may represent a novel QRS detection tool, for a robust ECG signal analysis.
Video Coding Using 3D Dual-Tree Wavelet Transform
Directory of Open Access Journals (Sweden)
Vetro Anthony
2007-01-01
Full Text Available This work investigates the use of the 3D dual-tree discrete wavelet transform (DDWT for video coding. The 3D DDWT is an attractive video representation because it isolates image patterns with different spatial orientations and motion directions and speeds in separate subbands. However, it is an overcomplete transform with 4: 1 redundancy when only real parts are used. We apply the noise-shaping algorithm proposed by Kingsbury to reduce the number of coefficients. To code the remaining significant coefficients, we propose two video codecs. The first one applies separate 3D set partitioning in hierarchical trees (SPIHT on each subset of the DDWT coefficients (each forming a standard isotropic tree. The second codec exploits the correlation between redundant subbands, and codes the subbands jointly. Both codecs do not require motion compensation and provide better performance than the 3D SPIHT codec using the standard DWT, both objectively and subjectively. Furthermore, both codecs provide full scalability in spatial, temporal, and quality dimensions. Besides the standard isotropic decomposition, we propose an anisotropic DDWT, which extends the superiority of the normal DDWT with more directional subbands without adding to the redundancy. This anisotropic structure requires significantly fewer coefficients to represent a video after noise shaping. Finally, we also explore the benefits of combining the 3D DDWT with the standard DWT to capture a wider set of orientations.
Directory of Open Access Journals (Sweden)
D. Seidl
1999-06-01
Full Text Available Among a variety of spectrogram methods Short-Time Fourier Transform (STFT and Continuous Wavelet Transform (CWT were selected to analyse transients in non-stationary tremor signals. Depending on the properties of the tremor signal a more suitable representation of the signal is gained by CWT. Three selected broadband tremor signals from the volcanos Mt. Stromboli, Mt. Semeru and Mt. Pinatubo were analyzed using both methods. The CWT can also be used to extend the definition of coherency into a time-varying coherency spectrogram. An example is given using array data from the volcano Mt. Stromboli.
Institute of Scientific and Technical Information of China (English)
ZENG Qing-hu; QIU Jing; LIU Guan-jun
2007-01-01
Noise is the biggest obstacle that makes the incipient fault diagnosis results of roller bearings uncorrected; a new method for diagnosing incipient fault of roller bearings based on the Wavelet Transform Correlation Filter and Hilbert Transform was proposed. First, the weak fault information features are picked up from the roller bearings fault vibration signals by use of a de-noising characteristic of the Wavelet Transform Correlation Filter as the preprocessing of the Hilbert Envelope Analysis. Then, in order to get fault features frequency, de-noised wavelet coefficients of high scales which represent high frequency signal were analyzed by Hilbert Envelope Spectrum Analysis. The simulation signals and diagnosing examples analysis results reveal that the proposed method is more effective than the method of direct wavelet coefficients-Hilbert Transform in de-noising and clarifying roller bearing incipient fault.
Institute of Scientific and Technical Information of China (English)
方健; 彭辉; 李自品; 舒乃秋
2011-01-01
小波网络是近年来神经网络研究中的一个新分支,是结合小波变换理论与神经网络的思想构造的一种新的神经网络模型.笔者构造的前馈小波神经网络是将小波分析与BP神经网络融合,以Gauss小波及其伸缩平移系作为隐含层小波基函数并且对小波神经网络做了一些改进.选择了300组油中溶解气体含量作为前馈小波神经网络训练及故障识别的样本,并对仿真结果进行分析.实验结果显示:文中构造的小波神经网络适合变压器故障诊断,其性能优于改良IEC法,传统BP神经网络法和基于主成分分析法的BP神经网络.该方法已经运用在实际的变压器故障诊断项目中.%This paper constructs a feed-forward wavelet network by combining the wavelet analysis with BP neural network. The wavelet network takes Gauss wavelet and its telescopic translation system as the hidden layer of the wavelet basic function, and the wavelet neural network is improved. 300 measured content data of dissolved gas in oil are selected as the samples for training the feed-forward wavelet network and faults recognition, and the simulation results are compared and analyzed. Experimental results demonstrate that the proposed improved wavelet network adapts to transformer fault diagnosis with better performance than the IEC, BPNN and the BP neural network based on principal component analysis. This method has been used in the actual transformer fault diagnosis project.
Classification of epileptic EEG using neural network and wavelet transform
Petrosian, Arthur A.; Homan, Richard; Prokhorov, Danil; Wunsch, Donald C., II
1996-10-01
One of the major contributions of electroencephalography has been its application in the diagnosis and clinical evaluation of epilepsy. The interpretation of the EEG is achieved through visual inspection by a trained electroencephalographer. However, descriptions of rules used during the visual analysis of data are often subjective and can vary from one reader to another. Computerized methods are a means to standardize this process. In recent years, much effort has been made to develop such methods that can characterize different interictal, ictal, and postictal stages. the main issue of whether there exists a preictal phenomenon remains unresolved. In the present study we address this issue making use of specifically designed and trained recurrent neural networks in conjunction with signal wavelet decomposition technique. The purpose of this combined consideration was to demonstrate the potential for seizure prediction by up to several minutes prior to its onset.
TRANSMISSION LINE FAULT ANALYSIS USING WAVELET THEORY
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Ravindra Malkar
2012-06-01
Full Text Available This paper describes a Wavelet transform technique to analyze power system disturbance such as transmission line faults with Biorthogonal and Haar wavelets. In this work, wavelet transform based approach,which is used to detect transmission line faults, is proposed. The coefficient of discrete approximation of the dyadic wavelet transform with different wavelets are used to be an index for transmission line fault detection and faulted – phase selection and select which wavelet is suitable for this application. MATLAB/Simulation is used to generate fault signals. Simulation results reveal that the performance of the proposed fault detection indicator is promising and easy to implement for computer relaying application.
Huda, Feblil; Kajiwara, Itsuro; Hosoya, Naoki
2014-08-01
In this paper, a vibration testing and health monitoring system based on an impulse response excited by laser is proposed to detect damage in membrane structures. A high power Nd: YAG pulse laser is used to supply an ideal impulse to a membrane structure by generating shock waves via laser-induced breakdown in air. A health monitoring apparatus is developed with this vibration testing system and a damage detecting algorithm which only requires the vibration mode shape of the damaged membrane. Artificial damage is induced in membrane structure by cutting and tearing the membrane. The vibration mode shapes of the membrane structure extracted from vibration testing by using the laser-induced breakdown and laser Doppler vibrometer are then analyzed by 2-D continuous wavelet transformation. The location of damage is determined by the dominant peak of the wavelet coefficient which can be seen clearly by applying a boundary treatment and the concept of an iso-surface to the 2-D wavelet coefficient. The applicability of the present approach is verified by finite element analysis and experimental results, demonstrating the ability of the method to detect and identify the positions of damage induced on the membrane structure.
Video coding with lifted wavelet transforms and complementary motion-compensated signals
Flierl, Markus H.; Vandergheynst, Pierre; Girod, Bernd
2004-01-01
This paper investigates video coding with wavelet transforms applied in the temporal direction of a video sequence. The wavelets are implemented with the lifting scheme in order to permit motion compensation between successive pictures. We improve motion compensation in the lifting steps and utilize complementary motion-compensated signals. Similar to superimposed predictive coding with complementary signals, this approach improves compression efficiency. We investigate experimentally and theoretically complementary motion-compensated signals for lifted wavelet transforms. Experimental results with the complementary motion-compensated Haar wavelet and frame-adaptive motion compensation show improvements in coding efficiency of up to 3 dB. The theoretical results demonstrate that the lifted Haar wavelet scheme with complementary motion-compensated signals is able to approach the bound for bit-rate savings of 2 bits per sample and motion-accuracy step when compared to optimum intra-frame coding of the input pictures.
Wavelet transform to discriminate between crop and weed in agronomic images
Bossu, Jérémie; Gée, Christelle; Truchetet, Frédéric
2007-09-01
In precision agriculture, the reduction of herbicide applications requires an accurate detection of weed patches. From image detection, to quantify weed infestations, it would be necessary to identify crop rows from line detection algorithm and to discriminate weed from crop. Our laboratory developed several methods for line detection based on Hough Transform, double Hough Transform or Gabor filtering. The Hough Transform is well adapted to image affected by perspective deformations but the computation burden is heavy and on-line applications are hardly handled. To lighten this problem, we have used a Gabor filter to enhance the crop rows present into the image but, if this method is robust with parallel crop rows (without perspective distortions), it implies to deform image with an inverse projection matrix to be applied in the case of an embedded camera. We propose, in order to implement a filter in the scale / space domain, to use a discrete dyadic wavelet transform. Thus, we can extract the vertical details contained in various parts of the image from different levels of resolution. Each vertical detail level kept allows to enhance the crop rows in a specific part of the initial image. The combination of these details enable us to discriminate crop from weeds with a simple logical operation. This spatial method, thanks to the fast wavelet transform algorithm, can be easily implemented for a real time application and it leads to better results than those obtained from Gabor filtering. For this method, the weed infestation rate is estimated and the performance are compared to those given by other methods. A discussion concludes about the ability of this method to detect the crop rows in agronomic images. Finally we consider the ability of this spatial-only approach to classify weeds from crop.
