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.
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.
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
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 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.
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.
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.
Psychoacoustic Music Analysis Based on the Discrete Wavelet Packet Transform
Directory of Open Access Journals (Sweden)
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.
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.
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.
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...
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.
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.
Institute of Scientific and Technical Information of China (English)
REN Shou-xin; GAO Ling
2004-01-01
This paper covers a novel method named wavelet packet transform based Elman recurrent neural network(WPTERNN) for the simultaneous kinetic determination of periodate and iodate. The wavelet packet representations of signals provide a local time-frequency description, thus in the wavelet packet domain, the quality of the noise removal can be improved. The Elman recurrent network was applied to non-linear multivariate calibration. In this case, by means of optimization, the wavelet function, decomposition level and number of hidden nodes for WPTERNN method were selected as D4, 5 and 5 respectively. A program PWPTERNN was designed to perform multicomponent kinetic determination. The relative standard error of prediction(RSEP) for all the components with WPTERNN, Elman RNN and PLS were 3.23%, 11.8% and 10.9% respectively. The experimental results show that the method is better than the others.
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.
Research of Adaptive Resolution Spectrum Sensing Method Based on Discrete Wavelet Packet Transform
Directory of Open Access Journals (Sweden)
Wei Naiqi
2013-09-01
Full Text Available Spectrum sensing is the precondition of the realization of cognitive radio. In order to achieve efficient multi-resolution spectrum sensing, and find the available spectrum hole quickly, it proposes a variable resolution adaptive frequency spectrum energy sensing method based on discrete wavelet packet transform (DWPT. The method applied hierarchical decomposition and threshold denoising characteristic of wavelet packet transform, and solved the problem of subband sort disorder in wavelet packet decomposition process; it can eliminate the influence of uncertainty noise on detection performance, effectively. It also can reduce the computational complexity according to demand of selection resolution and perception band. The simulation results and its analysis show that the proposed method has advantages of high precision, simple arithmetic and fine flexibility, etc. The method is adapted to fast sensing in the cognitive radio environment.
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.
Combined Power Quality Disturbances Recognition Using Wavelet Packet Entropies and S-Transform
Directory of Open Access Journals (Sweden)
Zhigang Liu
2015-08-01
Full Text Available 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 disturbances. The proposed method is tested and evaluated using a large number of simulated PQ disturbances and some real-life signals, which include voltage sag, swell, interruption, oscillation transient, impulsive transient, harmonics, voltage fluctuation and their combinations. In addition, the comparison of the proposed recognition approach with some existing techniques is made. The experimental results show that the proposed method can effectively recognize the single and combined PQ disturbances.
BER IMPROVEMENT OF WIRELESS LAN IEEE 802.11 STANDARD USING WAVELET PACKET TRANSFORMS
Directory of Open Access Journals (Sweden)
Sanjeev Kumar
2012-09-01
Full Text Available High data rates and spectral efficiency is the main requirements for wireless communication systems. Orthogonal Frequency Division Multiplexing (OFDM is a special form of multi carrier transmission used to achieve high data rates of the various WLAN standards. WLAN uses an Inverse Fast Fourier Transform (IFFT at the transmitter to modulate a high bit-rate signal onto a number of carriers and ensure orthogonality between the carriers. The FFT-OFDM has a disadvantage that it is inherently inflexible and requires a complex IFFT core. Recently, Wavelet Packet Transform is proposed as an alternate to FFT. It is a multiplexing method in which data is assigned to wavelet sub bands having different time and frequency resolutions. This paper presents a BER analysis of Fourier-based OFDM (FFT-OFDM and Wavelet Packet based OFDM (WPT-OFDM in WLAN standard (IEEE 802.11a. The performance of FFT and WPT OFDM for various modulation techniques such as PSK, DPSK and QAM for varying values of M was evaluated in AWGN Channel.
Radar Emitter Signal Recognition Using Wavelet Packet Transform and Support Vector Machines
Institute of Scientific and Technical Information of China (English)
Jin Weidong; Zhang Gexiang; Hu Laizhao
2006-01-01
This paper presents a novel method for radar emitter signal recognition. First, wavelet packet transform (WPT) is introduced to extract features from radar emitter signals. Then, rough set theory is used to select the optimal feature subset with good discriminability from original feature set, and support vector machines (SVMs) are employed to design classifiers. A large number of experimental results show that the proposed method achieves very high recognition rates for 9 radar emitter signals in a wide range of signal-to-noise rates, and proves a feasible and valid method.
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.
A NOVEL ALGORITHM OF MULTI-SENSOR IMAGE FUSION BASED ON WAVELET PACKET TRANSFORM
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In order to enhance the image information from multi-sensor and to improve the abilities of theinformation analysis and the feature extraction, this letter proposed a new fusion approach in pixel level bymeans of the Wavelet Packet Transform (WPT). The WPT is able to decompose an image into low frequencyband and high frequency band in higher scale. It offers a more precise method for image analysis than Wave-let Transform (WT). Firstly, the proposed approach employs HIS (Hue, Intensity, Saturation) transform toobtain the intensity component of CBERS (China-Brazil Earth Resource Satellite) multi-spectral image. ThenWPT transform is employed to decompose the intensity component and SPOT (Systeme Pour I'Observationde la Therre ) image into low frequency band and high frequency band in three levels. Next, two high fre-quency coefficients and low frequency coefficients of the images are combined by linear weighting strategies.Finally, the fused image is obtained with inverse WPT and inverse HIS. The results show the new approachcan fuse details of input image successfully, and thereby can obtain a more satisfactory result than that of HM(Histogram Matched)-based fusion algorithm and WT-based fusion approach.
Wavelet and wavelet packet compression of electrocardiograms.
Hilton, M L
1997-05-01
Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data. Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECG's are clinically useful.
Structural Damage Identification via Pseudo Strain Energy Density and Wavelet Packet Transform
Institute of Scientific and Technical Information of China (English)
CHEN Xiao-qiang; ZHU Hong-ping; GE Dong-dong
2009-01-01
Based on strain signals,a new time-domain methodology for detecting the beam local damage has been developed.The pseudo strain energy density (PSED) is defined and used to build two major damage indexes,the average pseudo strain energy density (APSED) and the average pseudo strain energy density rate (APSEDR).Probability and mathematical statistics are utilized to derive a standardized damage index.Furthermore,by applying the analytic relation between the strain energy release rate and the stress intensity factor,an analytic solution of crack depth is derived.For the dynamic strain signals,the wavelet packet transform is used to pre-process measured data.Finally,a numerical simulation indicates that this method can effectively identify the damage location and its absolute severity.
Robust Automatic Speech Recognition Features using Complex Wavelet Packet Transform Coefficients
Directory of Open Access Journals (Sweden)
Tjong Wan Sen
2013-09-01
Full Text Available To improve the performance of phoneme based Automatic Speech Recognition (ASR in noisy environment; we developed a new technique that could add robustness to clean phonemes features. These robust features are obtained from Complex Wavelet Packet Transform (CWPT coefficients. Since the CWPT coefficients represent all different frequency bands of the input signal, decomposing the input signal into complete CWPT tree would also cover all frequencies involved in recognition process. For time overlapping signals with different frequency contents, e. g. phoneme signal with noises, its CWPT coefficients are the combination of CWPT coefficients of phoneme signal and CWPT coefficients of noises. The CWPT coefficients of phonemes signal would be changed according to frequency components contained in noises. Since the numbers of phonemes in every language are relatively small (limited and already well known, one could easily derive principal component vectors from clean training dataset using Principal Component Analysis (PCA. These principal component vectors could be used then to add robustness and minimize noises effects in testing phase. Simulation results, using Alpha Numeric 4 (AN4 from Carnegie Mellon University and NOISEX-92 examples from Rice University, showed that this new technique could be used as features extractor that improves the robustness of phoneme based ASR systems in various adverse noisy conditions and still preserves the performance in clean environments.
Robust Automatic Speech Recognition Features using Complex Wavelet Packet Transform Coefficients
Directory of Open Access Journals (Sweden)
TjongWan Sen
2009-11-01
Full Text Available To improve the performance of phoneme based Automatic Speech Recognition (ASR in noisy environment; we developed a new technique that could add robustness to clean phonemes features. These robust features are obtained from Complex Wavelet Packet Transform (CWPT coefficients. Since the CWPT coefficients represent all different frequency bands of the input signal, decomposing the input signal into complete CWPT tree would also cover all frequencies involved in recognition process. For time overlapping signals with different frequency contents, e. g. phoneme signal with noises, its CWPT coefficients are the combination of CWPT coefficients of phoneme signal and CWPT coefficients of noises. The CWPT coefficients of phonemes signal would be changed according to frequency components contained in noises. Since the numbers of phonemes in every language are relatively small (limited and already well known, one could easily derive principal component vectors from clean training dataset using Principal Component Analysis (PCA. These principal component vectors could be used then to add robustness and minimize noises effects in testing phase. Simulation results, using Alpha Numeric 4 (AN4 from Carnegie Mellon University and NOISEX-92 examples from Rice University, showed that this new technique could be used as features extractor that improves the robustness of phoneme based ASR systems in various adverse noisy conditions and still preserves the performance in clean environments.
Xing, Y. F.; Wang, Y. S.; Shi, L.; Guo, H.; Chen, H.
2016-01-01
According to the human perceptional characteristics, a method combined by the optimal wavelet-packet transform and artificial neural network, so-called OWPT-ANN model, for psychoacoustical recognition is presented. Comparisons of time-frequency analysis methods are performed, and an OWPT with 21 critical bands is designed for feature extraction of a sound, as is a three-layer back-propagation ANN for sound quality (SQ) recognition. Focusing on the loudness and sharpness, the OWPT-ANN model is applied on vehicle noises under different working conditions. Experimental verifications show that the OWPT can effectively transfer a sound into a time-varying energy pattern as that in the human auditory system. The errors of loudness and sharpness of vehicle noise from the OWPT-ANN are all less than 5%, which suggest a good accuracy of the OWPT-ANN model in SQ recognition. The proposed methodology might be regarded as a promising technique for signal processing in the human-hearing related fields in engineering.
Multi-threshold de-noising of electrical imaging logging data based on the wavelet packet transform
Xie, Fang; Xiao, Chengwen; Liu, Ruilin; Zhang, Lili
2017-08-01
A key problem of effectiveness evaluation for fractured-vuggy carbonatite reservoir is how to accurately extract fracture and vug information from electrical imaging logging data. Drill bits quaked during drilling and resulted in rugged surfaces of borehole walls and thus conductivity fluctuations in electrical imaging logging data. The occurrence of the conductivity fluctuations (formation background noise) directly affects the fracture/vug information extraction and reservoir effectiveness evaluation. We present a multi-threshold de-noising method based on wavelet packet transform to eliminate the influence of rugged borehole walls. The noise is present as fluctuations in button-electrode conductivity curves and as pockmarked responses in electrical imaging logging static images. The noise has responses in various scales and frequency ranges and has low conductivity compared with fractures or vugs. Our de-noising method is to decompose the data into coefficients with wavelet packet transform on a quadratic spline basis, then shrink high-frequency wavelet packet coefficients in different resolutions with minimax threshold and hard-threshold function, and finally reconstruct the thresholded coefficients. We use electrical imaging logging data collected from fractured-vuggy Ordovician carbonatite reservoir in Tarim Basin to verify the validity of the multi-threshold de-noising method. Segmentation results and extracted parameters are shown as well to prove the effectiveness of the de-noising procedure.
OFDM Scheme Based on Wavelet Packet Transform-OrientedGraded Multi-Service
Institute of Scientific and Technical Information of China (English)
赵慧; 侯春萍
2003-01-01
In this paper, a concept of image grading transmission is put forward to enhance data rate and to improve the usage of subcarriers in orthogonal frequency division multiplexing (OFDM). The idea originates from the wavelet packets representative of an image in which information is graded in terms of different priorities. The graded image facilitates more efficient use of adaptive subcarriers and bits allocation. The results of simulation in typical mobile environment prove that the output signal noise ratio (SNR) of the graded image excels that of the ungraded image by 1-2 dB under the same channel condition.
Orthogonal Matrix-Valued Wavelet Packets
Institute of Scientific and Technical Information of China (English)
Qingjiang Chen; Cuiling Wang; Zhengxing Cheng
2007-01-01
In this paper,we introduce matrix-valued multiresolution analysis and matrixvalued wavelet packets. A procedure for the construction of the orthogonal matrix-valued wavelet packets is presented. The properties of the matrix-valued wavelet packets are investigated. In particular,a new orthonormal basis of L2(R,Cs×s) is obtained from the matrix-valued wavelet packets.
Group-normalized processing of complex wavelet packets
Institute of Scientific and Technical Information of China (English)
石卓尔; 保铮
1997-01-01
Linear phase is not possible for real valued FIR QMF, while linear phase FIR biorthogonal wavelet filter banks make the mean squared error of the constructed signal exceed that of the quantization error. W Lawton’ s method for complex valued wavelets construction is extended to generate the complex valued compactly supported wavelet packets that are symmetrical and unitary orthogonal; then well-defined wavelet packets are chosen by the analysis remarks on their time-frequency characteristics. Since the traditional wavelel packets transform coefficients do not exactly represent the strength of signal components, a modified adaptive wavelets transform, group-normalized wavelet packet transform (GNWPT), is presented and utilized for target extraction from formidable clutter or noises with the time-frequency masking technique. The extended definition of lp-norm entropy improves the performance cf GNWPT. Similar method can also be applied to image enhancement, clutter and noise suppression, optimal detection
Quantization of wavelet packet audio coding
Institute of Scientific and Technical Information of China (English)
Tan Jianguo; Zhang Wenjun; Liu Peilin
2006-01-01
The method of quantization noise control of audio coding in the wavelet domain is proposed. Using the inverse Discrete Fourier Transform (DFT), it converts the masking threshold coming from MPEG psycho-acoustic model in the frequency domain to the signal in the time domain; the Discrete Wavelet Packet Transform (DWPT) is performed; the energy in each subband is regarded as the maximum allowed quantization noise energy. The experimental result shows that the proposed method can attain the nearly transparent audio quality below 64kbps for the most testing audio signals.
Qu, Jinxiu; Zhang, Zhousuo; Wen, Jinpeng; Guo, Ting; Luo, Xue; Sun, Chuang; Li, Bing
2014-08-01
The viscoelastic sandwich structure is widely used in mechanical equipment, yet the structure always suffers from damage during long-term service. Therefore, state recognition of the viscoelastic sandwich structure is very necessary for monitoring structural health states and keeping the equipment running with high reliability. Through the analysis of vibration response signals, this paper presents a novel method for this task based on the adaptive redundant second generation wavelet packet transform (ARSGWPT), permutation entropy (PE) and the wavelet support vector machine (WSVM). In order to tackle the non-linearity existing in the structure vibration response, the PE is introduced to reveal the state changes of the structure. In the case of complex non-stationary vibration response signals, in order to obtain more effective information regarding the structural health states, the ARSGWPT, which can adaptively match the characteristics of a given signal, is proposed to process the vibration response signals, and then multiple PE features are extracted from the resultant wavelet packet coefficients. The WSVM, which can benefit from the conventional SVM as well as wavelet theory, is applied to classify the various structural states automatically. In this study, to achieve accurate and automated state recognition, the ARSGWPT, PE and WSVM are combined for signal processing, feature extraction and state classification, respectively. To demonstrate the effectiveness of the proposed method, a typical viscoelastic sandwich structure is designed, and the different degrees of preload on the structure are used to characterize the various looseness states. The test results show that the proposed method can reliably recognize the different looseness states of the viscoelastic sandwich structure, and the WSVM can achieve a better classification performance than the conventional SVM. Moreover, the superiority of the proposed ARSGWPT in processing the complex vibration response
Energy Technology Data Exchange (ETDEWEB)
Morsi, Walid G. [University of New Brunswick, Fredericton, New Brunswick (Canada); El-Hawary, M.E. [Dalhousie University, Halifax, Nova Scotia (Canada)
2010-07-15
High power quality (PQ) level represents one of the main objectives towards smart grid. The currently used PQIs that are a measure of the PQ level are defined under the umbrella of the Fourier foundation that produces unrealistic results in case of non-stationary PQ disturbances. In order to accurately measure those indices, wavelet packet transform (WPT) is used in this paper to reformulate the recommended PQIs and hence benefiting from the WPT capabilities in accurately analyzing non-stationary waveforms and providing a uniform time-frequency sub-bands leading to reduced size of the data to be processed which is a necessity to facilitate the implementation of smart grid. Numerical examples' results considering non-stationary waveforms prove the suitability of the WPT for PQIs measurement; also the results indicate that Daubechies 10 could be the best candidate wavelet basis function that could provide acceptable accuracy while requiring less number of wavelet coefficients and hence reducing the data size. Moreover, a new time-frequency overall and node crest factors are introduced in this paper. The new node crest factor is able to determine the node or the sub-band that is responsible for the largest impact which could not be achieved using traditional approaches. (author)
Image coding based on energy-sorted wavelet packets
Kong, Lin-Wen; Lay, Kuen-Tsair
1995-04-01
The discrete wavelet transform performs multiresolution analysis, which effectively decomposes a digital image into components with different degrees of details. In practice, it is usually implemented in the form of filter banks. If the filter banks are cascaded and both the low-pass and the high-pass components are further decomposed, a wavelet packet is obtained. The coefficients of the wavelet packet effectively represent subimages in different resolution levels. In the energy-sorted wavelet- packet decomposition, all subimages in the packet are then sorted according to their energies. The most important subimages, as measured by the energy, are preserved and coded. By investigating the histogram of each subimage, it is found that the pixel values are well modelled by the Laplacian distribution. Therefore, the Laplacian quantization is applied to quantized the subimages. Experimental results show that the image coding scheme based on wavelet packets achieves high compression ratio while preserving satisfactory image quality.