Reversible Integer Wavelet Transform for the Joint of Image Encryption and Watermarking
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Bin Wang
2015-01-01
Full Text Available In recent years, signal processing in the encrypted domain has attracted considerable research interest, especially embedding watermarking in encrypted image. In this work, a novel joint of image encryption and watermarking based on reversible integer wavelet transform is proposed. Firstly, the plain-image is encrypted by chaotic maps and reversible integer wavelet transform. Then the lossless watermarking is embedded in the encrypted image by reversible integer wavelet transform and histogram modification. Finally an encrypted image containing watermarking is obtained by the inverse integer wavelet transform. What is more, the original image and watermarking can be completely recovered by inverse process. Numerical experimental results and comparing with previous works show that the proposed scheme possesses higher security and embedding capacity than previous works. It is suitable for protecting the image information.
Image denoising algorithm of refuge chamber by combining wavelet transform and bilateral filtering
Institute of Scientific and Technical Information of China (English)
Zhang Weipeng
2013-01-01
In order to preferably identify infrared image of refuge chamber,reduce image noises of refuge chamber and retain more image details,we propose the method of combining two-dimensional discrete wavelet transform and bilateral denoising.First,the wavelet transform is adopted to decompose the image of refuge chamber,of which low frequency component remains unchanged.Then,three high-frequency components are treated by bilateral filtering,and the image is reconstructed.The result shows that the combination of bilateral filtering and wavelet transform for image denoising can better retain the details which are included in the image,while providing better visual effect.This is superior to using either bilateral filtering or wavelet transform alone.It is useful for perfecting emergency refuge system of coal.
Sarrafi, Aral; Mao, Zhu
2016-04-01
In the application of Structural Health Monitoring (SHM), processing the online-acquired data plays a very important role, among which wavelet transform is an outstanding tool and compared to Fourier transform, it handles the nonstationary behaviors in the time series in an adaptive fashion. When dealing with time-variant data, there are uncertainties from numerous resources inherent to the feature estimation, such as measurement noise, operational and environmental variability, hardware limitation, etc. The corruption from uncertainty will make the data interpretation ambiguous and thereby dramatically degrades the decision quality with regard to the occurrence, location, severity, and extent of damages. This paper derives a probabilistic model to quantify analytically the uncertainty of wavelet transform feature as a random variable, and variance is derived analytically in this work. Considering central limit theorem, Gaussian probability density function characterizes the distribution and this has been validated via Monte Carlo testing. By fully characterizing the uncertainty, the damage detection implementations may be facilitated with a quantified false alarm rate and miss catch rate.
Feature Extraction Using Discrete Wavelet Transform for Gear Fault Diagnosis of Wind Turbine Gearbox
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Rusmir Bajric
2016-01-01
Full Text Available Vibration diagnosis is one of the most common techniques in condition evaluation of wind turbine equipped with gearbox. On the other side, gearbox is one of the key components of wind turbine drivetrain. Due to the stochastic operation of wind turbines, the gearbox shaft rotating speed changes with high percentage, which limits the application of traditional vibration signal processing techniques, such as fast Fourier transform. This paper investigates a new approach for wind turbine high speed shaft gear fault diagnosis using discrete wavelet transform and time synchronous averaging. First, the vibration signals are decomposed into a series of subbands signals with the use of a multiresolution analytical property of the discrete wavelet transform. Then, 22 condition indicators are extracted from the TSA signal, residual signal, and difference signal. Through the case study analysis, a new approach reveals the most relevant condition indicators based on vibrations that can be used for high speed shaft gear spalling fault diagnosis and their tracking abilities for fault degradation progression. It is also shown that the proposed approach enhances the gearbox fault diagnosis ability in wind turbines. The approach presented in this paper was programmed in Matlab environment using data acquired on a 2 MW wind turbine.
Methods of compression of digital holograms, based on 1-level wavelet transform
Kurbatova, E. A.; Cheremkhin, P. A.; Evtikhiev, N. N.
2016-08-01
To reduce the size of memory required for storing information about 3D-scenes and to decrease the rate of hologram transmission, digital hologram compression can be used. Compression of digital holograms by wavelet transforms is among most powerful methods. In the paper the most popular wavelet transforms are considered and applied to the digital hologram compression. Obtained values of reconstruction quality and hologram's diffraction efficiencies are compared.
Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models
Energy Technology Data Exchange (ETDEWEB)
Tan, Zhongfu; Zhang, Jinliang; Xu, Jun [North China Electric Power University, Beijing 102206 (China); Wang, Jianhui [Argonne National Laboratory, Argonne, IL 60439 (United States)
2010-11-15
This paper proposes a novel price forecasting method based on wavelet transform combined with ARIMA and GARCH models. By wavelet transform, the historical price series is decomposed and reconstructed into one approximation series and some detail series. Then each subseries can be separately predicted by a suitable time series model. The final forecast is obtained by composing the forecasted results of each subseries. This proposed method is examined on Spanish and PJM electricity markets and compared with some other forecasting methods. (author)
Image Compression Using Wavelet Transform Based on the Lifting Scheme and its Implementation
Directory of Open Access Journals (Sweden)
A Alice Blessie
2011-05-01
Full Text Available This paper presents image compression using 9/7 wavelet transform based on the lifting scheme. This is simulated using ISE simulator and implemented in FPGA. The 9/7 wavelet transform performs well for the low frequency components. Implementation in FPGA is since because of its partial reconfiguration. The project mainly aims at retrieving the smooth images without any loss. This design may be used for both lossy and lossless compression.
Shape-adaptive discrete wavelet transform for coding arbitrarily shaped texture
Li, Shipeng; Li, Weiping
1997-01-01
This paper presents a shape adaptive discrete wavelet transform (SA-DWT) scheme for coding arbitrarily shaped texture. The proposed SA-DWT can be used for object-oriented image coding. The number of coefficients after SA-DWT is identical to the number of pels contained in the arbitrarily shaped image objects. The locality property of wavelet transform and self-similarity among subbands are well preserved throughout this process.For a rectangular region, the SA-DWT is identical to a standard wavelet transform. With SA-DWT, conventional wavelet based coding schemes can be readily extended to the coding of arbitrarily shaped objects. The proposed shape adaptive wavelet transform is not unitary but the small energy increase is restricted at the boundary of objects in subbands. Two approaches of using the SA-DWT algorithm for object-oriented image and video coding are presented. One is to combine scalar SA-DWT with embedded zerotree wavelet (EZW) coding technique, the other is an extension of the normal vector wavelet coding (VWC) technique to arbitrarily shaped objects. Results of applying SA-VWC to real arbitrarily shaped texture coding are also given at the end of this paper.
Single Channel Speech Enhancement by De-noising Using Stationary Wavelet Transform
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A method of single channel speech enhancement is proposed by de-noising using stationary wavelet transform. The approach developed herein processes multi-resolution wavelet coefficients individually and then recovery signal is reconstructed. The time invariant characteristics of stationary wavelet transform is particularly useful in speech de-noising. Experimental results show that the proposed speech enhancement by de-noising algorithm is possible to achieve an excellent balance between suppresses noise effectively and preserves as many target characteristics of original signal as possible. This de-noising algorithm offers a superior performance to speech signal noise suppress.
Identification of diesel front sound source based on continuous wavelet transform
Institute of Scientific and Technical Information of China (English)
郝志勇; 韩军
2004-01-01
Acoustic signals from diesel engines contain useful information but also include considerable noise components.To extract information for condition monitoring purposes, continuous wavelet transform (CWT) is used for the characterization of engine acoustics. This paper first reviews CWT characteristics represented by short duration transient signals.Wavelet selection and CWT are then implemented and wavelet transform is used to analyze the major sources of the engine front's exterior radiation sound. The research provides a reliable basis for engineering practice to reduce vehicle sound level.Comparison of the identification results of the measured acoustic signals with the identification results of the measured surface vibration showed good agreement.
Identification of diesel front sound source based on continuous wavelet transform
Institute of Scientific and Technical Information of China (English)
郝志勇; 韩军
2004-01-01
Acoustic signals from diesel engines contain useful information but also include considerable noise components To extract information for condition monitoring purposes, continuous wavelet transform (CWT) is used for the characterization of engine acoustics. This paper first reviews CWT characteristics represented by short duration transient signals. Wavelet selection and CWT are then implemented and wavelet transform is used to analyze the major sources of the engine front's exterior radiation sound. The research provides a reliable basis for engineering practice to reduce vehicle sound level. Comparison of the identification results of the measured acoustic signals with the identification results of the measured surface vibration showed good agreement.
Audio watermarking based on psychoacoustic model and critical band wavelet transform
Institute of Scientific and Technical Information of China (English)
TAO Zhi; ZHAO Heming; GU Jihua; WU Di
2007-01-01
Watermark embedding algorithm based on critical band wavelet transform of digital audio signal is proposed in this paper. The masking threshold for each audio signal segment was calculated on the basic of psychoacoustic model. According to the similarity between critical band of human auditory system and critical band wavelet transform, a watermark was embedded into the low-band and mid-band coefficients of digital wavelet. The embedding strength was adaptively controlled by the masking threshold. The experiment results show that the embedded watermark signal is inaudible, and the watermarked audio signal has good robustness against many attacks such as compression, noise, re-sampling, low-pass filtering.