Huang, Shieh-Kung; Loh, Chin-Hsiung; Chen, Chin-Tsun
2016-04-01
Seismic records collected from earthquake with large magnitude and far distance may contain long period seismic waves which have small amplitude but with dominant period up to 10 sec. For a general situation, the long period seismic waves will not endanger the safety of the structural system or cause any uncomfortable for human activity. On the contrary, for those far distant earthquakes, this type of seismic waves may cause a glitch or, furthermore, breakdown to some important equipments/facilities (such as the high-precision facilities in high-tech Fab) and eventually damage the interests of company if the amplitude becomes significant. The previous study showed that the ground motion features such as time-variant dominant frequencies extracted using moving window singular spectrum analysis (MWSSA) and amplitude characteristics of long-period waves identified from slope change of ground motion Arias Intensity can efficiently indicate the damage severity to the high-precision facilities. However, embedding a large hankel matrix to extract long period seismic waves make the MWSSA become a time-consumed process. In this study, the seismic ground motion data collected from broadband seismometer network located in Taiwan were used (with epicenter distance over 1000 km). To monitor the significant long-period waves, the low frequency components of these seismic ground motion data are extracted using wavelet packet transform (WPT) to obtain wavelet coefficients and the wavelet entropy of coefficients are used to identify the amplitude characteristics of long-period waves. The proposed method is a timesaving process compared to MWSSA and can be easily implemented for real-time detection. Comparison and discussion on this method among these different seismic events and the damage severity to the high-precision facilities in high-tech Fab is made.
Directory of Open Access Journals (Sweden)
Lei Zhang
2016-01-01
Full Text Available In order to improve the fault detection accuracy for rolling bearings, an automated fault diagnosis system is presented based on lifting wavelet packet transform (LWPT, sample entropy (SampEn, and classifier ensemble. Bearing vibration signals are firstly decomposed into different frequency subbands through a three-level LWPT, resulting in a total of 8 frequency-band signals throughout the third layers of the LWPT decomposition tree. The SampEns of all the 8 components are then calculated as feature vectors. Such a feature extraction paradigm is expected to depict complexity, irregularity, and nonstationarity of bearing vibrations. Moreover, a novel classifier ensemble is proposed to alleviate the effect of initial parameters on the performance of member classifiers and to improve classification effectiveness. Experiments were conducted on electric motor bearings considering various set of fault categories and fault severity levels. Experimental results demonstrate the proposed diagnosis system can effectively improve bearing fault recognition accuracy and stability in comparison with diagnosis methods based on a single classifier.
Wang, Yi; Xu, Guanghua; Liang, Lin; Jiang, Kuosheng
2015-03-01
The kurtogram-based methods have been proved powerful and practical to detect and characterize transient components in a signal. The basic idea of the kurtogram-based methods is to use the kurtosis as a measure to discover the presence of transient impulse components and to indicate the frequency band where these occur. However, the performance of the kurtogram-based methods is poor due to the low signal-to-noise ratio. As the weak transient signal with a wide spread frequency band can be easily masked by noise. Besides, selecting signal just in one frequency band will leave out some transient features. Aiming at these shortcomings, different frequency bands signal fusion is adopted in this paper. Considering that manifold learning aims at discovering the nonlinear intrinsic structure which embedded in high dimensional data, this paper proposes a waveform feature manifold (WFM) method to extract the weak signature from waveform feature space which obtained by binary wavelet packet transform. Minimum permutation entropy is used to select the optimal parameter in a manifold learning algorithm. A simulated bearing fault signal and two real bearing fault signals are used to validate the improved performance of the proposed method through the comparison with the kurtogram-based methods. The results show that the proposed method outperforms the kurtogram-based methods and is effective in weak signature extraction.
Detecting the BAO using Discrete Wavelet Packets
Garcia, Noel Anthony; Wu, Yunyun; Kadowaki, Kevin; Pando, Jesus
2017-01-01
We use wavelet packets to investigate the clustering of matter on galactic scales in search of the Baryon Acoustic Oscillations. We do so in two ways. We develop a wavelet packet approach to measure the power spectrum and apply this method to the CMASS galaxy catalogue from the Sloan Digital Sky Survey (SDSS). We compare the resulting power spectrum to published BOSS results by measuring a parameter β that compares our wavelet detected oscillations to the results from the SDSS collaboration. We find that β=1 indicating that our wavelet packet methods are detecting the BAO at a similar level as traditional Fourier techniques. We then use wavelet packets to decompose, denoise, and then reconstruct the galaxy density field. Using this denoised field, we compute the standard two-point correlation function. We are able to successfully detect the BAO at r ≈ 105 h-1 Mpc in line with previous SDSS results. We conclude that wavelet packets do reproduce the results of the key clustering statistics computed by other means. The wavelet packets show distinct advantages in suppressing high frequency noise and in keeping information localized.
Cribbs, Michael R.
2015-01-01
Approved for public release; distribution is unlimited In this thesis, a software-defined radio (SDR) transmitter and receiver is developed using GNU Radio. The designed SDR multiplexes orthogonal subcarriers using wavelet packet modulation (WPM). WPM achieves subcarrier orthogonality by employing the inverse discrete wavelet packet transform (IDWPT) for the transmitter and discrete wavelet packet transform (DWPT) for the receiver. Realization concerns for the IDWPT and DWPT are discussed ...
Optimization and Assessment of Wavelet Packet Decompositions with Evolutionary Computation
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Schell Thomas
2003-01-01
Full Text Available In image compression, the wavelet transformation is a state-of-the-art component. Recently, wavelet packet decomposition has received quite an interest. A popular approach for wavelet packet decomposition is the near-best-basis algorithm using nonadditive cost functions. In contrast to additive cost functions, the wavelet packet decomposition of the near-best-basis algorithm is only suboptimal. We apply methods from the field of evolutionary computation (EC to test the quality of the near-best-basis results. We observe a phenomenon: the results of the near-best-basis algorithm are inferior in terms of cost-function optimization but are superior in terms of rate/distortion performance compared to EC methods.
Institute of Scientific and Technical Information of China (English)
曹玲燕; 胡铟; 贺枫
2014-01-01
Considering instability and incomplete deduction of the chromatographic baseline of transformer oil on-line monitoring system,a wavelet packet analysis-based baseline chromatographic signal reprocessing meth-od was proposed,which having wavelet packet used to implement multi-resolution decomposition and to deduct both low and high-frequency disturbance signals so as to obtain a chromatographic signal needed.The experi-mental results show that compared to the traditional wavelet transform,the wavelet packet analysis can do bet-ter in signal processing,reducing baseline interference and improving analysis precision and model stability.%针对变压器油色谱在线监测系统在现场使用中存在的色谱基线不稳定、扣除不完全等问题，提出了基于小波包分析的色谱信号预处理。该方法通过小波包对信号进行多分辨率分解，扣除部分干扰高、低频信号，得到所需要的色谱信号。实验结果表明：将小波包应用到色谱信号数据预处理中，相对于传统小波变换能更细致地进行信号分析，较好地进行色谱基线的扣除，减少基线对色谱信号的干扰，从而有效提高油色谱在线监测系统的分析精度和模型稳定性。
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
Ghahabi, Omid
2011-01-01
A fast, efficient and scalable algorithm is proposed, in this paper, for re-encoding of perceptually quantized wavelet-packet transform (WPT) coefficients of audio and high quality speech and is called "adaptive variable degree-k zero-trees" (AVDZ). The quantization process is carried out by taking into account some basic perceptual considerations, and achieves good subjective quality with low complexity. The performance of the proposed AVDZ algorithm is compared with two other zero-tree-based schemes comprising: 1- Embedded Zero-tree Wavelet (EZW) and 2- The set partitioning in hierarchical trees (SPIHT). Since EZW and SPIHT are designed for image compression, some modifications are incorporated in these schemes for their better matching to audio signals. It is shown that the proposed modifications can improve their performance by about 15-25%. Furthermore, it is concluded that the proposed AVDZ algorithm outperforms these modified versions in terms of both output average bit-rates and computation times.
Denoising in Wavelet Packet Domain via Approximation Coefficients
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Zahra Vahabi
2012-01-01
Full Text Available In this paper we propose a new approach in the wavelet domain for image denoising. In recent researches wavelet transform has introduced a time-Frequency transform for computing wavelet coefficient and eliminating noise. Some coefficients have effected smaller than the other's from noise, so they can be use reconstruct images with other subbands. We have developed Approximation image to estimate better denoised image. Naturally noiseless subimage introduced image with lower noise. Beside denoising we obtain a bigger compression rate. Increasing image contrast is another advantage of this method. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain.100 images of LIVE Dataset were tested, comparing signal to noise ratios (SNR,soft thresholding was %1.12 better than hard thresholding, POAC was %1.94 better than soft thresholding and POAC with wavelet packet was %1.48 better than POAC.
Institute of Scientific and Technical Information of China (English)
2007-01-01
An energy distribution theory was presented based on regular evolvement of energy fraction of acous-tic signals with fluidization velocity. Wavelet packet analysis was used in processing the acoustic sig-nals originated from particle impact on the wall of a fluidized bed. A new criterion of judging incipient fluidization(Umf) velocity and minimum turbulent velocity(Umt) was proposed according to the energy distribution theory. Experiments were performed with five groups of high density polyethylene(PE) particles and one bimodal PE to acquire incipient fluidization velocity and minimum turbulent velocity by using the criterion. The feasibility of this method in obtaining characteristic fluidization parameters was further verified by comparing it to results from the pressure drop method and the empirical value from industry.
Institute of Scientific and Technical Information of China (English)
WANG JingDai; YANG YongRong; GE PengFei; SHU WeiJie; HOU LinXi
2007-01-01
An energy distribution theory was presented based on regular evolvement of energy fraction of acoustic signals with fluidization velocity. Wavelet packet analysis was used in processing the acoustic signals originated from particle impact on the wall of a fluidized bed. A new criterion of judging incipient fluidization (Umf) velocity and minimum turbulent velocity (Umt) was proposed according to the energy distribution theory. Experiments were performed with five groups of high density polyethylene (PE)particles and one binodal PE to acquire incipient fluidization velocity and minimum turbulent velocity by using the criterion. The feasibility of this method in obtaining characteristic fluidization parameters was further verified by comparing it to results from the pressure drop method and the empirical value from industry.
ON CONVERGENCE OF WAVELET PACKET EXPANSIONS
Institute of Scientific and Technical Information of China (English)
Morten Nielsen
2002-01-01
It is well known that the-Walsh-Fourier expansion of a function from the block space ([0, 1 ) ), 1 ＜q≤∞, converges pointwise a.e. We prove that the same result is true for the expansion of a function from in certain periodixed smooth periodic non-stationary wavelet packets bases based on the Haar filters. We also consider wavelet packets based on the Shannon filters and show that the expansion of Lp-functions, 1＜p＜∞, converges in norm and pointwise almost everywhere.
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.
Goossens, Bart; Aelterman, Jan; Luong, Hiep; Pizurica, Aleksandra; Philips, Wilfried
2013-02-01
In digital cameras and mobile phones, there is an ongoing trend to increase the image resolution, decrease the sensor size and to use lower exposure times. Because smaller sensors inherently lead to more noise and a worse spatial resolution, digital post-processing techniques are required to resolve many of the artifacts. Color filter arrays (CFAs), which use alternating patterns of color filters, are very popular because of price and power consumption reasons. However, color filter arrays require the use of a post-processing technique such as demosaicing to recover full resolution RGB images. Recently, there has been some interest in techniques that jointly perform the demosaicing and denoising. This has the advantage that the demosaicing and denoising can be performed optimally (e.g. in the MSE sense) for the considered noise model, while avoiding artifacts introduced when using demosaicing and denoising sequentially. In this paper, we will continue the research line of the wavelet-based demosaicing techniques. These approaches are computationally simple and very suited for combination with denoising. Therefore, we will derive Bayesian Minimum Squared Error (MMSE) joint demosaicing and denoising rules in the complex wavelet packet domain, taking local adaptivity into account. As an image model, we will use Gaussian Scale Mixtures, thereby taking advantage of the directionality of the complex wavelets. Our results show that this technique is well capable of reconstructing fine details in the image, while removing all of the noise, at a relatively low computational cost. In particular, the complete reconstruction (including color correction, white balancing etc) of a 12 megapixel RAW image takes 3.5 sec on a recent mid-range GPU.
Directory of Open Access Journals (Sweden)
Yudong Zhang
2015-03-01
Full Text Available Background: Developing an accurate computer-aided diagnosis (CAD system of MR brain images is essential for medical interpretation and analysis. In this study, we propose a novel automatic CAD system to distinguish abnormal brains from normal brains in MRI scanning. Methods: The proposed method simplifies the task to a binary classification problem. We used discrete wavelet packet transform (DWPT to extract wavelet packet coefficients from MR brain images. Next, Shannon entropy (SE and Tsallis entropy (TE were harnessed to obtain entropy features from DWPT coefficients. Finally, generalized eigenvalue proximate support vector machine (GEPSVM, and GEPSVM with radial basis function (RBF kernel, were employed as classifier. We tested the four proposed diagnosis methods (DWPT + SE + GEPSVM, DWPT + TE + GEPSVM, DWPT + SE + GEPSVM + RBF, and DWPT + TE + GEPSVM + RBF on three benchmark datasets of Dataset-66, Dataset-160, and Dataset-255. Results: The 10 repetition of K-fold stratified cross validation results showed the proposed DWPT + TE + GEPSVM + RBF method excelled not only other three proposed classifiers but also existing state-of-the-art methods in terms of classification accuracy. In addition, the DWPT + TE + GEPSVM + RBF method achieved accuracy of 100%, 100%, and 99.53% on Dataset-66, Dataset-160, and Dataset-255, respectively. For Dataset-255, the offline learning cost 8.4430s and online prediction cost merely 0.1059s. Conclusions: We have proved the effectiveness of the proposed method, which achieved nearly 100% accuracy over three benchmark datasets.
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.
Directory of Open Access Journals (Sweden)
Ranganadh Narayanam
2015-10-01
Full Text Available The objective of this project is to discuss a versatile speech enhancement method based on the human auditory model. In this project a speech enhancement scheme is being described which meets the demand for quality noise reduction algorithms which are capable of operating at a very low signal to noise ratio. We will be discussing how proposed speech enhancement system is capable of reducing noise with little speech degradation in diverse noise environments. In this model to reduce the residual noise and improve the intelligibility of speech a psychoacoustic model is incorporated into the generalized perceptual wavelet denoising method to reduce the residual noise. This is a generalized time frequency subtraction algorithm which advantageously exploits the wavelet multirate signal representation to preserve the critical transient information. Simultaneous masking and temporal masking of the human auditory system are modeled by the perceptual wavelet packet transform via the frequency and temporal localization of speech components. To calculate the bark spreading energy and temporal spreading energy the wavelet coefficients are used from which a time frequency masking threshold is deduced to adaptively adjust the subtraction parameters of the discussed method. To increase the intelligibility of speech an unvoiced speech enhancement algorithm also integrated into the system.
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
Features of energy distribution for blast vibration signals based on wavelet packet decomposition
Institute of Scientific and Technical Information of China (English)
LING Tong-hua; LI Xi-bing; DAI Ta-gen; PENG Zhen-bin
2005-01-01
Blast vibration analysis constitutes the foundation for studying the control of blasting vibration damage and provides the precondition of controlling blasting vibration. Based on the characteristics of short-time nonstationary random signal, the laws of energy distribution are investigated for blasting vibration signals in different blasting conditions by means of the wavelet packet analysis technique. The characteristics of wavelet transform and wavelet packet analysis are introduced. Then, blasting vibration signals of different blasting conditions are analysed by the wavelet packet analysis technique using MATLAB; energy distribution for different frequency bands is obtained. It is concluded that the energy distribution of blasting vibration signals varies with maximum decking charge,millisecond delay time and distances between explosion and the measuring point. The results show that the wavelet packet analysis method is an effective means for studying blasting seismic effect in its entirety, especially for constituting velocity-frequency criteria.