A method of image compression based on lifting wavelet transform and modified SPIHT
Lv, Shiliang; Wang, Xiaoqian; Liu, Jinguo
2016-11-01
In order to improve the efficiency of remote sensing image data storage and transmission we present a method of the image compression based on lifting scheme and modified SPIHT(set partitioning in hierarchical trees) by the design of FPGA program, which realized to improve SPIHT and enhance the wavelet transform image compression. The lifting Discrete Wavelet Transform (DWT) architecture has been selected for exploiting the correlation among the image pixels. In addition, we provide a study on what storage elements are required for the wavelet coefficients. We present lena's image using the 3/5 lifting scheme.
Directory of Open Access Journals (Sweden)
M. Rasoulpoor
2013-09-01
Full Text Available This paper presents a new approach for power transformer differential protection. The Wavelet Transform is applied to discriminate between inrush currents and internal fault currents in power transformers. Discrete wavelet transform decomposes the current signal into sub-bands that give more information about the properties of the signals in different frequency bands. Also, this transform is used to investigate the energy distribution of the signal on the different time and frequency scales. Recognition method is based on the correlation factors between energy percentage vectors of the Wavelet coefficients. Discrete Wavelet transform is used for decomposing the current signals to different frequency coefficients. After that, by constituting the energy percentage vectors of wavelet transform coefficients and calculating the correlation factors between these vectors, it is possible to form a recognition criterion to distinguish between inrush and internal fault current in the proposed method. The proposed algorithm is tested for several conditions by simulated inrush and internal fault currents. Simulation of current signals is performed using electromagnetic transient program PSCAD/EMTDC software that is a powerful program for the investigation of transient signals. Simulation results show that the proposed scheme accurately identifies inrush and fault currents in the distance of the power transformer protection in less than quarter of power frequency cycle. Also, beside the sensitivity and high reliability, the proposed method has low computation content and unlike the common methods does not require to determine the threshold for each new power system.
2007-11-02
be approved in the near future. The main features of JPEG2000 are use of wavelet transform and ROI (Region of Interest) method. It is expected that... wavelet transform is more effective than Fourier transform for ultrasonic echo signal/image processing. Furthermore, ROI method seems to be appropriate...compression method of medical images. The purpose of this paper is to investigate the effectiveness of wavelet transform compared with DCT (JPEG) and
小波变换与PAR方法在负荷短期预测中的应用%Application of Wavelet Transform and PAR in Load Short-term Forecasting
Institute of Scientific and Technical Information of China (English)
于帆; 董敏
2011-01-01
小波变换具有很多良好的性质,它能任意提取负荷序列的细节.针对负荷序列以天、周、年为周期的变化特点,引用小波变换算法对负荷进行了不同频段上的分解,然后利用能够准确描述数据周期性变化的PAR模型对负荷进行短期预测,建立了基于小波变换的PAR模型.实验证明,这种预测方法非常有效.%Wavelet transform has many advantages, and it can extract any details of load sequence. In according to the characteristics of Load sequences changes by the period of days, weeks, years, using wavelet transform algorithm on the decomposition of different frequency ranges, and then established the PAR model based on the wavelet transform which can describe the changes of data periodicity accurately, to forecast the load in a short time. Experiments show that this prediction method is very effective.
WAVELET TRANSFORM ANALYSIS OF ELECTROMYOGRAPHY KUNG FU STRIKES DATA
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Ana Carolina de Miranda Marzullo
2009-11-01
Full Text Available In martial arts and contact sports strikes are performed at near maximum speeds. For that reason, electromyography (EMG analysis of such movements is non-trivial. This paper has three main goals: firstly, to investigate the differences in the EMG activity of muscles during strikes performed with and without impacts; secondly, to assess the advantages of using Sum of Significant Power (SSP values instead of root mean square (rms values when analyzing EMG data; and lastly to introduce a new method of calculating median frequency values using wavelet transforms (WMDF. EMG data of the deltoid anterior (DA, triceps brachii (TB and brachioradialis (BR muscles were collected from eight Kung Fu practitioners during strikes performed with and without impacts. SSP results indicated significant higher muscle activity (p = 0.023 for the strikes with impact. WMDF results, on the other hand, indicated significant lower values (p = 0. 007 for the strikes with impact. SSP results presented higher sensitivity than rms to quantify important signal differences and, at the same time, presented lower inter-subject coefficient of variations. The result of increase in SSP values and decrease in WMDF may suggest better synchronization of motor units for the strikes with impact performed by the experienced Kung Fu practitioners
Real time continuous wavelet transform implementation on a DSP processor.
Patil, S; Abel, E W
2009-01-01
The continuous wavelet transform (CWT) is an effective tool when the emphasis is on the analysis of non-stationary signals and on localization and characterization of singularities in signals. We have used the B-spline based CWT, the Lipschitz Exponent (LE) and measures derived from it to detect and quantify the singularity characteristics of biomedical signals. In this article, a real-time implementation of a B-spline based CWT on a digital signal processor is presented, with the aim of providing quantitative information about the signal to a clinician as it is being recorded. A recursive algorithm implementation was shown to be too slow for real-time implementation so a parallel algorithm was considered. The use of a parallel algorithm involves redundancy in calculations at the boundary points. An optimization of numerical computation to remove redundancy in calculation was carried out. A formula has been derived to give an exact operation count for any integer scale m and any B-spline of order n (for the case where n is odd) to calculate the CWT for both the original and the optimized parallel methods. Experimental results show that the optimized method is 20-28% faster than the original method. As an example of applying this optimized method, a real-time implementation of the CWT with LE postprocessing has been achieved for an EMG Interference Pattern signal sampled at 50 kHz.
Adaptive lifting scheme of wavelet transforms for image compression
Wu, Yu; Wang, Guoyin; Nie, Neng
2001-03-01
Aiming at the demand of adaptive wavelet transforms via lifting, a three-stage lifting scheme (predict-update-adapt) is proposed according to common two-stage lifting scheme (predict-update) in this paper. The second stage is updating stage. The third is adaptive predicting stage. Our scheme is an update-then-predict scheme that can detect jumps in image from the updated data and it needs not any more additional information. The first stage is the key in our scheme. It is the interim of updating. Its coefficient can be adjusted to adapt to data to achieve a better result. In the adaptive predicting stage, we use symmetric prediction filters in the smooth area of image, while asymmetric prediction filters at the edge of jumps to reduce predicting errors. We design these filters using spatial method directly. The inherent relationships between the coefficients of the first stage and the other stages are found and presented by equations. Thus, the design result is a class of filters with coefficient that are no longer invariant. Simulation result of image coding with our scheme is good.
Baseline correction of intraoperative electromyography using discrete wavelet transform.
Rampp, Stefan; Prell, Julian; Thielemann, Henning; Posch, Stefan; Strauss, Christian; Romstöck, Johann
2007-08-01
In intraoperative analysis of electromygraphic signals (EMG) for monitoring purposes, baseline artefacts frequently pose considerable problems. Since artefact sources in the operating room can only be reduced to a limited degree, signal-processing methods are needed to correct the registered data online without major changes to the relevant data itself. We describe a method for baseline correction based on "discrete wavelet transform" (DWT) and evaluate its performance compared to commonly used digital filters. EMG data from 10 patients who underwent removal of acoustic neuromas were processed. Effectiveness, preservation of relevant EMG patterns and processing speed of a DWT based correction method was assessed and compared to a range of commonly used Butterworth, Resistor-Capacitor and Gaussian filters. Butterworth and DWT filters showed better performance regarding artefact correction and pattern preservation compared to Resistor-Capacitor and Gaussian filters. Assuming equal weighting of both characteristics, DWT outperformed the other methods: While Butterworth, Resistor-Capacitor and Gaussian provided good pattern preservation, the effectiveness was low and vice versa, while DWT baseline correction at level 6 performed well in both characteristics. The DWT method allows reliable and efficient intraoperative baseline correction in real-time. It is superior to commonly used methods and may be crucial for intraoperative analysis of EMG data, for example for intraoperative assessment of facial nerve function.
Wavelet entropy of BOLD time series: An application to Rolandic epilepsy.
Gupta, Lalit; Jansen, Jacobus F A; Hofman, Paul A M; Besseling, René M H; de Louw, Anton J A; Aldenkamp, Albert P; Backes, Walter H
2017-03-11
To assess the wavelet entropy for the characterization of intrinsic aberrant temporal irregularities in the time series of resting-state blood-oxygen-level-dependent (BOLD) signal fluctuations. Further, to evaluate the temporal irregularities (disorder/order) on a voxel-by-voxel basis in the brains of children with Rolandic epilepsy. The BOLD time series was decomposed using the discrete wavelet transform and the wavelet entropy was calculated. Using a model time series consisting of multiple harmonics and nonstationary components, the wavelet entropy was compared with Shannon and spectral (Fourier-based) entropy. As an application, the wavelet entropy in 22 children with Rolandic epilepsy was compared to 22 age-matched healthy controls. The images were obtained by performing resting-state functional magnetic resonance imaging (fMRI) using a 3T system, an 8-element receive-only head coil, and an echo planar imaging pulse sequence ( T2*-weighted). The wavelet entropy was also compared to spectral entropy, regional homogeneity, and Shannon entropy. Wavelet entropy was found to identify the nonstationary components of the model time series. In Rolandic epilepsy patients, a significantly elevated wavelet entropy was observed relative to controls for the whole cerebrum (P = 0.03). Spectral entropy (P = 0.41), regional homogeneity (P = 0.52), and Shannon entropy (P = 0.32) did not reveal significant differences. The wavelet entropy measure appeared more sensitive to detect abnormalities in cerebral fluctuations represented by nonstationary effects in the BOLD time series than more conventional measures. This effect was observed in the model time series as well as in Rolandic epilepsy. These observations suggest that the brains of children with Rolandic epilepsy exhibit stronger nonstationary temporal signal fluctuations than controls. 2 J. Magn. Reson. Imaging 2017. © 2017 International Society for Magnetic Resonance in Medicine.
Multi-image gradient-based algorithms for motion measurement using wavelet transform
Institute of Scientific and Technical Information of China (English)
2008-01-01
A multi-image wavelet transform motion estimation algorithm based on gradient methods is presented by using the characteristic of wavelet transfom.In this algorithm,the accuracy can be improved greatly using data in many images to measure motions between two images.In combination with the reliability measure for constraints function,the reliable data constraints of the images were decomposed with multi-level simultaneous wavelet transform rather than the traditional coarse-to-fine approach.Compared with conventional methods,this motion measurement algorithm based on multi-level simultaneous wavelet transform avoids propagating errors between the decomposed levels.Experimental simulations show that the implementation of this algo rithm is simple,and the measurement accuracy is improved.
Dual tree complex wavelet transform based denoising of optical microscopy images.
Bal, Ufuk
2012-12-01
Photon shot noise is the main noise source of optical microscopy images and can be modeled by a Poisson process. Several discrete wavelet transform based methods have been proposed in the literature for denoising images corrupted by Poisson noise. However, the discrete wavelet transform (DWT) has disadvantages such as shift variance, aliasing, and lack of directional selectivity. To overcome these problems, a dual tree complex wavelet transform is used in our proposed denoising algorithm. Our denoising algorithm is based on the assumption that for the Poisson noise case threshold values for wavelet coefficients can be estimated from the approximation coefficients. Our proposed method was compared with one of the state of the art denoising algorithms. Better results were obtained by using the proposed algorithm in terms of image quality metrics. Furthermore, the contrast enhancement effect of the proposed method on collagen fıber images is examined. Our method allows fast and efficient enhancement of images obtained under low light intensity conditions.
Directory of Open Access Journals (Sweden)
Lina Yang
2014-01-01
Full Text Available To reduce the computation complexity of wavelet transform, this paper presents a novel approach to be implemented. It consists of two key techniques: (1 fast number theoretic transform(FNTT In the FNTT, linear convolution is replaced by the circular one. It can speed up the computation of 2D discrete wavelet transform. (2 In two-dimensional overlap-save method directly calculating the FNTT to the whole input sequence may meet two difficulties; namely, a big modulo obstructs the effective implementation of the FNTT and a long input sequence slows the computation of the FNTT down. To fight with such deficiencies, a new technique which is referred to as 2D overlap-save method is developed. Experiments have been conducted. The fast number theoretic transform and 2D overlap-method have been used to implement the dyadic wavelet transform and applied to contour extraction in pattern recognition.
Liao, Ke; Zhu, Min; Ding, Lei
2013-08-01
The present study investigated the use of transform sparseness of cortical current density on human brain surface to improve electroencephalography/magnetoencephalography (EEG/MEG) inverse solutions. Transform sparseness was assessed by evaluating compressibility of cortical current densities in transform domains. To do that, a structure compression method from computer graphics was first adopted to compress cortical surface structure, either regular or irregular, into hierarchical multi-resolution meshes. Then, a new face-based wavelet method based on generated multi-resolution meshes was proposed to compress current density functions defined on cortical surfaces. Twelve cortical surface models were built by three EEG/MEG softwares and their structural compressibility was evaluated and compared by the proposed method. Monte Carlo simulations were implemented to evaluate the performance of the proposed wavelet method in compressing various cortical current density distributions as compared to other two available vertex-based wavelet methods. The present results indicate that the face-based wavelet method can achieve higher transform sparseness than vertex-based wavelet methods. Furthermore, basis functions from the face-based wavelet method have lower coherence against typical EEG and MEG measurement systems than vertex-based wavelet methods. Both high transform sparseness and low coherent measurements suggest that the proposed face-based wavelet method can improve the performance of L1-norm regularized EEG/MEG inverse solutions, which was further demonstrated in simulations and experimental setups using MEG data. Thus, this new transform on complicated cortical structure is promising to significantly advance EEG/MEG inverse source imaging technologies.
Super-resolution image restoration algorithms based on orthogonal discrete wavelet transform
Liu, Yang-yang; Jin, Wei-qi
2005-02-01
Several new super-resolution image restoration algorithms based on orthogonal discrete wavelet transform are proposed, by using orthogonal discrete wavelet transform and generalized cross validation ,and combining with Luck-Richardson super-resolution image restoration algorithm (LR) and Luck-Richardson algorithm based on Poisson-Markov model (MPML). Orthogonal discrete wavelet transform analyzed in both space and frequency domain has the capability of indicating local features of a signal, and concentrating the signal power to a few coefficients in wavelet transform domain. After an original image is "Symlets" orthogonal discrete wavelet transformed, an asymptotically optimal threshold is determined by minimizing generalized cross validation, and high frequency subbands in each decomposition level are denoised with soft threshold processes to converge respectively to those with maximum signal-noise-ratio, when the method is incorporated with existed super-resolution image algorithms, details of original image, especially of those with low signal-noise-ratio, could be well recovered. Single operation wavelet LR algorithm(SWLR),single operation wavelet MPML algorithm(SW-MPML) and MPML algorithm based on single operation and wavelet transform (MPML- SW) are some operative algorithms proposed based on the method. According to the processing results to simulating and practical images , because of the only one operation, under the guarantee of rapid and effective restoration processing, in comparison with LR and MPML, all the proposed algorithms could retain image details better, and be more suitable to low signal-noise-ratio images, They could also reduce operation time for up to hundreds times of iteratives, as well as, avoid the iterative operation of self-adaptive parameters in MPML, improve operating speed and precision. They are practical and instantaneous to some extent in the field of low signal-noise-ratio image restoration.
Wavelet analysis for ground penetrating radar applications: a case study
Javadi, Mehdi; Ghasemzadeh, Hasan
2017-10-01
Noises may significantly disturb ground penetrating radar (GPR) signals, therefore, filtering undesired information using wavelet analysis would be challenging, despite the fact that several methods have been presented. Noises are gathered by probe, particularly from deep locations, and they may conceal reflections, suffering from small altitudes, because of signal attenuation. Multiple engineering fields need data analysis to distinguish valued material, based on information obtained by underground observations. Using wavelets as one of the useful methods for analyzing data is considered in this paper. However, optimal wavelet analysis would be challenging in the realm of exploring GPR signals. There is no doubt that accounting for wavelet function, decomposition level, threshold estimation method and threshold transformation, in the matter of de-noising and investigating signals, is of great importance; they must be chosen with judgment as they influence the results enormously if they are not carefully designated. Multiple wavelet functions are applied to perform de-noising and reconstruction on synthetic noisy signals generated by the finite-difference time-domain (FDTD) method to account for the most appropriate function for the purpose. In addition, various possible decomposition levels, threshold estimation methods and threshold transformations in the de-noising procedure are tested. The optimal wavelet analysis is also evaluated by examining real data acquired from several antenna frequencies which are common in engineering practice.
Multispectral image sharpening using wavelet transform techniques and spatial correlation of edges
Lemeshewsky, George P.; Schowengerdt, Robert A.
2000-01-01
Several reported image fusion or sharpening techniques are based on the discrete wavelet transform (DWT). The technique described here uses a pixel-based maximum selection rule to combine respective transform coefficients of lower spatial resolution near-infrared (NIR) and higher spatial resolution panchromatic (pan) imagery to produce a sharpened NIR image. Sharpening assumes a radiometric correlation between the spectral band images. However, there can be poor correlation, including edge contrast reversals (e.g., at soil-vegetation boundaries), between the fused images and, consequently, degraded performance. To improve sharpening, a local area-based correlation technique originally reported for edge comparison with image pyramid fusion is modified for application with the DWT process. Further improvements are obtained by using redundant, shift-invariant implementation of the DWT. Example images demonstrate the improvements in NIR image sharpening with higher resolution pan imagery.
Energy Technology Data Exchange (ETDEWEB)
Matsushima, J.; Rokugawa, S.; Kato, Y. [The University of Tokyo, Tokyo (Japan). Faculty of Engineering; Yokota, T.; Miyazaki, T. [Geological Survey of Japan, Tsukuba (Japan); Ichie, Y. [The University of Tokyo, Tokyo (Japan)
1996-10-01
Data processing techniques have been investigated for clarifying structures and physical properties of geothermal reservoirs in the deep underground by seismic exploration using multiple wells. They include the initial motion time-distance tomography, amplitude tomography, diffracted wave tomography, and structure imaging using reflected wave or scattered wave. When applying these data processing methods to observed records, weak and minor signals essentially required are canceled due to averaging the analytical fields. In this study, influence of inhomogeneous media on the wavefield was evaluated. Data were analyzed considering frequency by using wavelet transform by which time-frequency can be easily analyzed. From the time-frequency analysis using wavelet transform, it was illustrated that high frequency scattered waves, generated by scatterer like cracks or by irregularity on the reflection surface, arrive behind direct P-wave and direct S-wave. 5 refs., 8 figs.