On Generalized Carleson Operators of Periodic Wavelet Packet Expansions
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Shyam Lal
2013-01-01
Full Text Available Three new theorems based on the generalized Carleson operators for the periodic Walsh-type wavelet packets have been established. An application of these theorems as convergence a.e. for the periodic Walsh-type wavelet packet expansion of block function with the help of summation by arithmetic means has been studied.
Directory of Open Access Journals (Sweden)
Guiji Tang
2016-01-01
Full Text Available A novel method of fault diagnosis for rolling bearing, which combines the dual tree complex wavelet packet transform (DTCWPT, the improved multiscale permutation entropy (IMPE, and the linear local tangent space alignment (LLTSA with the extreme learning machine (ELM, is put forward in this paper. In this method, in order to effectively discover the underlying feature information, DTCWPT, which has the attractive properties as nearly shift invariance and reduced aliasing, is firstly utilized to decompose the original signal into a set of subband signals. Then, IMPE, which is designed to reduce the variability of entropy measures, is applied to characterize the properties of each obtained subband signal at different scales. Furthermore, the feature vectors are constructed by combining IMPE of each subband signal. After the feature vectors construction, LLTSA is employed to compress the high dimensional vectors of the training and the testing samples into the low dimensional vectors with better distinguishability. Finally, the ELM classifier is used to automatically accomplish the condition identification with the low dimensional feature vectors. The experimental data analysis results validate the effectiveness of the presented diagnosis method and demonstrate that this method can be applied to distinguish the different fault types and fault degrees of rolling bearings.
Cai, Chen-Bo; Xu, Lu; Han, Qing-Juan; Wu, Hai-Long; Nie, Jin-Fang; Fu, Hai-Yan; Yu, Ru-Qin
2010-05-15
The paper focuses on solving a common and important problem of NIR quantitative analysis in multi-component systems: how to significantly reduce the size of the calibration set while not impairing the predictive precision. To cope with the problem orthogonal discrete wavelet packet transform (WPT), the least correlation design and correlation coefficient test (r-test) have been combined together. As three examples, a two-component carbon tetrachloride system with 21 calibration samples, a two-component aqueous system with 21 calibration samples, and a two-component aqueous system with 41 calibration samples have been treated with the proposed strategy, respectively. In comparison with some previous methods based on much more calibration samples, the results out of the strategy showed that the predictive ability was not obviously decreased for the first system while being clearly strengthened for the second one, and the predictive precision out of the third one was even satisfactory enough for most cases of quantitative analysis. In addition, all important factors and parameters related to our strategy are discussed in detail.
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.
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.
Some Results on the Wavelet Packet Decomposition of Nonstationary Processes
Directory of Open Access Journals (Sweden)
Touati Sami
2002-01-01
Full Text Available Wavelet/wavelet packet decomposition has become a very useful tool in describing nonstationary processes. Important examples of nonstationary processes encountered in practice are cyclostationary processes or almost-cyclostationary processes. In this paper, we study the statistical properties of the wavelet packet decomposition of a large class of nonstationary processes, including in particular cyclostationary and almost-cyclostationary processes. We first investigate in a general framework, the existence and some properties of the cumulants of wavelet packet coefficients. We then study more precisely the almost-cyclostationary case, and determine the asymptotic distributions of wavelet packet coefficients. Finally, we particularize some of our results in the cyclostationary case before providing some illustrative simulations.
Carracciuolo, Luisa; D'Amore, Luisa; Murli, Almerico
1998-10-01
We explore the filtering properties of wavelets functions in order to develop accurate and efficient numerical algorithms for Image Restoration problems. We propose a parallel implementation for MIMD distributed memory environments. The key insight of our approach is the use of distributed versions of Level 3 Basic Linear Algebra Subprograms as computational building blocks and the use of Basic Linear Algebra Communication Subprograms as communication building blocks for advanced architecture computers. The use of these low-level mathematical software libraries guarantees the development of efficient, portable and scalable high-level algorithms and hides many details of the parallelism from the user's point of view. Numerical experiments on a simulated image restoration applications are shown. The parallel software has been tested on a 12 nodes IBM SP2 available at the Center for Research on Parallel Computing and Supercomputers in Naples, Italy).
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.
Implemented Wavelet Packet Tree based Denoising Algorithm in Bus Signals of a Wearable Sensorarray
Schimmack, M.; Nguyen, S.; Mercorelli, P.
2015-11-01
This paper introduces a thermosensing embedded system with a sensor bus that uses wavelets for the purposes of noise location and denoising. From the principle of the filter bank the measured signal is separated in two bands, low and high frequency. The proposed algorithm identifies the defined noise in these two bands. With the Wavelet Packet Transform as a method of Discrete Wavelet Transform, it is able to decompose and reconstruct bus input signals of a sensor network. Using a seminorm, the noise of a sequence can be detected and located, so that the wavelet basis can be rearranged. This particularly allows for elimination of any incoherent parts that make up unavoidable measuring noise of bus signals. The proposed method was built based on wavelet algorithms from the WaveLab 850 library of the Stanford University (USA). This work gives an insight to the workings of Wavelet Transformation.
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
Institute of Scientific and Technical Information of China (English)
胥永刚; 孟志鹏; 陆明
2013-01-01
The operation states of rolling bearings which are the most common and important parts in the mechanical equipment, will affect the whole machine operation condition directly. Due to the working environment of rolling, bearing is complicated, the fault vibration signal of rolling bearing is usually non-stationary, and the strong noise interference is contained in the vibration signal at the same time. So it is important to eliminate the noise interference and extract fault feature information effectively for the rolling bearing. Dual-tree complex wavelet packet transform is a new method of signal processing. Dual-tree complex wavelet packet transform has many good characteristics, for example, approximate shift invariance, good directional selectivity、perfect reconstruction, limited data redundancy, efficient computational efficiency and so on. The high frequency part of dual-tree complex wavelet transform that is not decomposed, is further decomposed by dual-tree complex wavelet packet transform, so as to improve the whole frequency band signal frequency resolution and reduce the loss of information. In view of the above situation, a new fault diagnosis method is proposed based on dual-tree complex wavelet packet transform and threshold de-noising. Firstly, the non-stationary fault signal is decomposed into several different frequency band components through dual-tree complex wavelet packet decomposition. Secondly, Kurtosis and the cross-correlation coefficient of each component are obtained and compared. Due to the kurtosis reflecting the signal variations, if the kurtosis value is bigger, the degree of the change of signal is bigger too. The correlation coefficient can reflect the proximity between the component and the original signal at the same time, the correlation coefficient is bigger, the more similar with the original signal. Finally, the components that have a bigger value are chosen to be de-noised by a soft threshold and reconstructed by dual
Law, Leh-Sung; Kim, Jong Hyun; Liew, Willey Y. H.; Lee, Sun-Kyu
2012-11-01
In order to prevent possible damages to the spindle systems, reliable monitoring techniques are required to provide valuable information on the condition of the spindle condition. A technique is proposed for monitoring spindle bearings conditions via the use of acoustic emission (AE) signals, which implements Hilbert-Huang transform (HHT) analysis to extract the crucial characteristic from the measured data to correlate spindle running condition. The HHT becomes a promising technique in extracting the properties of nonlinear and non-stationary signal. However, the original HHT has several deficiencies, which eventually lead to misinterpretation to the final results. The improved version of HHT is proposed and used to overcome the weakness of the original HHT. The simulation and experimental results are used to verify the effectiveness of the WPD-HHT and therefore Hilbert marginal spectral, compared to traditional Fourier transform. Experimental results are presented to examine and explore the effectiveness of AE for monitoring spindle bearings conditions. It is concluded that good correlation existed between the results obtained by AE data and the increase in the preload, and change in the dimensions and geometry of the spindle bearings and their housings as the temperature increases. In support of this finding, vibration and acceleration data are also used to assess the amount changes in the antistrophic stiffness and radial error motion.
Institute of Scientific and Technical Information of China (English)
张雯雯; 刘黎平
2009-01-01
The method of adaptive denoising based on discrete wavelet transform (DWT) provides a feasible solution for radar signal filtering, but DWT does not have the characteristics of translation invariance of the wavelet coefficients. If signal reconstruction is not done with the same wavelet, it will cause considerable reconstruction errors.To deal with this phenomenon, this paper proposes an adaptive denoising method based on lifting static wavelet packet transformation. The authors developed the lifting method for static wavelet packets, and designed corresponding steps to determine optimal wavelet packet trees suitable for this system. They then conducted adaptive matching to each sub-band using a weighted coefficient iterative formula which has more momentum factors. Finally , a second adaptive filter of the matching results was used to acquire the fitted signal. Simulation results show that the method improves filtering performance without substantially increasing calculations.%基于离散小波变换(DWT)的自适应消噪方法为雷达信号的滤波提供了一种可行的方法.但DWT不具有平移不变性,若不用相同的小波对滤波后的信号进行重构,则会带来较大的重构误差.针对这一现象,提出了一种基于提升静态小波包变换的自适应消噪方法,它推导了静态小波包的提升实现方法,并设计出适合该系统的确定最优小波包分解树的相应步骤,利用引入更多动量因子的权系数迭代公式对各子带进行自适应匹配,并将匹配结果二次自适应,得到拟合的原信号.仿真结果表明,该方法可在计算量增加不大的前提下,进一步改善系统的滤波性能.
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 ...
离散余弦小波包变换及语音信号压缩感知%Discrete cosine wavelet packet transform and compressed sensing for speech signal
Institute of Scientific and Technical Information of China (English)
张长青; 陈砚圃
2014-01-01
针对语音信号压缩感知问题,在研究语音离散余弦变换(Discrete Cosine Transform,DCT)系数和小波包变换(Wavelet Packet Transform,WPT)特性的基础上构造了离散余弦小波包变换(Discrete Cosine Wavelet Packet Transform,DCWPT).DCWPT首先获取语音信号的DCT域系数,结合语音频谱特性选取部分DCT系数进行WPT变换,从而得到比DCT系数更加稀疏的DCWPT系数.为将此变换直接用于压缩感知,构造了DCWPT的正交稀疏分解矩阵并分析了其稀疏表示性能.结合稀疏表示基优化了正交匹配追踪重构算法,提出了基于DCWPT的语音信号压缩感知框架.通过压缩重构对照实验,采用主客观评价指标,得出该方法优于传统基于DCT的语音压缩感知方法的结论.
Printed Persian Subword Recognition Using Wavelet Packet Descriptors
Directory of Open Access Journals (Sweden)
Samira Nasrollahi
2013-01-01
Full Text Available In this paper, we present a new approach to offline OCR (optical character recognition for printed Persian subwords using wavelet packet transform. The proposed algorithm is used to extract font invariant and size invariant features from 87804 subwords of 4 fonts and 3 sizes. The feature vectors are compressed using PCA. The obtained feature vectors yield a pictorial dictionary for which an entry is the mean of each group that consists of the same subword with 4 fonts in 3 sizes. The sets of these features are congregated by combining them with the dot features for the recognition of printed Persian subwords. To evaluate the feature extraction results, this algorithm was tested on a set of 2000 subwords in printed Persian text documents. An encouraging recognition rate of 97.9% is got at subword level recognition.
DESIGN OF WAVELET PACKET BASED MODEL FOR MULTI CARRIER MODULATION
Directory of Open Access Journals (Sweden)
MIHIR NARAYAN MOHANTY
2012-04-01
Full Text Available In current scenario Multi-Carrier modulation (MCM is considered an effective technique for both wire and wireless communications. It divides the entire bandwidth into several parallel sub-channels. This splitting is by dividing the transmit data into several parallel low-bit-rate data streams and then to modulate the carrierscorresponding to those sub-channels. Though MCM technique uses Orthogonal Frequency Division Multiplexing (OFDM model, it is very sensitive to Carrier Frequency Offset (CFO, that leads to a severedistortion in subcarrier orthogonality and causes inter channel interference (ICI. In this paper, Wavelet Packet Transform is designed for the model of MCM as a novel alternative to the most exiting Orthogonal Frequency Division Multiplexing (OFDM technique, because of its time frequency representation and lower side lobes intransmitted signals, that reduces inter carrier interference (ICI, and inter symbol interference (ISI. Performance analysis is investigated for such model. Simulation results show a significant enhancement in terms of spectral efficiency.
A Packetized SPIHT Algorithm with Overcomplete Wavelet Coefficients for Increased Robustness
Directory of Open Access Journals (Sweden)
Sriraja Y
2006-01-01
Full Text Available This paper presents a wavelet-based image encoding scheme with error resilience and error concealment suitable for transmission over networks prone to packet losses. The scheme involves partitioning the data into independent descriptions of roughly equal lengths, achieved by a combination of packetization and modifications to the wavelet tree structure without additional redundancy. With a weighted-averaging-based interpolation method, our proposed encoding scheme attains an improvement of about 0.5–1.5 dB in PSNR over other similar methods. We also investigate the use of overcomplete wavelet transform coefficients as side information for our encoding scheme to improve the error resilience when severe packet losses occur. Experiments show that we are able to achieve a high coding performance along with a good perceptual quality for the reconstructed image.
Institute of Scientific and Technical Information of China (English)
孔德照; 林超; 沈学举; 王昕; 周晗
2013-01-01
提出一种基于小波包变换(WPT)的分数阶光学图像加密方法.利用WPT能够对图像多层次分解的特性,结合分数傅里叶变换(FRFT)的灵活性,将双随机相位、小波函数的类型及尺度因子和分数阶次作为密钥,实现了图像的多重密钥加解密.同时,实现了图像小波域上的选择性加密,使加密样式变得更灵活多样,还增强了加密图像的抵抗恶意的攻击能力.数值模拟了加密和解密过程,分析了加密效果和解密图像质量,验证了本文方法的可行性.%A novel method for the optical image encryption is presented, which is based on the wavelet packet transform (WPT) and fractional Fourier transform (FRFT). The idea of combining WPT with FRFT comes from the study of properties of them. Images can be decomposed by wavelet packet transform. With the increase in the order of WPT,the image will be decomposed into more parts,of which each contains the essential information. Based on the good property of WPT and the flexibility of FRFT, the method implicates encryption and decryption of the image and produces many keys, consisting of double random phase masks,the order of WPT and the order of FRFT. Meanwhile,the selected-image-encryption in wavlet domain is realized in this paper,which varies the patterns of encryptioa The method improves the security,and the ability of resisting malicious attacks is also enhanced. The encryption and decryption are implicated by numerical simulation. The result of the simulation provides the requirement for analyzing the properties of encryption and decryptioa The feasibility and simplicity of the method are verified by numerical simulation,and a simple optical implication of the method is also proposed. Based on the numerical simulation and theroy analysis,it can be confluded that the method for the optical image encryption is novel and effective.
DIESEL ENGINES' VIBROACOUSTIC SIGNATURE EXTRACTION BY WAVELET PACKET TECHNIQUE
Institute of Scientific and Technical Information of China (English)
邹剑; 陈进; 邹军; 耿遵敏
2002-01-01
Multisource unstable impulsive excitations, time-varying transmission path, concentrated mode, dispersion and reverberation that are important characteristics of reciprocating machines such as diesel engines result in wide-band non-stationary vibroacoustic responses which influence the effective extraction of vibroacoustic signatures and become a key factor to limit diesel engines' vibration diagnosis. In this paper, a serial theoretical deduction on the unstable dynamic properties of diesel engines was made; the mechanism of non-stationary vibroacoustic responses was elucidated. Based upon that, the wavelet packet technique was introduced. The reason for the existence of frequency aliasing in the Paley series from wavelet packets' decomposition was analyzed, and the wavelet packet frequency-shifting algorithm was given. Experiments on 190 serial diesel engines verify the given method's significant validity in vibroacoustic signature extraction and reciprocating machines' vibration diagnosis.
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.
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.
Wavelet packet based feature extraction and recognition of license plate characters
Institute of Scientific and Technical Information of China (English)
HUANG Wei; LU Xiaobo; LING Xiaojing
2005-01-01
To study the characteristics of license plate characters recognition, this paper proposes a method for feature extraction of license plate characters based on two-dimensional wavelet packet. We decompose license plate character images with two dimensional-wavelet packet and search for the optimal wavelet packet basis. This paper presents a criterion of searching for the optimal wavelet packet basis, and a practical algorithm. The obtained optimal wavelet packet basis is used as the feature of license plate character, and a BP neural network is used to classify the character.The testing results show that the proposed method achieved higher recognition rate than the traditional methods.
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.
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.
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.