Seismic signal analysis based on the dual-tree complex wavelet packet transform
Institute of Scientific and Technical Information of China (English)
谢周敏; 王恩福; 张国宏; 赵国存; 陈旭庚
2004-01-01
We tried to apply the dual-tree complex wavelet packet transform in seismic signal analysis. The complex waveletpacket transform (CWPT) combine the merits of real wavelet packet transform with that of complex continuouswavelet transform (CCWT). It can not only pick up the phase information of signal, but also produce better "focalizing" function if it matches the phase spectrum of signals analyzed. We here described the dual-tree CWPT algorithm, and gave the examples of simulation and actual seismic signals analysis. As shown by our results, thedual-tree CWPT is a very efecfive method in analyzing seismic signals with non-linear phase.
The WaveD Transform in R: Performs Fast Translation-Invariant Wavelet Deconvolution
Directory of Open Access Journals (Sweden)
Marc Raimondo
2007-04-01
Full Text Available This paper provides an introduction to a software package called waved making available all code necessary for reproducing the figures in the recently published articles on the WaveD transform for wavelet deconvolution of noisy signals. The forward WaveD transforms and their inverses can be computed using any wavelet from the Meyer family. The WaveD coefficients can be depicted according to time and resolution in several ways for data analysis. The algorithm which implements the translation invariant WaveD transform takes full advantage of the fast Fourier transform (FFT and runs in O(n(log n2
Lossless Image Compression Using A Simplified MED Algorithm with Integer Wavelet Transform
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Mohamed M. Fouad
2013-11-01
Full Text Available In this paper, we propose a lossless (LS image compression technique combining a prediction step with the integer wavelet transform. The prediction step proposed in this technique is a simplified version of the median edge detector algorithm used with JPEG-LS. First, the image is transformed using the prediction step and a difference image is obtained. The difference image goes through an integer wavelet transform and the transform coefficients are used in the lossless codeword assignment. The algorithm is simple and test results show that it yields higher compression ratios than competing techniques. Computational cost is also kept close to competing techniques.
Video Denoising based on Stationary Wavelet Transform and Center Weighted Median Filter
Directory of Open Access Journals (Sweden)
Soundarya K
2014-01-01
Full Text Available Noise removal using wavelet has the characteristic of preserving signal uniqueness even if noise is going to be minimized. Images are getting corrupted by impulse noise during image acquisition and transmission. A new median filter termed as the center weighted median filter (CWMF in the wavelet coefficient domain combined with stationary wavelet transform (SWT is proposed for video denoising. This filter iteratively smoothes the noisy wavelet coefficients variances preserving the edge information contained in the large magnitude wavelet coefficients. This Paper deals with uncompressed video of .avi format. The proposed algorithm works well for suppressing Gaussian noise with noise density from 10 to 70% while preserving image details. Simulation results show that higher peak signal to noise ratio can be obtained as compared to other recent image denoising methods.
Application of fractal-wavelet analysis for separation of geochemical anomalies
Afzal, Peyman; Ahmadi, Kamyar; Rahbar, Kambiz
2017-04-01
The purpose of this paper is separation and detection of different geochemical populations and anomalies from background utilizing fractal-wavelet analysis. Daubechies2 and Morlet wavelets were used for transformation of the Cu estimated data to spatial frequency based on lithogeochemical data in Bardaskan area (SE Iran) by a MATLAB code. Wavelet is a significant tool for transformation of exploratory data because the noise data are removed from results and also, accuracy for determination of thresholds can be higher than other conventional methods. The Cu threshold values for extremely, highly and moderately anomalies are 1.4%, 0.66% and 0.4%, respectively, according to the fractal-wavelet analysis based on the Daubichies2 transformation. Moreover, the fractal-wavelet analysis by the Morlet wavelet shows that the Cu threshold values are 2%, 0.75% and 0.46% for extremely, highly and moderately anomalies and populations, respectively. The results obtained by the both WT methods indicate that the main Cu enriched anomalies and populations were situated in the central parts of the Bardaskan district which are associated with surface mineralization and ancient mining digs. Furthermore, results derived via the Morlet WT is better than Daubichies2 WT according to the correlation with geological characteristics by logratio matrix. The results obtained by the fractal-wavelet method have a good correlation with geological particulars including alteration zones and surface Cu mineralization which reveals the proposed technique is an applicable approach for identification of various geochemical anomalies and zones from background. However, the main targets for detailed exploration is located in the central part of the studied area.
Institute of Scientific and Technical Information of China (English)
姜海燕; 杜民
2011-01-01
采用小波变换软阈值法有效去除试条图像噪声,根据小波分解后的系数重构图形定位GICA的光谱信号突变点的位置,提取试条光谱特性曲线的特征参量.采用BP神经网络对特征参量与浓度之间的多变量非线性函数关系进行建模,HCG试条测定结果表明,该测定方法相对误差符合要求,适用于GICA的定量测定.%This thesis uses wavelet soft- threshold denoising to preprocess the strip image. According to the analysis of maximum module of wavelet transform coefficients and their orientation in different scales, the breaking points of signals could be determined accurately by the wavelet transform and the useful characteristic parameters were extracted. By the training for the back -propagation neural network, the multivariables nonlinearity relationship between the HCG concentration and characteristic parameters is established, the result shows that HCG relative error can be decreased effectively by this method; it can be a good method for quantitative test of the gold immunochromatographic strip.
A Fast Feature Extraction Method Based on Integer Wavelet Transform for Hyperspectral Images
Institute of Scientific and Technical Information of China (English)
GUYanfeng; ZHANGYe; YUShanshan
2004-01-01
Hyperspectral remote sensing provides high-resolution spectral data and the potential for remote discrimination between subtle differences in ground covers. However, the high-dimensional data space generated by the hyperspectral sensors creates a new challenge for conventional spectral data analysis techniques. A challenging problem in using hyperspectral data is to eliminate redundancy and preserve useful spectral information for applications. In this paper, a Fast feature extraction (FFE) method based on integer wavelet transform is proposed to extract useful features and reduce dimensionality of hyperspectral images. The FFE method can be directly used to extract useful features from spectral vector of each pixel resident in the hyperspectral images. The FFE method has two main merits: high computational efficiency and good ability to extract spectral features. In order to better testify the effectiveness and the performance of the proposed method, classification experiments of hyperspectral images are performed on two groups of AVIRIS (Airborne visible/infrared imaging spectrometer) data respectively. In addition, three existing methods for feature extraction of hyperspectral images, i.e. PCA, SPCT and Wavelet Transform, are performed on the same data for comparison with the proposed method. The experimental investigation shows that the efficiency of the FFE method for feature extraction outclasses those of the other three methods mentioned above.
Kim, Jay; Welcome, Daniel E.; Dong, Ren G.; Joon Song, Won; Hayden, Charles
2007-11-01
Current guidelines to assess health risk of hand-arm vibration are based on the frequency-weighted rms acceleration level, therefore do not fully consider the effect of temporal variations of the spectral energy. Time averaging effect involved with the frequency analysis may severely underestimate the risk of impact tools. A time-frequency ( T- F) analysis is necessary to characterize a highly transient signal whose spectral characteristics change rapidly in time. The analytic wavelet transform (AWT) is an ideal T- F analysis tool as it possesses the advantages of both the Fourier and wavelet transforms. The AWT is applied to acceleration signals measured from six tools, five impact type tools and one relatively steady-type tool, to explore possible improvements of the current risk assessment method of hand-arm vibration exposure. Based on the unique capability of the AWT, several new concepts including frequency-weighted time history, cumulative injury function, and cumulative injury index are defined in this study. Possible applications of these new concepts to hand-arm vibration research are described. Based on the results from this study, needs for future research are discussed.
Application of wavelet analysis to crustal deformation data processing
Institute of Scientific and Technical Information of China (English)
张燕; 吴云; 刘永启; 施顺英
2004-01-01
The time-frequency analysis and anomaly detection of wavelet transformation make the method irresistibly advantageous in non-stable signal processing. In the paper, the two characteristics are analyzed and demonstrated withsynthetic signal. By applying wavelet transformation to deformation data processing, we find that about 4 monthsbefore strong earthquakes, several deformation stations near the epicenter received at the same time the abnormalsignal with the same frequency and the period from several days to more than ten days. The GPS observation stations near the epicenter all received the abnormal signal whose period is from 3 months to half a year. These abnormal signals are possibly earthquake precursors.
Impulse-noise suppression in speech using the stationary wavelet transform.
Nongpiur, R C; Shpak, D J
2013-02-01
An approach for detecting and removing impulse noise from speech using the wavelet transform is proposed. The approach utilizes the multi-resolution property of the wavelet transform, which provides finer time resolution at higher frequencies than the short-time Fourier transform to effectively identify and remove impulse noise. The paper then describes how the impulse-detection performance is dependent on certain wavelet features and their relationships with the impulse noise and the underlying speech signal. Performance comparisons carried out with an existing method show that the wavelet approach yields much better features for detecting the impulses. To remove the impulses, an algorithm that uses the stationary wavelet transform has been developed. The algorithm uses a two-step approach where the wavelet coefficients corresponding to the impulses are suppressed in the first step and then substituted by suitable coefficients located within the vicinity of the impulse in the second step. Performance evaluations with an existing method show that the proposed algorithm gives superior results.
Directory of Open Access Journals (Sweden)
Jikai Chen
2016-12-01
Full Text Available In a power system, the analysis of transient signals is the theoretical basis of fault diagnosis and transient protection theory. Shannon wavelet entropy (SWE and Shannon wavelet packet entropy (SWPE are powerful mathematics tools for transient signal analysis. Combined with the recent achievements regarding SWE and SWPE, their applications are summarized in feature extraction of transient signals and transient fault recognition. For wavelet aliasing at adjacent scale of wavelet decomposition, the impact of wavelet aliasing is analyzed for feature extraction accuracy of SWE and SWPE, and their differences are compared. Meanwhile, the analyses mentioned are verified by partial discharge (PD feature extraction of power cable. Finally, some new ideas and further researches are proposed in the wavelet entropy mechanism, operation speed and how to overcome wavelet aliasing.
Wavelets an elementary treatment of theory and applications
Koornwinder, T H
1993-01-01
Nowadays, some knowledge of wavelets is almost mandatory for mathematicians, physicists and electrical engineers. The emphasis in this volume, based on an intensive course on Wavelets given at CWI, Amsterdam, is on the affine case. The first part presents a concise introduction of the underlying theory to the uninitiated reader. The second part gives applications in various areas. Some of the contributions here are a fresh exposition of earlier work by others, while other papers contain new results by the authors. The areas are so diverse as seismic processing, quadrature formulae, and wavelet
Wavelet transform analysis of electromyography kung fu strikes data.
Neto, Osmar Pinto; Marzullo, Ana Carolina de Miranda
2009-11-01
In martial arts and contact sports strikes are performed at near maximum speeds. For that reason, electromyography (EMG) analysis of such movements is non-trivial. This paper has three main goals: firstly, to investigate the differences in the EMG activity of muscles during strikes performed with and without impacts; secondly, to assess the advantages of using Sum of Significant Power (SSP) values instead of root mean square (rms) values when analyzing EMG data; and lastly to introduce a new method of calculating median frequency values using wavelet transforms (WMDF). EMG data of the deltoid anterior (DA), triceps brachii (TB) and brachioradialis (BR) muscles were collected from eight Kung Fu practitioners during strikes performed with and without impacts. SSP results indicated significant higher muscle activity (p = 0.023) for the strikes with impact. WMDF results, on the other hand, indicated significant lower values (p = 0. 007) for the strikes with impact. SSP results presented higher sensitivity than rms to quantify important signal differences and, at the same time, presented lower inter-subject coefficient of variations. The result of increase in SSP values and decrease in WMDF may suggest better synchronization of motor units for the strikes with impact performed by the experienced Kung Fu practitioners. Key PointsThe results show higher muscle activity and lower electromyography median frequencies for strikes with impact compared to strikes without.SSP results presented higher sensitivity and lower inter-subject coefficient of variations than rms results.Kung Fu palm strikes with impact may present better motor units' synchronization than strikes without.
Medical image compression with embedded-wavelet transform
Cheng, Po-Yuen; Lin, Freddie S.; Jannson, Tomasz
1997-10-01
The need for effective medical image compression and transmission techniques continues to grow because of the huge volume of radiological images captured each year. The limited bandwidth and efficiency of current networking systems cannot meet this need. In response, Physical Optics Corporation devised an efficient medical image management system to significantly reduce the storage space and transmission bandwidth required for digitized medical images. The major functions of this system are: (1) compressing medical imagery, using a visual-lossless coder, to reduce the storage space required; (2) transmitting image data progressively, to use the transmission bandwidth efficiently; and (3) indexing medical imagery according to image characteristics, to enable automatic content-based retrieval. A novel scalable wavelet-based image coder was developed to implement the system. In addition to its high compression, this approach is scalable in both image size and quality. The system provides dramatic solutions to many medical image handling problems. One application is the efficient storage and fast transmission of medical images over picture archiving and communication systems. In addition to reducing costs, the potential impact on improving the quality and responsiveness of health care delivery in the US is significant.
Matrix Expression of the Orthogonal Wavelet (Packets) Transform%正交小波(包)的矩阵表达
Institute of Scientific and Technical Information of China (English)
杜红彬; 滕虎; 姚平经
2002-01-01
Matrix expression of finite orthogonal wavelet transform of finite impulse response signal is more valuable for theoretical analysis and understanding. However, clear deduction for matrix expression has not been provided yet. In this paper, the formulation to generate the related matrix is put forward and the theorem on the orthogonality of this matrix proved. This effort deploys a basis for more deeper and wider applications in chemical processes.
Directory of Open Access Journals (Sweden)
Claudia C. Botero Suárez
2007-07-01
Full Text Available Este artículo describe la detección de actividad precrisis mediante la aplicación de la correlación cruzada junto con la transformada Wavelet. La transformada Wavelet es aplicada a los datos EEG puros para la reducción y pre-procesamiento de las señales. Esta técnica de extracción de características provee las señales simplificadas para ser procesadas por medio de la técnica de correlación cruzada. El análisis ha sido realizado con un grupo de datos tanto precrisis como intercrisis, (incluyendo crisis agudas inducidas y crisis espontáneas recurrentes, con el fin de determinar su sensitividad y especificidad (tasa de falsas predicciones. Son determinados, adicionalmente, el período de ocurrencia de crisis y el horizonte de previsión de crisis.This paper describes the detection of a pre-crisis activity through the application of Cross-Correlation together with the Wavelet Transform. The Wavelet Transform is applied in the data reduction and pre-processing of signals. This feature extract technique provides the simplified signals to process by means of the Cross-Correlation technique. The analysis with a group of pre-crisis and inter-crisis data (including both induced acute crises and recurrent spontaneous crises, to determinate its sensitivity and its specificity (False Prediction Rate has been done. The seizure occurrence period and the seizure prediction horizon are calculated additionally.
Mammogram Enhancement Using Lifting Dyadic Wavelet Transform and Normalized Tsallis Entropy
Institute of Scientific and Technical Information of China (English)
Muhammad Hussain
2014-01-01
In this paper, we present a new technique for mammogram enhancement using fast dyadic wavelet transform (FDyWT) based on lifted spline dyadic wavelets and normalized Tsallis entropy. First, a mammogram image is decom-posed into a multiscale hierarchy of low-subband and high-subband images using FDyWT. Then noise is suppressed using normalized Tsallis entropy of the local variance of the modulus of oriented high-subband images. After that, the wavelet coeﬃcients of high-subbands are modified using a non-linear operator and finally the low-subband image at the first scale is modified with power law transformation to suppress background. Though FDyWT is shift-invariant and has better poten-tial for detecting singularities like edges, its performance depends on the choice of dyadic wavelets. On the other hand, the number of vanishing moments is an important characteristic of dyadic wavelets for singularity analysis because it provides an upper bound measurement for singularity characterization. Using lifting dyadic schemes, we construct lifted spline dyadic wavelets of different degrees with increased number of vanishing moments. We also examine the effect of these wavelets on mammogram enhancement. The method is tested on mammogram images, taken from MIAS (Mammographic Image Analysis Society) database, having various background tissue types and containing different abnormalities. The comparison with the state-of-the-art contrast enhancement methods reveals that the proposed method performs better and the difference is statistically significant.
Detection Of Ventricular Late Potentials Using Wavelet Transform And ANT Colony Optimization
Subramanian, A. Sankara; Gurusamy, G.; Selvakumar, G.
2010-10-01
Ventricular late Potentials (VLPs) are low-level high frequency signals that are usually found with in the terminal part of the QRS complex from patients after Myocardial Infraction. Patients with VLPs are at risk of developing Ventricular Tachycardia, which is the major cause of death if patients suffering from heart disease. In this paper the Discrete Wavelet Transform was used to detect VLPs and then ANT colony optimization (ACO) was applied to classify subjects with and without VLPs. A set of Discrete Wavelet Transform (DWT) coefficients is selected from the wavelet decomposition. Three standard parameters of VLPs such as QRST, D40 and V40 are also established. After that a novel clustering algorithm based on Ant Colony Optimization is developed for classifying arrhythmia types. The wavelet decomposition enabled us to perform the task efficiently and produced reliable results.
Identification of Semen Celosiae and Cockscomb Flower Using Continuous Wavelet Transform with FTIR
Institute of Scientific and Technical Information of China (English)
Changjiang Zhang; Cungui Cheng
2006-01-01
Infrared spectra of semen celosiae and cockscomb flower can be obtained directly, quickly and accurately employing Fourier transform infrared spectroscopy (FTIR) with OMNI sampler. Continuous wavelet transform (CWT) is employed to zoom in local region of infrared spectra of semen celosiae and cockscomb flower. Thus difference of infrared spectra between semen celosiae and cockscomb flower is greatly extruded. Identification rate is greatly improved.Daubechies wavelet is used as mother wavelet. CWT is implemented to the infrared spectra of semen celosiae and cockscomb flower. The difference between semen celosiae and cockscomb flower is observed at all scales in the continuous wavelet domain. An optimal scale is selected to identify semen celosiae and cockscomb flower. Experimental results show that it is effective to apply CWT on the basis of FTIR to identify traditional Chinese medicinal materials, which are the same general but different species.