基于小波包变换的电磁超声接收信号特征提取%Feature Extraction of EMAT Received Signal Based on Wavelet Packet Transform
Institute of Scientific and Technical Information of China (English)
蔡强富; 陈鹏; 韩德来
2013-01-01
This paper used the improved power spectrum to qualitative analysis the electromagnetic ultrasonic flaw signals,followed by the energy spectrum of wavelet packet distill the electromagnetic ultrasonic flaw received signal feature, discusing and analyzing the characteristic parameters from wavelet packet wavelet function selected,decomposition level and noise robustness. The results show that;through selectting the appropriate wavelet function and wavelet packet decomposition level,wavelet packet energy spectrum of energy ratio can subtly reflect the characteristics of the signal;The wavelet packet energy spectrum of characteristic parameters have good damnification-sensitive and noise-robustness, besides, which can distinguish the EMAT different types of injury under the strong noise.%使用改进的功率谱函数对电磁超声缺陷信号进行了缺陷的定性分析,使用小波包能量谱对电磁超声缺陷接收信号进行了特征提取,从小波包的小波函数选取、分解层次及特征参数的噪声鲁棒性3个方面开展了讨论分析.结果表明:通过选择适当的小波函数和小波包分解层次,小波包能量谱的能量比可以精细地反映信号的特征；基于小波包能量谱的特征参数具有良好的损伤敏感性及噪声鲁棒性,能在强噪声影响下实现对EMAT不同损伤类型的判别.
A wavelet packet based block-partitioning image coding algorithm with rate-distortion optimization
Institute of Scientific and Technical Information of China (English)
YANG YongMing; XU Chao
2008-01-01
As an elegant generalization of wavelet transform, wavelet packet (WP) provides an effective representation tool for adaptive waveform analysis. Recent work shows that image-coding methods based on WP decomposition can achieve significant gain over those based on a usual wavelet transform. However, most of the work adopts a tree-structured quantization scheme, which is a successful technique for wavelet image coding, but not appropriate for WP subbands. This paper presents an image-coding algorithm based on a rate-distortion optimized wavelet packet decomposition and on an intraband block-partitioning scheme. By encoding each WP subband separately with the block-partitioning algorithm and the JPEG2000 context modeling, the proposed algorithm naturally avoids the difficulty in defining parent-offspring relationships for the WP coefficients, which has to be faced when adopting the tree-structured quantization scheme. The experimental results show that the proposed algorithm significantly outperforms SPIHT and JPEG2000 schemes and also surpasses state-of-the-art WP image coding algorithms, in terms of both PSNR and visual quality.
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。
Structural safety criteria for blasting vibration based on wavelet packet energy spectra
Institute of Scientific and Technical Information of China (English)
Zhong Guosheng; Li Jiang; Zhao Kui
2011-01-01
Given multi-resolution decomposition of wavelet packet transforms, wavelet packet frequency band energy has been deduced from different bands of blasting vibration signals. Our deduction reflects the total effect of all three key elements (intensity, frequency and duration of vibration) of blasting vibration.We considered and discuss the dynamic response of structures and the effect of inherent characteristics of controlled structures to blasting vibration. Frequency band response coefficients for controlled structures by blasting vibration have been obtained. We established multi-factor blasting vibration safety criteria, referred to as response energy criteria. These criteria reflect the total effect of intensity,frequency and duration of vibration and the inherent characteristics (natural frequency and damping ratio) of dynamic responses from controlled structures themselves. Feasibility and reliability of the criteria are validated by an example.
A NOVEL METHOD FOR NETWORK WORM DETECTION BASED ON WAVELET PACKET ANALYSIS
Institute of Scientific and Technical Information of China (English)
Liao Mingtao; Zhang Deyun; Hou Lin
2006-01-01
Objective To detect unknown network worm at its early propagation stage. Methods On the basis of characteristics of network worm attack, the concept of failed connection flow (FCT) was defined. Based on wavelet packet analysis of FCT time series, this method computed the energy associated with each wavelet packet of FCT time series, transformed the FCT time series into a series of energy distribution vector on frequency domain, then a trained K-nearest neighbor (KNN) classifier was applied to identify the worm. Results The experiment showed that the method could identify network worm when the worm started to scan. Compared to theoretic value, the identification error ratio was 5.69%. Conclusion The method can detect unknown network worm at its early propagation stage effectively.
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 ...
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
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.
Structural health monitoring of long-span suspension bridges using wavelet packet analysis
Institute of Scientific and Technical Information of China (English)
Ding Youliang; Li Aiqun
2007-01-01
During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage. This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform (WPT). The WPTbased method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum (WPES) has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices VD reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index VD is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations.
Structural health monitoring of long-span suspension bridges using wavelet packet analysis
Ding, Youliang; Li, Aiqun
2007-09-01
During the service life of civil engineering structures such as long-span bridges, local damage at key positions may continually accumulate, and may finally result in their sudden failure. One core issue of global vibration-based health monitoring methods is to seek some damage indices that are sensitive to structural damage. This paper proposes an online structural health monitoring method for long-span suspension bridges using wavelet packet transform (WPT). The WPT-based method is based on the energy variations of structural ambient vibration responses decomposed using wavelet packet analysis. The main feature of this method is that the proposed wavelet packet energy spectrum (WPES) has the ability to detect structural damage from ambient vibration tests of a long-span suspension bridge. As an example application, the WPES-based health monitoring system is used on the Runyang Suspension Bridge under daily environmental conditions. The analysis reveals that changes in environmental temperature have a long-term influence on the WPES, while the effect of traffic loadings on the measured WPES of the bridge presents instantaneous changes because of the nonstationary properties of the loadings. The condition indication indices V D reflect the influences of environmental temperature on the dynamic properties of the Runyang Suspension Bridge. The field tests demonstrate that the proposed WPES-based condition indication index V D is a good candidate index for health monitoring of long-span suspension bridges under ambient excitations.
Directory of Open Access Journals (Sweden)
Imaouchen Yacine
2015-01-01
Full Text Available To detect rolling element bearing defects, many researches have been focused on Motor Current Signal Analysis (MCSA using spectral analysis and wavelet transform. This paper presents a new approach for rolling element bearings diagnosis without slip estimation, based on the wavelet packet decomposition (WPD and the Hilbert transform. Specifically, the Hilbert transform first extracts the envelope of the motor current signal, which contains bearings fault-related frequency information. Subsequently, the envelope signal is adaptively decomposed into a number of frequency bands by the WPD algorithm. Two criteria based on the energy and correlation analyses have been investigated to automate the frequency band selection. Experimental studies have confirmed that the proposed approach is effective in diagnosing rolling element bearing faults for improved induction motor condition monitoring and damage assessment.
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.
Lakshmanan, M.K.
2011-01-01
Wavelet Packet Modulation (WPM) is a multi-carrier transmission technique that uses orthogonal wavelet packet bases to combine a collection of information bits into a single composite signal. This system can be considered as a viable alternative, for wide-band communication, to the popular
Lakshmanan, M.K.
2011-01-01
Wavelet Packet Modulation (WPM) is a multi-carrier transmission technique that uses orthogonal wavelet packet bases to combine a collection of information bits into a single composite signal. This system can be considered as a viable alternative, for wide-band communication, to the popular Orthogona
Institute of Scientific and Technical Information of China (English)
胥永刚; 孟志鹏; 赵国亮; 付胜
2014-01-01
为有效利用双树复小波包变换提取齿轮故障特征信息，提出基于双树复小波包能量泄漏特性分析的故障诊断方法。首先根据高斯白噪声频率充满整个频带的特性，通过双树复小波包变换对高斯白噪声进行分解，利用频带能量泄漏的定量分析方法，验证了双树复小波包变换具有较低的频带能量泄漏特性；其次利用双树复小波包变换逐层分解信号，对每层分解所得分量求其FFT谱的峭度，得到基于双树复小波包变换的谱峭度图，根据图中峭度最大的原则，可以自动准确的选择信号分解最佳层数和最佳分量；最后将基于双树复小波包变换的谱峭度图的故障诊断方法应用于实际工程中，对齿轮故障振动信号进行分析，选择最佳分解层数和分量后利用希尔伯特包络解调，有效准确地提取了故障特征信息，验证了方法的可行性和有效性。该研究可为旋转机械设备中齿轮箱故障诊断的故障特征提取提供参考。%The gear is the key component of rotating machinery, so a fault in the gear will directly affect the condition of the whole machine’s operation. It was difficult to extract the fault feature information effectively from the vibration signals of a faulty gear. In the field of fault diagnosis, envelope demodulation was one of the most common signal processing methods. However, a filtering process was required before envelope demodulation. The parameters of a filter were determined by experience, and that has a great influence on the results of signal processing. The discrete wavelet packet transform has a larger energy leakage of frequency band, which obviously affected the results of the envelope demodulation. It is necessary to have a method with a lower energy leakage of the frequency band before envelope demodulation. The dual tree complex wavelet packet transform (DT-CWPT) was a new signal processing method that had many
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.
Detecting emboli from Doppler ultrasound signals with the wavelet packet analysis method
Institute of Scientific and Technical Information of China (English)
CHEN Xi; SUN Zhimin; WANG Yuanyuan; WANG Weiqi
2004-01-01
A Doppler ultrasound analysis method based on wavelet package transform was proposed for embolic detection. The embolic Doppler signal was firstly decomposed using the wavelet packet. Then the sensitive characteristics were calculated from each sub-band signal and used in the emboli classification. This method was applied to analyze 300 cases simulated and 163 cases clinical Doppler signals. The minimum error ratio of embolic detection using this method was 13 percents lower than that using the traditional spectrogram analysis method.It was shown that this method overcame the limit between the time and frequency resolution in the short time Fourier transform, improved the accuracy of embolic detection greatly and extracted more reliable parameters for the clinical diagnosis.
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.
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.
Detection of broken rotor bars in induction machines: An approach using wavelet packets in MCSA
Escobar-Moreira, León; Antonino-Daviu, José; Riera-Guasp, Martin
2012-12-01
Bar breaking diagnosis in electrical induction cage motors is a topic of interest due to their extensive use in industry. In contrast to the typical method of using Fourier analysis of the steady-state stator current, Discrete Wavelet Transform (DWT) methods have been found to better analyze the time changing nature of the current spectrum of these machines at start-up when broken bars exist [1]. This paper advances the analysis to Wavelet Packets (WP) in order to study the high order harmonic components of the spectrum which constitute a useful source of information in situations where tracing the low-frequency fault harmonics (sideband components) may not reach a definite diagnostic (i.e. presence of low-frequency load torque oscillations, effect of inter-bar currents, etc...).
Application of Wavelet Packet Energy Spectrum to Extract the Feature of the Pulse Signal
Institute of Scientific and Technical Information of China (English)
Dian-guo CAO; Yu-qiang WU; Xue-wen SHI; Peng WANG
2010-01-01
The wavelet packet is presented as a new kind of multi-scale analysis technique followed by Wavelet analysis. The fundamental and realization arithmetic of the wavelet packet analysis method are described in this paper. A new application approach of the wavelet packed method to extract the feature of the pulse signal from energy distributing angle is expatiated. It is convenient for the microchip to process and judge by using the wavelet packet analysis method to make the pulse signals quantized and analyzed. Kinds of experiments are simulated in the lab, and the experiments prove that it is a convenient and accurate method to extract the feature of the pulse signal based on wavelet packed-energy spectrum analysis.
Fault Diagnosis of a Turbo-unit Based on Wavelet Packet Theory
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
In this paper we studied the fault feature of the generator set and the characteristics of wavelet packet theory for signal de-noising. The vibration signal of the generator set in diffrent states is analyzed by using the signal re-construction technique of the wavelet packet theory. The time domain method is given for the generator set fault diagnosis. The experiment results show that the wavelet packet theory can be used to directly identify the state of the generator set and provide a credible new idea for complex machinery fault diagnosis.
Kim, Eui-Youl; Lee, Young-Joon; Lee, Sang-Kwon
2012-07-01
This paper presents the fault detect method of a moving transfer robot in the mass production line of liquid crystal display (LCD) manufacturers based on the wavelet packet transform (WPT) for feature extraction and the artificial neural network (ANN) for fault classification. Most of fault detection methods in a mechanical system have been researched based on the vibration signal. Unlike the existing methodologies, this study aims to minimize the uncertainty of a field engineer's decision making process for determining whether a fault is present or not based on the human auditory perception by developing a fault diagnosis system that uses the abnormal operating sound radiated from a moving transfer robot as a source signal. Abnormal operating sound radiated from a moving transfer robot has been used for this work instead of other source signals such as vibration, acoustic emission, electrical signal, etc. Its advantage as a source signal makes it possible to monitor the status of multiple faults by using only a microphone despite a relatively low sensitivity. In the application of ANN, since it is important to minimize the error of trained ANN in terms of the accuracy of fault diagnosis logic, in the paper, the number of input and target data samples was increased through a regeneration process based on statistical properties, and then the uncorrelated nodes in the input vector were also removed to improve the orthogonality of the input vector based on the entropy based feature selection method. Consequently, it can be concluded that the abnormal operating sound is sufficiently useful as a source signal for the fault diagnosis of mechanical components as well as other source signals.
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.
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
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.
A Generalization of the Mean Size Formula of Wavelet Packets in Lp
Institute of Scientific and Technical Information of China (English)
Song LI; Guo Mao WANG; Zhi Song LIU
2005-01-01
The purpose of this paper is to investigate the mean size formula of wavelet packets in Lp for 0 ＜ p ≤∞. We generalize a mean size formula of wavelet packets given in terms of the p-norm joint spectral radius and we also give some asymptotic formulas for the Lp-norm or quasi-norm on the subdivision trees. All results will be given in the general setting.
Institute of Scientific and Technical Information of China (English)
任芳; 杨兆建; 熊诗波; 梁义维
2003-01-01
The theory and method of wavelet packet decomposition and its energy spectrum dealing with the coal-rock Interface Identification are presented in the paper. The characteristic frequency band of the coal-rock signal could be identified by wavelet packet decomposition and its energy spectrum conveniently, at the same time, quantification analysis were performed. The result demonstrates that this method is more advantageous and of practical value than traditional Fourier analysis method.
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.
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.
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.
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.
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
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.
Adaptive wavelet packet-based de-speckling of ultrasound images with bilateral filter.
Esakkirajan, Sankaralingam; Vimalraj, Chinna Thambi; Muhammed, Rashad; Subramanian, Ganapathi
2013-12-01
A new adaptive wavelet packet-based approach to minimize speckle noise in ultrasound images is proposed. This method combines wavelet packet thresholding with a bilateral filter. Here, the best bases after wavelet packet decomposition are selected by comparing the first singular value of all sub-bands, and the noisy coefficients are thresholded using a modified NeighShrink technique. The algorithm is tested with various ultrasound images, and the results, in terms of peak signal-to-noise ratio and mean structural similarity values, are compared with those for some well-known de-speckling techniques. The simulation results indicate that the proposed method has better potential to minimize speckle noise and retain fine details of the ultrasound image. Copyright © 2013 World Federation for Ultrasound in Medicine & Biology. All rights reserved.
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.
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.
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.
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
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.
Chen, Xiaoguang; Liu, Dan; Xu, Guanghua; Jiang, Kuosheng; Liang, Lin
2014-12-26
For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal classification technique, wavelet packet entropy (WPEntropy) flow manifold learning, for the evaluation of bearing factory quality. The data were analyzed using wavelet packet entropy (WPEntropy) flow manifold learning. The results showed that the ultrasonic technique with WPEntropy flow manifold learning was able to detect different types of defects on the bearing components. The test method and the proposed technique are described and the different signals are analyzed and discussed.
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.
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
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.
Chen, H. X.; Chua, Patrick S. K.; Lim, G. H.
2008-10-01
The machinery fault diagnosis is important for improving reliability and performance of systems. Many methods such as Time Synchronous Average (TSA), Fast Fourier Transform (FFT)-based spectrum analysis and short-time Fourier transform (STFT) have been applied in fault diagnosis and condition monitoring of mechanical system. The above methods analyze the signal in frequency domain with low resolution, which is not suitable for non-stationary vibration signal. The Kolmogorov-Smirnov (KS) test is a simple and precise technique in vibration signal analysis for machinery fault diagnosis. It has limited use and advantage to analyze the vibration signal with higher noise directly. In this paper, a new method for the fault degradation assessment of the water hydraulic motor is proposed based on Wavelet Packet Analysis (WPA) and KS test to analyze the impulsive energy of the vibration signal, which is used to detect the piston condition of water hydraulic motor. WPA is used to analyze the impulsive vibration signal from the casing of the water hydraulic motor to obtain the impulsive energy. The impulsive energy of the vibration signal can be obtained by the multi-decomposition based on Wavelet Packet Transform (WPT) and used as feature values to assess the fault degradation of the pistons. The kurtosis of the impulsive energy in the reconstructed signal from the Wavelet Packet coefficients is used to extract the feature values of the impulse energy by calculating the coefficients of the WPT multi-decomposition. The KS test is used to compare the kurtosis of the impulse energy of the vibration signal statistically under the different piston conditions. The results show the applicability and effectiveness of the proposed method to assess the fault degradation of the pistons in the water hydraulic motor.
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.
An investigation on the sensitivity of wavelet packet modulation to time synchronization error
Lakshmanan, M.K.; Karamehmedovic, D.; Nikookar, H.
2010-01-01
Wavelet Packet based Multi-Carrier Modulation (WPMCM) offers an alternative to the well-established OFDM as an efficient multicarrier modulation technique. It has the advantage of being a generic transmission scheme whose actual characteristics can be widely customized to fulfill several requirement
Content-Adaptive Packetization and Streaming of Wavelet Video over IP Networks
Directory of Open Access Journals (Sweden)
Chien-Peng Ho
2007-03-01
Full Text Available This paper presents a framework of content-adaptive packetization scheme for streaming of 3D wavelet-based video content over lossy IP networks. The tradeoff between rate and distortion is controlled by jointly adapting scalable source coding rate and level of forward error correction (FEC protection. A content dependent packetization mechanism with data-interleaving and Reed-Solomon protection for wavelet-based video codecs is proposed to provide unequal error protection. This paper also tries to answer an important question for scalable video streaming systems: given extra bandwidth, should one increase the level of channel protection for the most important packets, or transmit more scalable source data? Experimental results show that the proposed framework achieves good balance between quality of the received video and level of error protection under bandwidth-varying lossy IP networks.
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Based on wavelet packet decomposition (WPD) algorithm and Teager energy operator (TEO), a novel gearbox fault detection and diagnosis method is proposed. Its process is expatiated after the principles of WPD and TEO modulation are introduced respectively. The preprocessed signal is interpolated with the cubic spline function, then expanded over the selected basis wavelets. Grouping its wavelet packet components of the signal based on the minimum entropy criterion, the interpolated signal can be decomposed into its dominant components with nearly distinct fault frequency contents. To extract the demodulation information of each dominant component, TEO is used. The performance of the proposed method is assessed by means of several tests on vibration signals collected from the gearbox mounted on a heavy truck. It is proved that hybrid WPD-TEO method is effective and robust for detecting and diagnosing localized gearbox faults.
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.
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.
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
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.
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.
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.
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.
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.
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.
Institute of Scientific and Technical Information of China (English)
WANG Pan-pan; SHI Li-ping; HU Yong-jun; MIAO Chang-xin
2012-01-01
To effectively extract the interturn short circuit fault features of induction motor from stator current signal,a novel feature extraction method based on the bare-bones particle swarm optimization (BBPSO) algorithm and wavelet packet was proposed.First,according to the maximum inner product between the current signal and the cosine basis functions,this method could precisely estimate the waveform parameters of the fundamental component using the powerful global search capability of the BBPSO,which can eliminate the fundamental component and not affect other harmonic components.Then,the harmonic components of residual current signal were decomposed to a series of frequency bands by wavelet packet to extract the interturn circuit fault features of the induction motor.Finally,the results of simulation and laboratory tests demonstrated the effectiveness of the proposed method.
Enhancement of Non-Air Conducted Speech Based on Wavelet-Packet Adaptive Threshold
Directory of Open Access Journals (Sweden)
Xijing Jing
2013-01-01
Full Text Available This study developed a new kind of speech detecting method by using millimeter wave. Because of the advantage of the millimeter wave, this speech detecting method has great potential application and may provide some exciting possibility for wide applications. However, the MMW conduct speech is in less intelligible and poor audibility since it is corrupted by additive combined noise. This paper, therefore, also developed an algorithm of wavelet packet threshold by using hard threshold and soft threshold for removing noise based on the good capability of wavelet packet for analyzing time-frequency signal. Comparing to traditional speech enhancement algorithm, the results from both simulation and listening evaluation suggest that the proposed algorithm takes on a better performance on noise removing while the distortion of MMW radar speech remains acceptable, the enhanced speech also sounds more pleasant to human listeners, resulting in improved results over classical speech enhancement algorithms.
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
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.
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.
Time-Frequency Distribution of Music based on Sparse Wavelet Packet Representations
DEFF Research Database (Denmark)
Endelt, Line Ørtoft
We introduce a new method for generating time-frequency distributions, which is particularly useful for the analysis of music signals. The method presented here is based on $\\ell1$ sparse representations of music signals in a redundant wavelet packet dictionary. The representations are found usin......, by masking the energy from less structured music instruments. We present four examples for visualizing structured content, including vocal and single instrument....
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...
Seismic Target Classification Using a Wavelet Packet Manifold in Unattended Ground Sensors Systems
Directory of Open Access Journals (Sweden)
Enliang Song
2013-07-01
Full Text Available One of the most challenging problems in target classification is the extraction of a robust feature, which can effectively represent a specific type of targets. The use of seismic signals in unattended ground sensor (UGS systems makes this problem more complicated, because the seismic target signal is non-stationary, geology-dependent and with high-dimensional feature space. This paper proposes a new feature extraction algorithm, called wavelet packet manifold (WPM, by addressing the neighborhood preserving embedding (NPE algorithm of manifold learning on the wavelet packet node energy (WPNE of seismic signals. By combining non-stationary information and low-dimensional manifold information, WPM provides a more robust representation for seismic target classification. By using a K nearest neighbors classifier on the WPM signature, the algorithm of wavelet packet manifold classification (WPMC is proposed. Experimental results show that the proposed WPMC can not only reduce feature dimensionality, but also improve the classification accuracy up to 95.03%. Moreover, compared with state-of-the-art methods, WPMC is more suitable for UGS in terms of recognition ratio and computational complexity.
Institute of Scientific and Technical Information of China (English)
DING YouLiang; LI AiQun; LIU Tao
2008-01-01
The structural damage alarming method based on wavelet packet energy spectrum (WPES) for long-span cable-stayed bridges is presented through combination of ambient vibration test and wavelet packet analysis.The environmental variability in the measured WPES and damage alarming indices ERVD of the Runyang Ca-ble-stayed Bridge are discussed in detail using the wavelet packet analysis of the measured acceleration responses of the bridge under daily environmental condi-tions.The analysis results reveal that the actual environmental conditions includ-ing traffic Ioadings,environmental temperature and typhoon Ioadings have re-markable correlations with the measured WPES.The changes of environmental temperature have a long-term trend influence on the WPES,while the influences of traffic and typhoon Ioadings on the measured WPES of the bridge present instan-taneous changes because of the nonstationary properties of the Ioadings.The analysis results of the measured responses further reveal that the damage alarm-ing indices ERVD can sensitively reflect the influences of environmental tempera-ture and typhoon Ioadings on the dynamic properties of Runyang Cable-stayed Bridge.Therefore,the proposed structural damage alarming indices ERVD under ambient vibrations are suitable for real-time damage alarming for long-span ca-ble-stayed bridges.
Institute of Scientific and Technical Information of China (English)
2008-01-01
The structural damage alarming method based on wavelet packet energy spectrum (WPES) for long-span cable-stayed bridges is presented through combination of ambient vibration test and wavelet packet analysis. The environmental variability in the measured WPES and damage alarming indices ERVD of the Runyang Cable-stayed Bridge are discussed in detail using the wavelet packet analysis of the measured acceleration responses of the bridge under daily environmental conditions. The analysis results reveal that the actual environmental conditions including traffic loadings, environmental temperature and typhoon loadings have remarkable correlations with the measured WPES. The changes of environmental temperature have a long-term trend influence on the WPES, while the influences of traffic and typhoon loadings on the measured WPES of the bridge present instantaneous changes because of the nonstationary properties of the loadings. The analysis results of the measured responses further reveal that the damage alarming indices ERVD can sensitively reflect the influences of environmental temperature and typhoon loadings on the dynamic properties of Runyang Cable-stayed Bridge. Therefore, the proposed structural damage alarming indices ERVD under ambient vibrations are suitable for real-time damage alarming for long-span cable-stayed bridges.
Wavelet Packet Entropy in Speaker-Independent Emotional State Detection from Speech Signal
Directory of Open Access Journals (Sweden)
Mina Kadkhodaei Elyaderani
2015-01-01
Full Text Available In this paper, wavelet packet entropy is proposed for speaker-independent emotion detection from speech. After pre-processing, wavelet packet decomposition using wavelet type db3 at level 4 is calculated and Shannon entropy in its nodes is calculated to be used as feature. In addition, prosodic features such as first four formants, jitter or pitch deviation amplitude, and shimmer or energy variation amplitude besides MFCC features are applied to complete the feature vector. Then, Support Vector Machine (SVM is used to classify the vectors in multi-class (all emotions or two-class (each emotion versus normal state format. 46 different utterances of a single sentence from Berlin Emotional Speech Dataset are selected. These are uttered by 10 speakers in sadness, happiness, fear, boredom, anger, and normal emotional state. Experimental results show that proposed features can improve emotional state detection accuracy in multi-class situation. Furthermore, adding to other features wavelet entropy coefficients increase the accuracy of two-class detection for anger, fear, and happiness.
Characterizations of Orthogonal Vector-valued Multivariate Wavelet Packets%多元向量值正交小波包的刻画
Institute of Scientific and Technical Information of China (English)
华德林; 冯金顺
2008-01-01
In this paper,the notion of orthogonal vector-valued wavelet packets of space L2(Rs,Cn)is introduced.A procedure for constructing the orthogonal vector-valued wavelet packets is presented.Their properties are characterized by virtue of time-frequency analysis method,matrix theory and finite group theory,and three orthogonality formulas are obtained.Finally,new orthonormal bases of space L2(Rs,Cn)are extracted from these wavelet packets.
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.
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.
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.
Wavelet packet-based identification of complex oscillation in biological signals
Institute of Scientific and Technical Information of China (English)
Zhang Shuqing; Sarah K. Spurgeon; Zhang Liguo; Jin Mei; John A. Twiddle; Fernando S. Schlindwein
2008-01-01
Owing to the intrinsic nonlinearities of the system, a contracting mechanism, such as myogenic response,may induce different oscillatory patterns. Many specialists discussed the relations of oscillatory patterns with intrinsic control system or some pathological condition, but there is no single, well-defined criterion to achieve the identifieation of regular, stochastic, and chaotic activities. In this paper, we focus on the Mallat algorithm of wavelet packet and use it in the identification of the regular periodic, stochastic, and chaotic fluctuations. According to the specificfrequency configuration of the chaos activity, we select proper layers of decomposition of wavelet packet and did fine segments to the frequency of signals. The frequency band of energy convergence could be recognized. The signal of periodic, stochastic, and chaotic could be distinguished depending on it. Numerical experiment is given to show its efficiency. Experiments on 12 babies' lung data have been done. This identification by means of wavelet packe tcould support the cardiologist or cerebral specialist to do more observation and deeper analysis to physic signals.
Institute of Scientific and Technical Information of China (English)
DUAN Yali; SU Rongguo; SHI Xiaoyong; WANG Xiulin; ZHU Chenjian; SUN Yan
2013-01-01
An in vivo fluorescence discrimination technique for phytoplankton population was developed by using Wavelet packet transform,cluster analysis and non-negative least squares.The technique was used to analyze water samples from different sea regions.For simulative mixtures,when dominant species account for 60％,70％,80％,90％ at the division level,the correct discrimination ratios (CDRs) are 83.0％,99.1％,99.7％ and 99.9％ with the relative contents of 58.5％,68.4％,77.7％ and 86.3％,respectively; when the algae dominance are 60％,70％,80％,90％,100％ at the genus level,the CDRs are 86.1％,94.9％,95.2％,96.8％ and 96.7％,respectively.For laboratory mixtures,the CDRs are 88.1％ and 78.4％ at the division and genus level,respectively.For field samples,the CDRs were 91.7％ and 80％ at the division and genus level,respectively (mesocosm experiments),and the CDRs were 100％ and 66.7％ at the division and genus level,respectively (Jiaozhou Bay).The fluorometric technique was used to estimate the phytoplankton community composition and relative abundance of different classes for the April 2010 cruise in the Yellow Sea with the results agreeing with those in published papers by other authors.
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.
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.
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.
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.
Two Level DCT and Wavelet Packets Denoising Robust Image Watermarking
Directory of Open Access Journals (Sweden)
N.Koteswara Rao
2014-01-01
Full Text Available In this paper we present a low frequency watermarking scheme on gray level images, which is based on DCT transform and spread spectrum communications technique.The DCT of non overlapping 8x8 blocks of the host image is computed, then using each block DC coefficients we construct a low-resolution approximation image. We apply block based DCT on this approximation image, then a pseudo random noise sequence is added into its high frequencies. For detection, we extract the approximation image from the watermarked image, then the same pseudo random noise sequence is generated, and its correlation is computed with high frequencies of the watermarked approximation image. In our method, higher robustness is obtained because of embedding the watermark in low frequency. In addition, higher imperceptibility is gained by scattering the watermark's bit in different blocks. We evaluated the robustness of the proposed technique against many common attacks such as JPEG compression, additive Gaussian noise and median filter. Compared with related works, our method proved to be highly resistant in cases of compression and additive noise, while preserving high PSNR for the watermarked images.
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.
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.
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)
Application of Wavelet Packet De-noising in Time-Frequency Analysis of the Local Wave Method
Institute of Scientific and Technical Information of China (English)
LI Hong-kun; MA Xiao-jiang; WANG Zhen; ZHU Hong
2003-01-01
The local wave method is a very good time-frequency method for nonstationary vibration signal analysis. But the interfering noise has a big influence on the accuracy of time-frequency analysis. The wavelet packet de-noising method can eliminate the interference of noise and improve the signal-noise-ratio. This paper uses the local wave method to decompose the de-noising signal and perform a time-frequency analysis. We can get better characteristics. Finally, an example of wavelet packet de-noising and a local wave time-frequency spectrum application of diesel engine surface vibration signal is put forward.
Institute of Scientific and Technical Information of China (English)
ZHANG Xiaodong; BI Guangguo
2001-01-01
A wavelet packet function based multiple access (WPMA) system is developed in this paper to maximize capacity and improve receiver performance over frequency selective multipath fading channels. To design an efficient receiver that mitigates residual multiple access interference (MAI) and intersymbol interference, while improving received signal-to-interference and noise ratio (SINR) simultaneously on the uplink, a multichannel decision feedback equalizer (DFE) following a wavelet packet function based RAKE receiver is proposed. Simulation results show that, over GSM TU channels the developed receiver performs quite well if the power of each user is perfectly controlled or the space diversity combining (SDC) technique is applied.
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.
Fault Diagnosis for IC Engines Using Wavelet Packet and Image Processing
Institute of Scientific and Technical Information of China (English)
ZHAO Hong; XIA Yong; LIANG Xiao-guo
2003-01-01
There are few applications of image processing technology for diagnosing and state monitoring for internal combustion (IC) engines, which is discussed in detail in this paper. The time-frequency distribution images of cylinder head vibration signals are obtained by decomposing them with a wavelet packet algorithm. It is the first time that we look at time-frequency distribution images from the point of images. Bused on this, a new method for applying image processing technology for diagnosing and state monitoring for internal combustion engines is presented in this paper. A valve fault diagnosis model is set up by image matching, which is realized on a four-stroke, six-cylinder diesel engine. At the same time, some notes are presented in this paper. It has been proved that it is of no good effect to diagnose with his tograms of time-frequency images generated by cylinder head vibration signals that have been processed with a wavelet packet algorithm. The reason is given in this paper. Comparisons of diagnosing effect are carried out between noise-addedsignals and original signals. It has little effect on diagnosing results after signals have been added with noise. The results show that this method has a clear physical meaning and is of good engineering practicability, feasibility, good precision and high speed.
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
wavelet. The second half of the chapter groups together miscellaneous points about the discrete wavelet transform, including coefficient manipulation for signal denoising and smoothing, a description of Daubechies' wavelets, the properties of translation invariance and biorthogonality, the two-dimensional discrete wavelet transforms and wavelet packets. The fourth chapter is dedicated to wavelet transform methods in the author's own specialty, fluid mechanics. Beginning with a definition of wavelet-based statistical measures for turbulence, the text proceeds to describe wavelet thresholding in the analysis of fluid flows. The remainder of the chapter describes wavelet analysis of engineering flows, in particular jets, wakes, turbulence and coherent structures, and geophysical flows, including atmospheric and oceanic processes. The fifth chapter describes the application of wavelet methods in various branches of engineering, including machining, materials, dynamics and information engineering. Unlike previous chapters, this (and subsequent) chapters are styled more as literature reviews that describe the findings of other authors. The areas addressed in this chapter include: the monitoring of machining processes, the monitoring of rotating machinery, dynamical systems, chaotic systems, non-destructive testing, surface characterization and data compression. The sixth chapter continues in this vein with the attention now turned to wavelets in the analysis of medical signals. Most of the chapter is devoted to the analysis of one-dimensional signals (electrocardiogram, neural waveforms, acoustic signals etc.), although there is a small section on the analysis of two-dimensional medical images. The seventh and final chapter of the book focuses on the application of wavelets in three seemingly unrelated application areas: fractals, finance and geophysics. The treatment on wavelet methods in fractals focuses on stochastic fractals with a short section on multifractals
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
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.
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/.
[The comparison of the extraction of beta wave from EEG between FFT and wavelet transform].