Text Detection in Video Using Haar Wavelet Transformation and Morphological Operator
Directory of Open Access Journals (Sweden)
Dinesh AnnajiKene
2015-11-01
Full Text Available This paper presents simple and efficient method for text detection, extraction and localization from video or static images using Haar wavelet and Morphological operator. Haar wavelet transform have its coefficients either 1 or -1 , so that the operation speed of Haar wavelet transformation is fastest among all wavelets. The sub bands contain both text edges and non-text edges however the intensity of text edges is different that of the non-text edges. Instead of using Canny operator we used Sobal operator for edge detection because Sobal operator detect more edges than Canny operator when there is text information. Morphological operators are applied to edit or smoothing out the text region. Then detected text regions are further decomposed into character level. Then using some refinement the final text region are obtained.
Adaptive Bayesian-based speck-reduction in SAR images using complex wavelet transform
Ma, Ning; Yan, Wei; Zhang, Peng
2005-10-01
In this paper, an improved adaptive speckle reduction method is presented based on dual tree complex wavelet transform (CWT). It combines the characteristics of additive noise reduction of soft thresholding with the CWT's directional selectivity, being its main contribution to adapt the effective threshold to preserve the edge detail. A Bayesian estimator is applied to the decomposed data also to estimate the best value for the noise-free complex wavelet coefficients. This estimation is based on alpha-stable and Gaussian distribution hypotheses for complex wavelet coefficients of the signal and noise, respectively. Experimental results show that the denoising performance is among the state-of-the-art techniques based on real discrete wavelet transform (DWT).
Institute of Scientific and Technical Information of China (English)
Gao Chao; Zhou Shanxue
2010-01-01
This letter investigates the wavelet transform,as well as the principle and the method of the noise reduction based on wavelet transform,it chooses the threshold noise reduction,and discusses in detail the principles,features and design steps of the threshold method. Rigrsure,heursure,sqtwolog and minimization four kinds of threshold selection method are compared qualitatively,and quantitatively. The wavelet analysis toolbox of MATLAB helps to realize the computer simulation of the signal noise reduction. The graphics and calculated standard deviation of the various threshold noise reductions show that,when dealing with the actual pressure signal of the oil pipeline leakage,sqtwolog threshold selection method can effectively remove the noise. Aiming to the pressure signal of the oil pipeline leakage,the best choice is the wavelet threshold noise reduction with sqtwolog threshold. The leakage point is close to the actual position,with the relative error of less than 1%.
Directory of Open Access Journals (Sweden)
Li Yuanyuan
2013-01-01
Full Text Available In this study, a Wavelet Transformation (WT device of Surface Acoustic Wave (SAW technology is developed on the basis of acoustics, electronics, wavelet theory, applied mathematics and semiconductor planar technology. The Finger Reflection (FR error is the primary reason for this kind of device. To solve the problem, a mathematic model of Littlewood-pelay wavelet was established first, which is matched with the model of SAW. Using the methods of split finger and fake finger to design IDT of Littlewood-pelay WT device of SAW with L-edit software, the FR error can be reduced and the equivalent construction of IDT is simulated.
Pattern discrimination of joint transform correlator based on wavelet subband filtering
Lin, Li-Chien; Cheng, Chau-Jern
2004-04-01
We propose and demonstrate a Gabor wavelet prefiltering prior to classical and binarized joint transform correlator implementation to enhance texture features of fingerprints. The frequency- and orientation-selective properties of the wavelet subband filter are utilized to extract important textural features for optimal correlation recognition. A selection criterion for wavelet subbands is derived, and it is shown that the maximum signal-to-noise ratio of the correlator is achieved by optimizing the threshold level. Simulation results show that the proposed method increases the discrimination power of the correlator, especially under noisy environments.
Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis
Directory of Open Access Journals (Sweden)
SU, H.
2011-08-01
Full Text Available Border effects are very common in many finite signals analysis and processing approaches using convolution operation. Alleviating the border effects that can occur in the processing of finite-length signals using wavelet transform is considered in this paper. Traditional methods for alleviating the border effects are suitable to compression or coding applications. We propose an algorithm based on Fourier series which is proved to be appropriate to the application of time-frequency analysis of nonlinear signals. Fourier series extension method preserves the time-varying characteristics of the signals. A modified signal duration expression for measuring the extent of border effects region is presented. The proposed algorithm is confirmed to be efficient to alleviate the border effects in comparison to the current methods through the numerical examples.
Directory of Open Access Journals (Sweden)
Rania Salah El-Sayed
2012-11-01
Full Text Available Face recognition has become one of the most challenging tasks in the pattern recognition field and it is very important for many applications such as: video surveillance, forensic applications criminal investigations, and in many other fields it is also very useful. In this paper we are using sparse representation approach based on discrete wavelet transform (DWT to achieve more robustness to variation in lighting, directions and expressions, because sparse representation does not exterminate obstacles posed by several practical issues, such as lighting, pose, and especially facial expressions, which tend to distort almost all the features and can thus compromise the accuracy of sparse representation. The result of new proposed approach is compared with sparse representation approach to show that the proposed approach is more robust to illumination, direction and expression variations than sparse representation.
Energy Technology Data Exchange (ETDEWEB)
Gketsis, Zacharias E.; Zervakis, Michalis E.; Stavrakakis, George [Department of Electronics and Computer Engineering, Technical University of Crete, Chania 73100 (Greece)
2009-11-15
This paper exploits the Wavelet Transform (WT) analysis along with Artificial Neural Networks (ANN) for the diagnosis of electrical machines winding faults. A novel application is presented exploring the problem of automatically identifying short circuits of windings, which often appear during machine manufacturing and operation. Such faults are usually resulting from electrodynamics forces generated during the flow of large short circuit currents, as well as forces occurring when the machines are transported. The early detection and classification of winding failures is of particular importance, as these kinds of defects can lead to winding damage due to overheating, imbalance, etc. Application results and investigations of windmill generator winding turn-to-turn faults between adjacent winding wires are presented. The ANN approach is proven effective in detecting and classifying faults based on WT features extracted from high frequency measurements of the admittance, current, or voltage responses. (author)
Alshahrani, S; Abbod, M; Alamri, B; Taylor, G.
2015-01-01
In this paper, detection method and classification technique of power quality disturbances is presented. Due to the increase of nonlinear load recently, it becomes an essential requirement to insure high level of power supply and efficient commotional consuming. Wavelet Transform represents a powerful mathematical platform which is needed especially at non-stationary situations. Disturbances are fed into wavelets to filter, detect and extract its features at different frequencies. Training of...
Sharma, K. K.; Jain, Heena
2013-01-01
The security of digital data including images has attracted more attention recently, and many different image encryption methods have been proposed in the literature for this purpose. In this paper, a new image encryption method using wavelet packet decomposition and discrete linear canonical transform is proposed. The use of wavelet packet decomposition and DLCT increases the key size significantly making the encryption more robust. Simulation results of the proposed technique are also presented.
Combined Power Quality Disturbances Recognition Using Wavelet Packet Entropies and S-Transform
Zhigang Liu; Yan Cui; Wenhui Li
2015-01-01
Aiming at the combined power quality +disturbance recognition, an automated recognition method based on wavelet packet entropy (WPE) and modified incomplete S-transform (MIST) is proposed in this paper. By combining wavelet packet Tsallis singular entropy, energy entropy and MIST, a 13-dimension vector of different power quality (PQ) disturbances including single disturbances and combined disturbances is extracted. Then, a ruled decision tree is designed to recognize the combined disturbance...
Biomedical Image Processing Using FCM Algorithm Based on the Wavelet Transform
Institute of Scientific and Technical Information of China (English)
YAN Yu-hua; WANG Hui-min; LI Shi-pu
2004-01-01
An effective processing method for biomedical images and the Fuzzy C-mean (FCM) algorithm based on the wavelet transform are investigated.By using hierarchical wavelet decomposition, an original image could be decomposed into one lower image and several detail images. The segmentation started at the lowest resolution with the FCM clustering algorithm and the texture feature extracted from various sub-bands. With the improvement of the FCM algorithm, FCM alternation frequency was decreased and the accuracy of segmentation was advanced.
A fault location method using Lamb waves and discrete wavelet transform
Souza, Pablo Rodrigo de; Nobrega, Eurípedes Guilherme de Oliveira
2012-01-01
Non-destructive evaluation methods and signal process techniques are important steps in structural health monitoring systems to assess the structure integrity. This paper presents a method for fault location in aluminum beams based on time of flight of Lamb waves. The dynamic response signal captured from the structure was processed using the discrete wavelet transform. The information accuracy obtained from the processed signal depends on the correct choice of the mother wavelet. The best mo...
Mine-hoist fault-condition detection based on the wavelet packet transform and kernel PCA
Institute of Scientific and Technical Information of China (English)
XIA Shi-xiong; NIU Qiang; ZHOU Yong; ZHANG Lei
2008-01-01
A new algorithm was developed to correctly identify fault conditions and accurately monitor fault development in a mine hoist. The new method is based on the Wavelet Packet Transform (WPT) and kernel PCA (Kernel Principal Component Analysis, KPCA). For non-linear monitoring systems the key to fault detection is the extracting of main features. The wavelet packet transform is a novel technique of signal processing that possesses excellent characteristics of time-frequency localization. It is suitable for analysing time-varying or transient signals. KPCA maps the original input features into a higher dimension feature space through a non-linear mapping. The principal components are then found in the higher dimension feature space. The KPCA transformation was applied to extracting the main nonlinear features from experimental fault feature data after wavelet packet transformation. The results show that the proposed method affords credible fault detection and identification.