Wang, Haowen; Qian, Zhiyu; Li, Hongjing; Chen, Chunxiao; Ding, Shangwen
2013-08-01
In order to choose a fast and efficient real-time method in beta wave information extraction, we compared the result and the efficiency of the information separation of both fast Fourier transform (FFT) and wavelet transform of EEG beta band in the present paper. Our work provides the basis for the EEG data come from the real-time health assessment of 3DTV. We took the EEGs of 5 healthy volunteers before, after and during the process of watching 3DTV and meanwhile recorded the results. The trends of the relative energy and the time cost of two methods were compared by using both the FFT and wavelet packet transform (WPT) which was to extract the feature of EEG beta wave. It demonstrated that (1) Results of the two methods were consistent in the trends of watching 3DTV; (2) Results of the differences in two methods were consistent before and after watching 3DTV; (3) FFT took less time than the wavelet transform in the same case. It is concluded that the results of both FFT and Wavelet transform are consistent in feature extraction of EEG, and a fast method to work with the large quantities of EEG data obtained in the experiments can be offered in the future.
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
Reusability of Patterns Using Discrete Wavelet Transformation in Watermarking
Directory of Open Access Journals (Sweden)
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.
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.
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.
Directory of Open Access Journals (Sweden)
Huan Zhao
2011-06-01
Full Text Available According to the distribution characteristic of noise and clean speech signal in the frequency domain, a new speech enhancement method based on teager energy operator (TEO and perceptual wavelet packet decomposition (PWPD is proposed. Firstly, a modified Mask construction method is made to protect the acoustic cues at the low frequencies. Then a level-dependent parameter is introduced to further adjust the thresholds in light of the noise distribution feature. At last the sub-bands which have very little influence are set directly 0 to improve the signal-to-noise ratio (SNR and reduce the computation load. Simulation results show that, under different kinds of noise environments, this new method not only enhances the signal-to-noise ratio (SNR and perceptual evaluation of speech quality (PESQ, but also reduces the computation load, which is very advantageous for real-time realizing.
Diagnosis of Gearbox Typical Fault in Rolling Mills Based on the Wavelet Packets Technology
Institute of Scientific and Technical Information of China (English)
CUI Lingli; GAO Lixin; ZHANG Jianyu; DING Fang
2006-01-01
The early impulse fault diagnosis of the gearbox in rolling mills is often difficult and labour intensive because the gearbox of that high speed machine is multi-shafting transmission system, in which many gearsets and rolling bears work together at the same time and there are much complex frequency structure and various disturb. A new time-frequency method based on the wavelet packets technique was developed and used to extract the impact feature from signals collected from faulty data of one rolling mills gearbox. The method improves the signal to noise ration so that results obtained using this method represents features with fine resolution in both low-frequency and the high frequency bands. The results of analysis indicate the validity and the practicability of the method proposed here.
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...
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.
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
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.
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.
DENOISING AND HARMONIC DETECTION USING NONORTHOGONAL WAVELET PACKETS IN INDUSTRIAL APPLICATIONS
Institute of Scientific and Technical Information of China (English)
P. MERCORELLI
2007-01-01
New industrial applications call for new methods and new ideas in signal analysis. Wavelet packets are new tools in industrial applications and they have just recently appeared in projects and patents. In training neural networks, for the sake of dimensionality and of ratio of time, compact information is needed. This paper deals with simultaneous noise suppression and signal compression of quasi-harmonic signals. A quasi-harmonic signal is a signal with one dominant harmonic and some more sub harmonics in superposition. Such signals often occur in rail vehicle systems, in vhich noisy signals are present. Typically, they are signals which come from rail overhead power lines and are generated by intermodulation phenomena and radio interferences. An important task is to monitor and recognize them. This paper proposes an algorithm to differentiate discrete signals from their noisy observations using a library of nonorthonormal bases. The algorithm combines the shrinkagetechnique and techniques in regression analysis using Shannon Entropy function and Cross Entropy function to select the best discernable bases. Cosine and sine wavelet bases in wavelet packets are used.The algorithm is totally general and can be used in many industrial applications. The effectiveness of the proposed method consists of using as few as possible samples of the measured signal and in the meantime highlighting the difference between the noise and the desired signal. The problem is a difficult one, but well posed. In fact, compression reduces the level of the measured noise and undesired signals but introduces the well known compression noise. The goal is to extract a coherent signal from the measured signal which will be "well represented" by suitable waveforms and a noisy signal or incoherent signal which cannot be "compressed well" by the waveforms. Recursive residual iterations with cosine and sine bases allow the extraction of elements of the required signal and the noise. The algorithm
A Secret Image Sharing Method Using Integer Wavelet Transform
Directory of Open Access Journals (Sweden)
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.
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.
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.
Applications of wavelet packet theory on cab FSK signals%小波包方法在车载FSK信号中的应用
Institute of Scientific and Technical Information of China (English)
孙艳朋; 贾利民; 范明
2001-01-01
FSK信号作为保障铁路安全运行的主要信号制式，在国内铁路上现在有两种，是法国引进的UT信号和国内自主开发的YP信号。小波变换是继傅里叶变换之后的重大突破，而小波包则是小波变换的进一步发展，克服了小波变换的一些不足。本文首先研究了车载FSK信号的特征，再利用小波包对车载FSK信号进行滤波处理。文中，给出了如何确定给定频率的信号在小波包分解树各个分解层中对应节点的算法，在滤波处理过程中，为了处理带内的噪声，也给出了采用阈值的方法来减少带内白噪声，阈值的选取充分应用到FSK信号的小波包分解的特点。最后，我们给出了计算机产生的仿真FSK信号和现场采集的FSK信号的两种仿真，仿真结果表明，根据车载FSK信号的特性，小波包方法是处理车载FSK信号的有效方法。%As the key signal system guaranteeing the safety for the railway, there are two types of FSK system used now by China railway: UT signal imported from France and the homemade YP signal. Wavelet transform is a big breakthrough after Fourier transforms, and the wavelet packet theory is the further development for wavelet transform, for it overcomes some shortcomings of wavelet transform. In this article, we study first the main characters of cab FSK signal, then the wavelet packets method is applied to the FSK signal filtering. We give an algorithm that determines the corresponding decomposition node for a signal with a pre-specified frequency in the decomposition tree. In order to reduce the in-band white noise in the denoising process, we give an algorithm based on threshold technology, and we also give a method to calculate the threshold that takes full advantage of the character of the wavelet packet decomposition of the FSK signal. In the last part of the article,a simulations on both computer simulation data and field data are given, and the simulation
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.
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.
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.
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.
Combining Wavelet Transform and Hidden Markov Models for ECG Segmentation
Directory of Open Access Journals (Sweden)
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.
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.
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.
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.
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.
Van Dijck, Gert; Van Hulle, Marc M.
2011-01-01
The damage caused by corrosion in chemical process installations can lead to unexpected plant shutdowns and the leakage of potentially toxic chemicals into the environment. When subjected to corrosion, structural changes in the material occur, leading to energy releases as acoustic waves. This acoustic activity can in turn be used for corrosion monitoring, and even for predicting the type of corrosion. Here we apply wavelet packet decomposition to extract features from acoustic emission signals. We then use the extracted wavelet packet coefficients for distinguishing between the most important types of corrosion processes in the chemical process industry: uniform corrosion, pitting and stress corrosion cracking. The local discriminant basis selection algorithm can be considered as a standard for the selection of the most discriminative wavelet coefficients. However, it does not take the statistical dependencies between wavelet coefficients into account. We show that, when these dependencies are ignored, a lower accuracy is obtained in predicting the corrosion type. We compare several mutual information filters to take these dependencies into account in order to arrive at a more accurate prediction. PMID:22163921
Institute of Scientific and Technical Information of China (English)
DENG Ke; ZHANG Lu; LUO Mao-Kang
2011-01-01
@@ Aiming at the shortage of conventional threshold function in wavelet noise reduction of chaotic signals, we propose a wavelet-packet noise reduction method of chaotic signals based on a new higher order threshold function.The method retains the useful high-frequency information, and the threshold function is continuous and derivable, therefore it is more consistent with the characteristics of the continuous signal.Contrast simulation experiment shows that the effect of noise reduction and the precision of noise reduction of chaotic signals both are improved.%Aiming at the shortage of conventional threshold function in wavelet noise reduction of chaotic signals, we propose a wavelet-packet noise reduction method of chaotic signals based on a new higher order threshold function. The method retains the useful high-frequency information, and the threshold function is continuous and derivable,therefore it is more consistent with the characteristics of the continuous signal. Contrast simulation experiment shows that the effect of noise reduction and the precision of noise reduction of chaotic signals both are improved.
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.
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
The frequency domain division theory of dyadic wavelet decomposition and wavelet packet decomposition (WPD) with orthogonal wavelet base frame are presented. The WPD coefficients of signals are treated as the outputs of equivalent bandwidth filters with different center frequency. The corresponding WPD entropy values of coefficients increase sharply when the discrete spectrum interferences (DSIs), frequency spectrum of which is centered at several frequency points existing in some frequency region. Based on WPD, an entropy threshold method (ETM) is put forward, in which entropy is used to determine whether partial discharge (PD) signals are interfered by DSIs. Simulation and real data processing demonstrate that ETM works with good efficiency, without pre-knowing DSI information. ETM extracts the phase of PD pulses accurately and can calibrate the quantity of single type discharge.
使用复小波包的MIMO-OFDM无线系统%Complex wavelet packet based MIMO-OFDM wireless system
Institute of Scientific and Technical Information of China (English)
肖征荣; 余智; 赵绍刚; 吴伟陵
2004-01-01
为了在频率选择性信道中提供高速数据业务,提出了一种新的多入多出-正交频分复用系统MIMO-OFDM(Multi-Input Multi-Output-Orthogonal Frequency Division Multiplexing).该系统使用复小波包变换CWPT(Complex Wavelet Packet Transform)来实现OFDM,而不是使用传统的快速傅立叶变换FFT(Fast Fourier Transform).由于复小波包函数具有很好的特性,通过对有2个用户的MIMO-OFDM系统进行仿真的结果表明,基于CWPT的MIMO-OFDM系统性能要比使用传统的FFT的MIMO-OFDM 系统好,但是复杂度略高.
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...
小波包变换在风电场谐波分析中的应用%Application of Wavelet Packet in Harmonic Analysis for Wind Power Plants
Institute of Scientific and Technical Information of China (English)
解胜民; 杨秀媛
2013-01-01
含有变频器的风力发电机组在并网发电时会给电力系统注入时变谐波.快速傅里叶变换(FFT)是目前谐波分析的主要方法,但是它不适合处理非平稳时变信号.提出利用小波包变换(WPT)的方法对电流信号进行分析.基于Daubechies小波,采用适当的采集频率和小波包分解树,使谐波频率落在小波包频带并利用其小波包系数重构出各次谐波.可以实现信号频带的均匀划分,能够更好地提取信号的时频特性,还具有分辨非平稳时变谐波的能力.仿真结果显示小波包变换的谐波分析能力更好,能根据要求分离任意次谐波.%The wind turbine containing the inverter under grid connected mode will inject time-varying harmonic current into the power system.The fast Fourier transform (FFT) is currently the main method for the electrical harmonic analysis while it is not suitable for analyzing time-varying signals.A novel method for analyzing the current signal based on the wavelet packet transform is proposed.Based on the db wavelet,this method makes use of appropriate sampling frequency and the tree of the wavelet packet decomposition.The harmonic frequency tested will locate in the frequency band and the harmonic is reconstructed by using the wavelet packet coefficient.Using wavelet packet transform,the frequency band of signal can be uniformly divided and the signal features in time domain and frequency domain are extracted better.WPT also has the ability to distinguish non-stationary time-varying harmonic possesses for harmonic analysis.The result of the simulation shows that the wavelet packet transform is more effective in the analysis of the harmonic.WPT can even extract any times of harmonics.
Application and improvement of wavelet packet de-noising in satellite transponder
Institute of Scientific and Technical Information of China (English)
Yannian Lou; Chaojie Zhang; Xiaojun Jin; Zhonghe Jin
2015-01-01
The satel ite transponder is a widely used module in satel ite missions, and the most concerned issue is to reduce the noise of the transferred signal. Otherwise, the telemetry signal wil be pol uted by the noise contained in the transferred signal, and the additional power wil be consumed. Therefore, a method based on wavelet packet de-noising (WPD) is introduced. Compared with other techniques, there are two features making WPD more suit-able to be applied to satel ite transponders: one is the capability to deal with time-varying signals without any priori information of the input signals; the other is the capability to reduce the noise in band, even if the noise overlaps with signals in the frequency domain, which provides a great de-noising performance especial y for wideband signals. Besides, an oscil ation detector and an av-eraging filter are added to decrease the partial oscil ation caused by the thresholding process of WPD. Simulation results show that the proposed algorithm can reduce more noises and make less distortions of the signals than other techniques. In addition, up to 12 dB additional power consumption can be reduced at –10 dB signal-to-noise ratio (SNR).
Application of the Wavelet Packet Method in Discrimination Between Nuclear Explosion and Earthquake
Institute of Scientific and Technical Information of China (English)
Yang Xuanhui; Shen Ping; Liu Xiqiang; Zheng Zhizhen
2004-01-01
Although the CTBT (Comprehensive Nuclear Test-Ban Treaty) was passed in 1996, it is still necessary to develop new and highly efficient methods (Wu Zhongliang, Chen Yuntai, et al.,1993; Xu Shaoxie, et al. 1994; Richard L. Garwin, 1994) to monitor possible events. Many discrimination criteria (Xu Shaoxie, et al., 1994; Institute of Geophysics, Chinese Academy of Sciences, 1976; Richard L. Garwin, 1994) have been put forward since the 1950s. The results show that each of the existing criteria has its own limitation, but the seismological method is an important and efficient method in the discrimination between nuclear explosion and earthquake. Especially in recent years, because of the little and little equivalent as well as the increasing hiding steps used in the test, a number of more efficient seismological methods have been worked out. In this paper, a new discrimination method, the Wavelet Packet Component Ratio (WPCR) method, is put forward. This method makes full use of the difference in variation with time between the spectra of nuclear explosions and earthquakes. Its discrimination efficiency is rather high.
Ebrahimi, Farideh; Mikaeili, Mohammad; Estrada, Edson; Nazeran, Homer
2008-01-01
Currently in the world there is an alarming number of people who suffer from sleep disorders. A number of biomedical signals, such as EEG, EMG, ECG and EOG are used in sleep labs among others for diagnosis and treatment of sleep related disorders. The usual method for sleep stage classification is visual inspection by a sleep specialist. This is a very time consuming and laborious exercise. Automatic sleep stage classification can facilitate this process. The definition of sleep stages and the sleep literature show that EEG signals are similar in Stage 1 of non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep. Therefore, in this work an attempt was made to classify four sleep stages consisting of Awake, Stage 1 + REM, Stage 2 and Slow Wave Stage based on the EEG signal alone. Wavelet packet coefficients and artificial neural networks were deployed for this purpose. Seven all night recordings from Physionet database were used in the study. The results demonstrated that these four sleep stages could be automatically discriminated from each other with a specificity of 94.4 +/- 4.5%, a of sensitivity 84.2+3.9% and an accuracy of 93.0 +/- 4.0%.
Study of wavelet packet energy entropy for emotion classification in speech and glottal signals
He, Ling; Lech, Margaret; Zhang, Jing; Ren, Xiaomei; Deng, Lihua
2013-07-01
The automatic speech emotion recognition has important applications in human-machine communication. Majority of current research in this area is focused on finding optimal feature parameters. In recent studies, several glottal features were examined as potential cues for emotion differentiation. In this study, a new type of feature parameter is proposed, which calculates energy entropy on values within selected Wavelet Packet frequency bands. The modeling and classification tasks are conducted using the classical GMM algorithm. The experiments use two data sets: the Speech Under Simulated Emotion (SUSE) data set annotated with three different emotions (angry, neutral and soft) and Berlin Emotional Speech (BES) database annotated with seven different emotions (angry, bored, disgust, fear, happy, sad and neutral). The average classification accuracy achieved for the SUSE data (74%-76%) is significantly higher than the accuracy achieved for the BES data (51%-54%). In both cases, the accuracy was significantly higher than the respective random guessing levels (33% for SUSE and 14.3% for BES).
Institute of Scientific and Technical Information of China (English)
DING YouLiang; LI AiQun; SUN Jun; DENG Yang
2009-01-01
In order to establish an environmental-condition-normalized structural damage alarming method, the seasonal correlation analysis of wavelet packet energy spectrum (WPES) and temperature of Runyang Suspension Bridge is performed by means of the 236-day health monitoring data. The analysis results reveal that the measured WPES has remarkable seasonal correlation with the environmental tempera-ture. The seasonal change of environmental temperature accounts for the variation of the damage alarming parameter Ip of the dominant frequency bands with an averaged variance of 200%. The statis-tical modeling technique using a 6th-order polynomial is adopted to formulate the correlation between the WPES and temperature, on the basis of which the abnormal changes of measured damage alarming parameter Ip are detected using the mean value control chart. It is found that the proposed method can effectively eliminate temperature complications from the time series of WPES and exhibit good capa-bility for detecting the damage-induced 10% variances of the damage alarming parameter Ip. And the proposed WPES-based method is superior the modal frequency and hence is more suitable for online real-time damage alarming for long-span bridges.