Area and Throughput Trade-Offs in the Design of Pipelined Discrete Wavelet Transform Architectures
Silva, Sandro V
2011-01-01
The JPEG2000 standard defines the discrete wavelet transform (DWT) as a linear space-to-frequency transform of the image domain in an irreversible compression. This irreversible discrete wavelet transform is implemented by FIR filter using 9/7 Daubechies coefficients or a lifting scheme of factorizated coefficients from 9/7 Daubechies coefficients. This work investigates the tradeoffs between area, power and data throughput (or operating frequency) of several implementations of the Discrete Wavelet Transform using the lifting scheme in various pipeline designs. This paper shows the results of five different architectures synthesized and simulated in FPGAs. It concludes that the descriptions with pipelined operators provide the best area-power-operating frequency trade-off over non-pipelined operators descriptions. Those descriptions require around 40% more hardware to increase the maximum operating frequency up to 100% and reduce power consumption to less than 50%. Starting from behavioral HDL descriptions pr...
Xue, G. Q.; Yan, Y. J.; Li, X.
2007-08-01
This paper presents some new theoretical analysis and numerical simulations of that transient electromagnetic diffusion-field response is transformed into a pseudo-seismic wavelet in engineering geology exploration. It can clearly reveal the electric interface under ground. To simplify the integral equation used in the transformation, the integral range is separated into seven windows, and each window is compiled into a group of integral coefficients. Then, the accuracy of the coefficients is tested, and the calculated coefficients are used to derive the pseudo-seismic wavelet by optimization method. Finally, several geo-electric models are designed, so that model responses are transformed into the pseudo-seismic wavelet. The transformed imaginary wave shows that some reflection and refraction phenomena appear when the wave meets the electric interface. This result supports the introduction of the seismic interpretation in data processing of transient electromagnetic method.
Implementation of the 2-D Wavelet Transform into FPGA for Image
León, M.; Barba, L.; Vargas, L.; Torres, C. O.
2011-01-01
This paper presents a hardware system implementation of the of discrete wavelet transform algoritm in two dimensions for FPGA, using the Daubechies filter family of order 2 (db2). The decomposition algorithm of this transform is designed and simulated with the Hardware Description Language VHDL and is implemented in a programmable logic device (FPGA) XC3S1200E reference, Spartan IIIE family, by Xilinx, take advantage the parallels properties of these gives us and speeds processing that can reach them. The architecture is evaluated using images input of different sizes. This implementation is done with the aim of developing a future images encryption hardware system using wavelet transform for security information.
Use of switched capacitor filters to implement the discrete wavelet transform
Kaiser, Kraig E.; Peterson, James N.
1993-01-01
This paper analyzes the use of IIR switched capacitor filters to implement the discrete wavelet transform and the inverse transform, using quadrature mirror filters (QMF) which have the necessary symmetry for reconstruction of the data. This is done by examining the sensitivity of the QMF transforms to the manufacturing variance in the desired capacitances. The performance is evaluated at the outputs of the separate filter stages and the error in the reconstruction of the inverse transform is compared with the desired results.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In view of the feature of flight flutter test data with atmospheric turbulence excitation, a method which combines wavelet transformation with random decrement technique for identifying flight flutter modal parameters is presented. This approach firstly uses random decrement technique to gain free decays corresponding to the acceleration response of the structure to some non-zero initial conditions. Then the continuous Morlet wavelet transformation of the free decays is performed; and the Parseval formula and residue theorem are used to simplify the transformation. The maximal wavelet transformation coefficients in different scales are searched out by means of band-filtering characteristic of Morlet wavelet, and then the modal parameters are identified according to the relationships with maximal modulus and angle of the wavelet transform. In addition, the condition of modal uncoupling is discussed according to variation trend of flight flutter modal parameters in the flight flutter state. The analysis results of simulation and flight flutter test data show that this approach is not only simple, effective and feasible, but also having good noise immunity.
Journee, HL; de Jonge, AB; Hamoen, DJ; Smit, A; van Bruggen, AC; Mooij, JJA; Boom, H; Robinson, C; Rutten, W; Neuman, M; Wijkstra, H
1997-01-01
Wavelet Transform (WT) is applied in a method for timing the blood pulse wave between the internal carotid artery: and one of the intracranial arteries. The required accuracy is a few milliseconds. In contrast to the Fourier Transform (FT), WT is an appropriate technique for the detection of
Application of wavelet transform in active power filter harmonic analysis%小波变换在有源电力滤波器谐波分析中的应用
Institute of Scientific and Technical Information of China (English)
梁东莺; 毛蔚
2009-01-01
In order to effectively analyze and resolve Active impedance transform, wavelet transform on the use of harmonic and inter harmonic detection methods are studied, and on this basis to explore the use of wavelet analysis to study the control of time-frequency characteristics of impedance and frequency characteristics of the basic principles of analysis of the use of wavelet transform to separate harmonic inter-harmonic wave with the algorithm, taking into account time and frequency domain resolution. The simulation results show that the method not only has the characteristics of high-resolution, but also can identify the APF time-frequency impedance chara-cteristics, it is very useful for harmonic analysis, in the active power filter harmonic inhibitory aspects, and it has providing a feasible solution.%为有效分析和解决有源阻抗变换,对使用小波变换检测谐波与间谐波的方法进行了研究,并在此基础上探讨了利用小波分析、研究时频阻抗的控制特性和频率特性的基本原理,提出了利用小波变换来分离谐波与间谐波的算法,并兼顾时域和频域的分辨率.仿真结果表明,该方法不仅具有高分辨率特性,能较好地找出APF的时频阻抗特性,可以较好地分析谐波,以使其跟踪特性最优,为有源电力滤波器谐波抑制提供了可行的解决途径.
Daubechies Wavelet Tool: Application For Human Face Recognition
Directory of Open Access Journals (Sweden)
Ms. Swapna M. Patil,
2011-03-01
Full Text Available In this paper fusion of visual and thermal images in wavelet transformed domain has been presented. Here, Daubechies wavelet transform, called as D2, coefficients from visual and corresponding coefficients computed in the same manner from thermal images are combined to get fused coefficients. After decomposition up to fifth level (Level 5 fusion of coefficients is done. Inverse Daubechies wavelet transform of those coefficients gives us fused face images. The main advantage of using wavelet transform is that it is well-suited to manage different image resolution and allows the image decomposition in different kinds of coefficients, while preserving the image information. Fused images thus found are passed through Principal Component Analysis (PCA for reduction of dimensions and then those reduced fused images are classified using a multi-layer perceptron. For experiments IRIS Thermal/Visual Face Database was used. Experimental results show that the performance of the approach presented here achieves maximum success rate of 100% in many cases.
Steganography based on wavelet transform and modulus function
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In order to provide larger capacity of the hidden secret data while maintaining a good visual quality of stego-image,in accordance with the visual property that human eyes are less sensitive to strong texture,a novel steganographic method based on wavelet and modulus function is presented.First,an image is divided into blocks of prescribed size,and every block is decomposed into one-level wavelet.Then,the capacity of the hidden secret data is decided with the number of wavelet coefficients of larger magnitude.Finall,secret information is embedded by steganography based on modulus function. From the experimental results,the proposed method hides much more information and maintains a good visual quality of stego-image.Besides,the embedded data can be extracted from the stego-image without referencing the original image.
偏微分方程和连续小波变换%Partial differential equation and continuous wavelet transform
Institute of Scientific and Technical Information of China (English)
屈汉章; 赵瑞珍; 宋国乡
2001-01-01
利用连续小波变换讨论了偏微分方程和积分方程之间的关系，得到了一类偏微分方程利用连续小波变换能够变换成在弱拓扑下等价的积分方程的结果．由积分方程决定的线性算子是有界算子，从而将偏微分方程的讨论与积分方程的讨论联系起来，使得连续小波变换能够应用于偏微分方程和积分方程中．%We discuss the relation between partial differential equationsand integral equations by using the continuous wavelet transform and obtain the result that some partial differential equations can be transformed into the integral equations by using the continuous wavelet transform which are equivalent in the weak topology. Associating the discussion of the partial differential equations with the discussion of the integral equations makes the continuous wavelet transform applicable the discussion of the partial differential equations and the integral equations.
van den Berg, J. C.
2004-03-01
A guided tour J. C. van den Berg; 1. Wavelet analysis, a new tool in physics J.-P. Antoine; 2. The 2-D wavelet transform, physical applications J.-P. Antoine; 3. Wavelets and astrophysical applications A. Bijaoui; 4. Turbulence analysis, modelling and computing using wavelets M. Farge, N. K.-R. Kevlahan, V. Perrier and K. Schneider; 5. Wavelets and detection of coherent structures in fluid turbulence L. Hudgins and J. H. Kaspersen; 6. Wavelets, non-linearity and turbulence in fusion plasmas B. Ph. van Milligen; 7. Transfers and fluxes of wind kinetic energy between orthogonal wavelet components during atmospheric blocking A. Fournier; 8. Wavelets in atomic physics and in solid state physics J.-P. Antoine, Ph. Antoine and B. Piraux; 9. The thermodynamics of fractals revisited with wavelets A. Arneodo, E. Bacry and J. F. Muzy; 10. Wavelets in medicine and physiology P. Ch. Ivanov, A. L. Goldberger, S. Havlin, C.-K. Peng, M. G. Rosenblum and H. E. Stanley; 11. Wavelet dimension and time evolution Ch.-A. Guérin and M. Holschneider.