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
In order to establish an environmental-condition-normalized structural damage alarming method,the seasonal correlation analysis of wavelet packet energy spectrum(WPES)and temperature of Runyang Suspension Bridge is performed by means of the 236-day health monitoring data.The analysis results reveal that the measured WPES has remarkable seasonal correlation with the environmental tempera-ture.The seasonal change of environmental temperature accounts for the variation of the damage alarming parameter Ip of the dominant frequency bands with an averaged variance of 200%.The statis-tical modeling technique using a 6th-order polynomial is adopted to formulate the correlation between the WPES and temperature,on the basis of which the abnormal changes of measured damage alarming parameter Ip are detected using the mean value control chart.It is found that the proposed method can effectively eliminate temperature complications from the time series of WPES and exhibit good capa-bility for detecting the damage-induced 10% variances of the damage alarming parameter Ip.And the proposed WPES-based method is superior the modal frequency and hence is more suitable for online real-time damage alarming for long-span bridges.
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.
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.
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
Ng, J.; Kingsbury, N. G.
2004-02-01
wavelet. The second half of the chapter groups together miscellaneous points about the discrete wavelet transform, including coefficient manipulation for signal denoising and smoothing, a description of Daubechies’ wavelets, the properties of translation invariance and biorthogonality, the two-dimensional discrete wavelet transforms and wavelet packets. The fourth chapter is dedicated to wavelet transform methods in the author’s own specialty, fluid mechanics. Beginning with a definition of wavelet-based statistical measures for turbulence, the text proceeds to describe wavelet thresholding in the analysis of fluid flows. The remainder of the chapter describes wavelet analysis of engineering flows, in particular jets, wakes, turbulence and coherent structures, and geophysical flows, including atmospheric and oceanic processes. The fifth chapter describes the application of wavelet methods in various branches of engineering, including machining, materials, dynamics and information engineering. Unlike previous chapters, this (and subsequent) chapters are styled more as literature reviews that describe the findings of other authors. The areas addressed in this chapter include: the monitoring of machining processes, the monitoring of rotating machinery, dynamical systems, chaotic systems, non-destructive testing, surface characterization and data compression. The sixth chapter continues in this vein with the attention now turned to wavelets in the analysis of medical signals. Most of the chapter is devoted to the analysis of one-dimensional signals (electrocardiogram, neural waveforms, acoustic signals etc.), although there is a small section on the analysis of two-dimensional medical images. The seventh and final chapter of the book focuses on the application of wavelets in three seemingly unrelated application areas: fractals, finance and geophysics. The treatment on wavelet methods in fractals focuses on stochastic fractals with a short section on multifractals. The
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.
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.
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.
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.
Characterization of EEG Signals Using Wavelet Packet and Fuzzy Entropy in Motor Imagination Tasks
Directory of Open Access Journals (Sweden)
Boris Alexander Medina
2017-05-01
Full Text Available Context: Clinical rhythm analysis on advanced signal processing methods is very important in medical areas such as brain disorder diagnostic, epilepsy, sleep analysis, anesthesia analysis, and more recently in brain-computer interfaces (BCI. Method: Wavelet transform package is used on this work to extract brain rhythms of electroencephalographic signals (EEG related to motor imagination tasks. We used the Competition BCI 2008 database for this characterization. Using statistical functions we obtained features that characterizes brain rhythms, which are discriminated using different classifiers; they were evaluated using a 10-fold cross validation criteria. Results: The classification accuracy achieved 81.11% on average, with a degree of agreement of 61%, indicating a "suitable" concordance, as it has been reported in the literature. An analysis of relevance showed the concentration of characteristics provided in the nodes as a result of Wavelet decomposition, as well as the characteristics that more information content contribute to improve the separability decision region for the classification task. Conclusions: The proposed method can be used as a reference to support future studies focusing on characterizing EEG signals oriented to the imagination of left and right hand movement, considering that our results proved to compared favourably to those reported in the literature. Language: Spanish.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
Institute of Scientific and Technical Information of China (English)
陈清江; 刘洪运
2008-01-01
The notion of vector-valued multiresolution analysis is introduced and the concept of orthogonal vector-valued wavelets with 3-scale is proposed.A necessary and sufficient condition on the existence of orthogonal vector-valued wavelets is given by means of paraunitary vector filter bank theory.An algorithm for constructing a class of compactly supported orthogonal vector-valued wavelets is presented.Their characteristics is discussed by virtue of operator theory,time-frequency method.Moreover,it is shown how to design various orthonormal bases of space L2(R,Cn) from these wavelet packets.
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
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.
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.
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.
Automatic Target Detection Using Wavelet Transform
Directory of Open Access Journals (Sweden)
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.
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.
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.
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.
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...
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.
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.
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
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.
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.
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...
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.
Directory of Open Access Journals (Sweden)
Dongqing Wang
2016-11-01
Full Text Available This study presented wavelet packet feature assessment of neural control information in paretic upper-limb muscles of stroke survivors for myoelectric pattern recognition, taking advantage of high-resolution time-frequency representations of surface electromyographic (EMG signals. On this basis, a novel channel selection method was developed by combining the Fisher's class separability index (FCSI and the sequential feedforward selection (SFS analyses, in order to determine a small number of appropriate EMG channels from original high-density EMG electrode array. The advantages of the wavelet packet features and the channel selection analyses were further illustrated by comparing with previous conventional approaches, in terms of classification performance when identifying 20 functional arm/hand movements implemented by 12 stroke survivors. This study offers a practical approach including paretic EMG feature extraction and channel selection that enables active myoelectric control of multiple degrees of freedom with paretic muscles. All these efforts will facilitate upper-limb dexterity restoration and improved stroke rehabilitation.
Directory of Open Access Journals (Sweden)
Maurizio Murroni
2008-01-01
Full Text Available Multiple transmission of heterogeneous services is a central aspect of broadcasting technology. Often, in this framework, the design of efficient communication systems is complicated by stringent bandwidth constraint. In wavelet packet division multiplexing (WPDM, the message signals are waveform coded onto wavelet packet basis functions. The overlapping nature of such waveforms in both time and frequency allows improving the performance over the commonly used FDM and TDM schemes, while their orthogonality properties permit to extract the message signals by a simple correlator receiver. Furthermore, the scalable structure of WPDM makes it suitable for broadcasting heterogeneous services. This work investigates unequal error protection (UEP of data which exhibit different sensitivities to channel errors to improve the performance of WPDM for transmission over band-limited channels. To cope with bandwidth constraint, an appropriate distribution of power among waveforms is proposed which is driven by the channel error sensitivities of the carried message signals in case of Gaussian noise. We address this problem by means of the genetic algorithms (GAs, which allow flexible suboptimal solution with reduced complexity. The mean square error (MSE between the original and the decoded message, which has a strong correlation with subjective perception, is used as an optimization criterion.
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.
Wavelet Transform and Neural Networks in Fault Diagnosis of a Motor Rotor
Institute of Scientific and Technical Information of China (English)
RONG Ming-xing
2012-01-01
In the motor fault diagnosis technique, vibration and stator current frequency components of detection are two main means. This article will discuss the signal detection method based on vibration fault. Because the motor vibration signal is a non-stationary random signal, fault signals often contain a lot of time-varying, burst proper- ties of ingredients. The traditional Fourier signal analysis can not effectively extract the motor fault characteristics, but are also likely to be rich in failure information but a weak signal as noise. Therefore, we introduce wavelet packet transforms to extract the fault characteristics of the signal information. Obtained was the result as the neural network input signal, using the L-M neural network optimization method for training, and then used the BP net- work for fault recognition. This paper uses Matlab software to simulate and confirmed the method of motor fault di- agnosis validity and accuracy
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...
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
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.
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.
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.
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.
Institute of Scientific and Technical Information of China (English)
陈伟根; 谢波; 龙震泽; 崔鲁; 李永森; 周渠; 陈曦
2016-01-01
Air-gap discharge is the main type of partial discharge (PD) within power transformer. It is of great significance to study the discharge development stage for the monitoring and diagnosis of transformer potential faults. This paper build an air-gap discharge model in simulative transformer tank, collecting PD signals based on constant voltage method, utilizing wavelet packet decomposition method to partition the PD signal bands obtaining signal energy distribution in each frequency band as well as total signal energy tendency along with PD development process. The new PD parameter describing the development process, wavelet packet energy entropy, was proposed based on the signal energy variation in each frequency band. Due to the cyclic change of wavelet packet energy entropy, the step points of wavelet packet entropy are taken as the way to effectively divide the PD development stage. According to the thresholds of wavelet packet energy entropy in different stages, the PD development stages were identified.%能量分布以及局放发展过程信号总能量发展情况,基于不同频带下信号能量变化特征提出以小波包能量熵作为局部放电发展特性的新特征量,通过小波包能量熵在整个过程中的循环变化特征规律,提出以小波包能量熵"阶跃"断层点为支点的局部放电阶段有效划分方式,并根据小波包能量熵在不同阶段的阈值特点,建立通过阈值判定来识别局部放电发展阶段的模型.
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.
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.
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.
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.
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.
Image Compression using Haar and Modified Haar Wavelet Transform
Directory of Open Access Journals (Sweden)
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.
Rossant, Florence; Mikovicova, Beata; Adam, Mathieu; Trocan, Maria
2010-12-01
This paper presents a complete iris identification system including three main stages: iris segmentation, signature extraction, and signature comparison. An accurate and robust pupil and iris segmentation process, taking into account eyelid occlusions, is first detailed and evaluated. Then, an original wavelet-packet-based signature extraction method and a novel identification approach, based on the fusion of local distance measures, are proposed. Performance measurements validating the proposed iris signature and demonstrating the benefit of our local-based signature comparison are provided. Moreover, an exhaustive evaluation of robustness, with regards to the acquisition conditions, attests the high performances and the reliability of our system. Tests have been conducted on two different databases, the well-known CASIA database (V3) and our ISEP database. Finally, a comparison of the performances of our system with the published ones is given and discussed.
Directory of Open Access Journals (Sweden)
Rossant Florence
2010-01-01
Full Text Available Abstract This paper presents a complete iris identification system including three main stages: iris segmentation, signature extraction, and signature comparison. An accurate and robust pupil and iris segmentation process, taking into account eyelid occlusions, is first detailed and evaluated. Then, an original wavelet-packet-based signature extraction method and a novel identification approach, based on the fusion of local distance measures, are proposed. Performance measurements validating the proposed iris signature and demonstrating the benefit of our local-based signature comparison are provided. Moreover, an exhaustive evaluation of robustness, with regards to the acquisition conditions, attests the high performances and the reliability of our system. Tests have been conducted on two different databases, the well-known CASIA database (V3 and our ISEP database. Finally, a comparison of the performances of our system with the published ones is given and discussed.
Directory of Open Access Journals (Sweden)
Maria Trocan
2010-01-01
Full Text Available This paper presents a complete iris identification system including three main stages: iris segmentation, signature extraction, and signature comparison. An accurate and robust pupil and iris segmentation process, taking into account eyelid occlusions, is first detailed and evaluated. Then, an original wavelet-packet-based signature extraction method and a novel identification approach, based on the fusion of local distance measures, are proposed. Performance measurements validating the proposed iris signature and demonstrating the benefit of our local-based signature comparison are provided. Moreover, an exhaustive evaluation of robustness, with regards to the acquisition conditions, attests the high performances and the reliability of our system. Tests have been conducted on two different databases, the well-known CASIA database (V3 and our ISEP database. Finally, a comparison of the performances of our system with the published ones is given and discussed.
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.
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.
Xu, Bin; Zhang, Ting; Song, Gangbing; Gu, Haichang
2013-03-01
Concrete-Filled Steel Tube (CFST) has been widely adopted in high-rise buildings and bridges as a typical structural member carrying vertical loads in recent years. The debonding between the steel tube and the concrete can dramatically reduce the confinement effect of steel tube on the concrete and decrease the load-carrying capacity and the ductility of the CFST. It is still challenging to develop reliable debonding monitoring and detection techniques for CFST because of the inaccessibility of the interface. In this study, an active interface condition monitoring approach for CFST by the use of lead zirconate titanate (PZT) piezoceramics based functional smart aggregates (SAs) embedded in concrete as actuator and PZT patches bonded on the surface of the steel tube as sensors is proposed and verified experimentally. Laboratory tests are performed on the CFST column, in which the deboning is mimicked by setting four thin styrofoam plates with different sizes on different locations of the four internal surfaces of the steel tube, respectively, before casting the concrete. The responses of the PZT sensors are measured when each SA is excited with sweep sinusoidal signals. According to the Fourier spectra and two evaluation indices based on the wavelet packet analysis on the PZT sensors measurements, the artificially mimicked debonding areas are detected successfully. Analysis on the sensitivity of the two evaluation indices shows that the indices based on wavelet packet analysis are more sensitive to the debonding defect. The proposed PZT based active debonding monitoring method provides an innovative approach to detect the debonding damage of CFST columns.
Xu, Bin; Chen, Hongbing; Xia, Song
2017-03-01
In recent years, Piezoelectric Lead Zirconate Titanate (PZT) based active interfacial debonding defect detection approach for concrete-filled steel tubular (CFST) columns has been proposed and validated experimentally. In order to investigate the mechanism of the PZT based interfacial debonding detection approach, a multi-physics coupling finite element model (FEM) composed of surface-mounted PZT actuator, embedded PZT sensor and a rectangular CFST column is constructed to numerically simulate the stress wave propagation induced by the surface-mounted PZT actuator under different excitation signals with different frequency and amplitude. The measurements of the embedded PZT sensor in concrete core of the CFST columns with different interfacial debonding defect lengths and depths are determined numerically with transient dynamic analysis. The linearity between the PZT response and the input amplitude, the effect of different frequency and measurement distance are discussed and the stress wave fields of CFST members without and with interface debonding defects are compared. Then, the response of the embedded PZT in concrete core is analyzed with wavelet packet analysis. The root mean square deviation (RMSD) of wavelet packet energy spectrum of the PZT measurement is employed as an evaluation index for the interfacial debonding detection. The results showed that the defined index under continuous sinusoidal and sweep frequency signals changes with the interfacial defects length and depth and is capable of effectively identifying the interfacial debonding defect between the concrete core and the steel tubular. Moreover, the index under sweep frequency signal is more sensitive to the interfacial debonding. The simulation results indicate that the interfacial debonding defect leads to the changes in the propagation path, travel time and the magnitude of stress waves. The simulation results meet the findings from the previous experimental study by the authors and help
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.
基于谐波小波包理论的轴承故障诊断%Fault diagnosis of rolling bearings based on harmonic wavelet packet theory
Institute of Scientific and Technical Information of China (English)
吴逍; 纪国宜
2011-01-01
The application of practical wavelet analysis in fault diagnosis is growing rapidly. There are many different wavelets to use but no accepted procedure for choosing among them,the results of them have great difference. The investigation of harmonic wavelet and harmonic wavelet packet analysis revealed good characteristics in vibration signal analysis on partial frequency domain. A simulating example and several experimental examples illustrate how the harmonic wavelet packets method is applied to fault diagnosis of rolling bearings. The favorable results are obtained through the analysis of those signals on a test rig. It is shown that harmonic wavelet packet has many advantages over other wavelets and has the broad application prospect in the domain of fault diagnosis.%小波分析在故障诊断中得到较广泛的应用,但采用不同的小波,分析结果往往会有很大差异.通过对谐波小波和谐波小波包的分析研究,指出了谐波小波包对振动信号局部频段分析的优良特性.结合仿真信号与故障实验进行分析,提出将谐波小波包方法用于诊断轴承故障.实验验证取得了满意结果,表明谐波小波包方法是一种有效的故障诊断工具.
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.
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
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 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.
Harris, Arief R; Schwerdtfeger, Karsten; Strauss, Daniel J
2008-01-01
Local discriminant bases (LDB) have a major disadvantage in their representation which is sensitive to signal translations. The discriminant features will be not consistent when the same but shifted signal is applied. Thus, to overcome this problem, an approximate shift-invariant features extraction based on local discriminant bases is introduced. This technique is based on approximate shift-invariant wavelet packed decomposition which integrate a cost function for decimation decision in each sub-band expansion. This technique gives a consistent best tree selection both in top-down and bottom-up search method. It also provides a consistent wavelet shape in a shape-adapted wavelet method to determine the best wavelet library for a particular signal. This method has an advantage especially in electroencephalographic (EEG) measurement in which there is an inter-individual shift in time for the signals. An application of this method is provided by the discrimination between signals with transcranial magnetic stimulation (TMS) and acoustic-somatosensory stimulation (ASS).
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.
Multiple descriptions based wavelet image coding
Institute of Scientific and Technical Information of China (English)
陈海林; 杨宇航
2004-01-01
We present a simple and efficient scheme that combines multiple descriptions coding with wavelet transform under JPEG2000 image coding architecture. To reduce packet losses, controlled amounts of redundancy are added to the wavelet transform coefficients to produce multiple descriptions of wavelet coefficients during the compression process to produce multiple descriptions bit-stream of a compressed image. Even if areceiver gets only parts of descriptions (other descriptions being lost), it can still reconstruct image with acceptable quality. Specifically, the scheme uses not only high-performance wavelet transform to improve compression efficiency, but also multiple descriptions technique to enhance the robustness of the compressed image that is transmitted through unreliable network channels.
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.
Facial Expression Recognition Using Stationary Wavelet Transform Features
Directory of Open Access Journals (Sweden)
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
Wavelet transform based ECG signal filtering implemented on FPGA
Directory of Open Access Journals (Sweden)
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.
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
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.
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).
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.
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 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.
Optical Wavelet Signals Processing and Multiplexing
Cincotti, Gabriella; Moreolo, Michela Svaluto; Neri, Alessandro
2005-12-01
We present compact integrable architectures to perform the discrete wavelet transform (DWT) and the wavelet packet (WP) decomposition of an optical digital signal, and we show that the combined use of planar lightwave circuits (PLC) technology and multiresolution analysis (MRA) can add flexibility to current multiple access optical networks. We furnish the design guidelines to synthesize wavelet filters as two-port lattice-form planar devices, and we give some examples of optical signal denoising and compression/decompression techniques in the wavelet domain. Finally, we present a fully optical wavelet packet division multiplexing (WPDM) scheme where data signals are waveform-coded onto wavelet atom functions for transmission, and numerically evaluate its performances.
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.
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.
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.
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.
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.
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.
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.
Directory of Open Access Journals (Sweden)
Wei Li
2013-01-01
Full Text Available Belt conveyors are the equipment widely used in coal mines and other manufacturing factories, whose main components are a number of idlers. The faults of belt conveyors can directly influence the daily production. In this paper, a fault diagnosis method combining wavelet packet decomposition (WPD and support vector machine (SVM is proposed for monitoring belt conveyors with the focus on the detection of idler faults. Since the number of the idlers could be large, one acceleration sensor is applied to gather the vibration signals of several idlers in order to reduce the number of sensors. The vibration signals are decomposed with WPD, and the energy of each frequency band is extracted as the feature. Then, the features are employed to train an SVM to realize the detection of idler faults. The proposed fault diagnosis method is firstly tested on a testbed, and then an online monitoring and fault diagnosis system is designed for belt conveyors. An experiment is also carried out on a belt conveyor in service, and it is verified that the proposed system can locate the position of the faulty idlers with a limited number of sensors, which is important for operating belt conveyors in practices.
Directory of Open Access Journals (Sweden)
Shuihua Wang
2015-09-01
Full Text Available To develop an automatic tea-category identification system with a high recall rate, we proposed a computer-vision and machine-learning based system, which did not require expensive signal acquiring devices and time-consuming procedures. We captured 300 tea images using a 3-CCD digital camera, and then extracted 64 color histogram features and 16 wavelet packet entropy (WPE features to obtain color information and texture information, respectively. Principal component analysis was used to reduce features, which were fed into a fuzzy support vector machine (FSVM. Winner-take-all (WTA was introduced to help the classifier deal with this 3-class problem. The 10 × 10-fold stratified cross-validation results show that the proposed FSVM + WTA method yields an overall recall rate of 97.77%, higher than 5 existing methods. In addition, the number of reduced features is only five, less than or equal to existing methods. The proposed method is effective for tea identification.
Wei, Jiahong; Liu, Chong; Ren, Tongqun; Liu, Haixia; Zhou, Wenjing
2017-02-08
The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in railway maintenance. However, the vision-based method cannot identify the severity of rail fastener looseness. In this paper, the condition of rail fastening system is monitored based on an automatic and remote-sensing measurement system. Meanwhile, wavelet packet analysis is used to analyze the acceleration signals, based on which two damage indices are developed to locate the damage position and evaluate the severity of rail fasteners looseness, respectively. To verify the effectiveness of the proposed method, an experiment is performed on a high-speed railway experimental platform. The experimental results show that the proposed method is effective to assess the condition of the rail fastening system. The monitoring system significantly reduces the inspection time and increases the efficiency of maintenance management.
Directory of Open Access Journals (Sweden)
Jiahong Wei
2017-02-01
Full Text Available The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in railway maintenance. However, the vision-based method cannot identify the severity of rail fastener looseness. In this paper, the condition of rail fastening system is monitored based on an automatic and remote-sensing measurement system. Meanwhile, wavelet packet analysis is used to analyze the acceleration signals, based on which two damage indices are developed to locate the damage position and evaluate the severity of rail fasteners looseness, respectively. To verify the effectiveness of the proposed method, an experiment is performed on a high-speed railway experimental platform. The experimental results show that the proposed method is effective to assess the condition of the rail fastening system. The monitoring system significantly reduces the inspection time and increases the efficiency of maintenance management.
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.
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.
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.
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
Directory of Open Access Journals (Sweden)
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)
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.
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.
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).``
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)
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.
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.
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.
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.
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)
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.
Adapted wavelet analysis from theory to software
Wickerhauser, Mladen Victor
1994-01-01
This detail-oriented text is intended for engineers and applied mathematicians who must write computer programs to perform wavelet and related analysis on real data. It contains an overview of mathematical prerequisites and proceeds to describe hands-on programming techniques to implement special programs for signal analysis and other applications. From the table of contents: - Mathematical Preliminaries - Programming Techniques - The Discrete Fourier Transform - Local Trigonometric Transforms - Quadrature Filters - The Discrete Wavelet Transform - Wavelet Packets - The Best Basis Algorithm - Multidimensional Library Trees - Time-Frequency Analysis - Some Applications - Solutions to Some of the Exercises - List of Symbols - Quadrature Filter Coefficients
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.
[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.
Reversible Integer Wavelet Transform for the Joint of Image Encryption and Watermarking
Directory of Open Access Journals (Sweden)
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.
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.
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.
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
WAVELET TRANSFORM ANALYSIS OF ELECTROMYOGRAPHY KUNG FU STRIKES DATA
Directory of Open Access Journals (Sweden)
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 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
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.
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.
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.
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.
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.
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.
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.
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
Directory of Open Access Journals (Sweden)
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.
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.
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.
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.
基于小波包分析的齿轮箱故障诊断研究%Gearbox Fault Diagnosis Based on Wavelet Packet Analysis
Institute of Scientific and Technical Information of China (English)
蒋宇; 曹磊
2012-01-01
通过对齿轮箱正常和故障运行状态的振动信号进行分析，利用小波包理论将3种工况振动信号进行分解。根据不同频带内能量分布的不同以及能量比值指标，有效地进行了3种工况的识别与分类，结果表明。利用小波包分解是齿轮箱故障的一种有效的诊断方法。%Vibration signals of the normal and abnormal running state of the gearbox are analyzed, and the three working vibration signals are decomposed by using Wavelet Packet Theory. According to different energy distribution and energy ratio index of different frequency bands, the three working modes of gearbox are identified and classified effectively. The results indicate that the wavelet packet decomposition is an effective method for gearbox fault diagnosis.
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.
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%.
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.
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.
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.
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...
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...
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...
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.
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.
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)
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
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.
Guesmi, Latifa; Hraghi, Abir; Menif, Mourad
2015-09-01
There is a need, for high speed optical communication networks, in the monitoring process, to determine the modulation format type of a received signal. In this paper, we present a new achievement of modulation format recognition technique, where we proposed the use of wavelet transform of the detected signal in conjunction with the artificial neural network (ANN) algorithm. Besides, wavelet transform is one of the most popular candidates of the time-frequency transformations, where the wavelets are generated from a basic wavelet function by dilations and translations. We proved that this technique is capable of recognizing the multi-carriers modulation scheme with high accuracy under different transmission impairments such as chromatic dispersion (CD), differential group delay (DGD) and accumulated amplified spontaneous emission (ASE) noise with different ranges. Both the theoretical analysis and the simulation results showed that the wavelet transform not only can be used for modulation identification of optical communication signals, but also has a better classification accuracies under appropriate OSNR (optical signal-to-noise ratio) values.
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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.
EEG Signal Denoising and Feature Extraction Using Wavelet Transform in Brain Computer Interface
Institute of Scientific and Technical Information of China (English)
WU Ting; YAN Guo-zheng; YANG Bang-hua; SUN Hong
2007-01-01
Electroencephalogram (EEG) signal preprocessing is one of the most important techniques in brain computer interface (BCI). The target is to increase signal-to-noise ratio and make it more favorable for feature extraction and pattern recognition. Wavelet transform is a method of multi-resolution time-frequency analysis, it can decompose the mixed signals which consist of different frequencies into different frequency band. EEG signal is analyzed and denoised using wavelet transform. Moreover, wavelet transform can be used for EEG feature extraction. The energies of specific sub-bands and corresponding decomposition coefficients which have maximal separability according to the Fisher distance criterion are selected as features. The eigenvector for classification is obtained by combining the effective features from different channels. The performance is evaluated by separability and pattern recognition accuracy using the data set of BCI 2003 Competition, the final classification results have proved the effectiveness of this technology for EEG denoising and feature extraction.
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.
Ţălu, Ştefan; StȨpień, Krzysztof; Caglayan, Mustafa Oguzhan
2015-11-01
This paper analyses the three-dimensional (3-D) surface morphology of optic surface of unworn contact lenses (CLs) using atomic force microscopy (AFM) and wavelet transform. Refractive powers of all lens samples were 2.50 diopters. Topographic images were acquired in contact mode in air-conditioned medium (35% RH, 23°C). Topographic measurements were taken over a 5 µm × 5 µm area with 512 pixel resolution. Resonance frequency of the tip was 65 kHz. The 3-D surface morphology of CL unworn samples revealed (3-D) micro-textured surfaces that can be analyzed using (AFM) and wavelet transform. AFM and wavelet transform are accurate and sensitive tools that may assist CL manufacturers in developing CLs with optimal surface characteristics.
Identification of turbulence structures above a forest canopy using a wavelet transform
Turner, B. J.; Leclerc, M. Y.; Gauthier, M.; Moore, K. E.; Fitzjarrald, D. R.
1994-01-01
The wavelet transform is used to identify scales of large coherent structures present in atmospheric turbulence above the subarctic forest at Schefferville. Individual coherent structures contributing to much of the exchange between the forest and the atmosphere are depicted in terms of both scale and location using contour diagrams of wavelet transform coefficients. Three typical case studies of turbulence and flux observations were selected to examine the physical characteristics of these flux-filled events and their evolution with distance away from the forest canopy. A wavelet transform spectral technique is applied to vertical velocity, temperature, and turbulent heat flux data observed over the sparse coniferous forest to extract the relative importance of each scale present in those data series. The scale of turbulence structures in relation with their characteristic spacing is discussed.
Analysis of corrosion behavior of LY12 in sodium chloride solution with wavelet transform technique
Institute of Scientific and Technical Information of China (English)
张昭; 曹发和; 程英亮; 张鉴清; 王建明; 曹楚南
2002-01-01
Wavelet transforms(WT) are proposed as an alternative tool to overcome the limitations of fast Fourier transforms(FFT) in the analysis of electrochemical noise(EN) data. The most relevant feature of this method of analysis is its capability of decomposing electrochemical noise records into different sets of wavelet coefficients(distinct type of events), which contains information about the time scale characteristic of the associated corrosion event. In this context, the potential noise fluctuations during the free corrosion of commercial aluminum alloy LY12 in sodium chloride solution was recorded and analyzed with wavelet transform technique. The typical results show that the EN signal is composed of distinct type of events, which can be classified according to their scales, i.e. their time constants. Meanwhile, the energy distribution plot(EDP) can be used as "fingerprints" of EN signals and can be very useful for analyzing EN data in the future.
Design and Implementation of Fast- Lifting Based Wavelet Transform for Image Compression
Directory of Open Access Journals (Sweden)
Lokesh B.S
2014-06-01
Full Text Available The digital data can be compressed and retrieved using Discrete Wavelet Transform (DWT and Inverse Discrete wavelet Transform (IDWT. The medical images need to be compressed and retrieved without loosing of information. The Discrete Wavelet Transform (DWT is based on time-scale representation which provides efficient multi-resolution. This paper mainly describes the lifting based scheme gives lossless mode of information. The lifting based DWT and IDWT are having lower computational complexity and reduced memory requirement. Conventional convolution based DWT and IDWT are area and power hungry. These drawbacks can be overcome by using the lifting based scheme. This system adopts lifting based scheme DWT and IDWT which gives the lossless information of the data, reduces the complexity and optimized in area and power. In this research the DWT and IDWT are simulated and the design of hardware model is carried out using RTL level coding.
Model Based Ceramic tile inspection using Discrete Wavelet Transform and Euclidean Distance
Elmougy, Samir; El-Azab, Ahmed
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 defects which known as reference image, and the image to be inspected which known as test image. The second phase is used to decide whether the tested image is defected or not using the Euclidean distance similarity measure. The experimentation results of the proposed algorithm give 97% for correct detection of ceramic defects.
Directory of Open Access Journals (Sweden)
Min Wang
2015-01-01
Full Text Available This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD, with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts, with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with image rotations and the enhancement of the directional features: to filter the diagonal part, one needs first to rotate it 45 degrees and rotate it back after filtering. Finally, reconstruct the image from the low-frequency part and the filtered high-frequency parts by the inverse wavelet transform to get the final denoising image. Experiments show the effectiveness of this method, compared with relevant methods.
Wavelet transform for real-time detection of action potentials in neural signals.
Quotb, Adam; Bornat, Yannick; Renaud, Sylvie
2011-01-01
We present a study on wavelet detection methods of neuronal action potentials (APs). Our final goal is to implement the selected algorithms on custom integrated electronics for on-line processing of neural signals; therefore we take real-time computing as a hard specification and silicon area as a price to pay. Using simulated neural signals including APs, we characterize an efficient wavelet method for AP extraction by evaluating its detection rate and its implementation cost. We compare software implementation for three methods: adaptive threshold, discrete wavelet transform (DWT), and stationary wavelet transform (SWT). We evaluate detection rate and implementation cost for detection functions dynamically comparing a signal with an adaptive threshold proportional to its SD, where the signal is the raw neural signal, respectively: (i) non-processed; (ii) processed by a DWT; (iii) processed by a SWT. We also use different mother wavelets and test different data formats to set an optimal compromise between accuracy and silicon cost. Detection accuracy is evaluated together with false negative and false positive detections. Simulation results show that for on-line AP detection implemented on a configurable digital integrated circuit, APs underneath the noise level can be detected using SWT with a well-selected mother wavelet, combined to an adaptive threshold.
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Huaqing Wang
2012-03-01
Full Text Available A least square method based on data fitting is proposed to construct a new lifting wavelet, together with the nonlinear idea and redundant algorithm, the adaptive redundant lifting transform based on fitting is firstly stated in this paper. By variable combination selections of basis function, sample number and dimension of basis function, a total of nine wavelets with different characteristics are constructed, which are respectively adopted to perform redundant lifting wavelet transforms on low-frequency approximate signals at each layer. Then the normalized lP norms of the new node-signal obtained through decomposition are calculated to adaptively determine the optimal wavelet for the decomposed approximate signal. Next, the original signal is taken for subsection power spectrum analysis to choose the node-signal for single branch reconstruction and demodulation. Experiment signals and engineering signals are respectively used to verify the above method and the results show that bearing faults can be diagnosed more effectively by the method presented here than by both spectrum analysis and demodulation analysis. Meanwhile, compared with the symmetrical wavelets constructed with Lagrange interpolation algorithm, the asymmetrical wavelets constructed based on data fitting are more suitable in feature extraction of fault signal of roller bearings.
Impedance cardiography signal denoising using discrete wavelet transform.
Chabchoub, Souhir; Mansouri, Sofienne; Salah, Ridha Ben
2016-09-01
Impedance cardiography (ICG) is a non-invasive technique for diagnosing cardiovascular diseases. In the acquisition procedure, the ICG signal is often affected by several kinds of noise which distort the determination of the hemodynamic parameters. Therefore, doctors cannot recognize ICG waveform correctly and the diagnosis of cardiovascular diseases became inaccurate. The aim of this work is to choose the most suitable method for denoising the ICG signal. Indeed, different wavelet families are used to denoise the ICG signal. The Haar, Daubechies (db2, db4, db6, and db8), Symlet (sym2, sym4, sym6, sym8) and Coiflet (coif2, coif3, coif4, coif5) wavelet families are tested and evaluated in order to select the most suitable denoising method. The wavelet family with best performance is compared with two denoising methods: one based on Savitzky-Golay filtering and the other based on median filtering. Each method is evaluated by means of the signal to noise ratio (SNR), the root mean square error (RMSE) and the percent difference root mean square (PRD). The results show that the Daubechies wavelet family (db8) has superior performance on noise reduction in comparison to other methods.
Institute of Scientific and Technical Information of China (English)
李杰; 刘希强; 李红; 毛玉华; 郑树田
2005-01-01
Wavelet transform method is applied to measure time-frequency distribution characteristics of digital deformation data and noise. Based on the characteristics of primary modulus and stochastic white noise discrimination factor of wavelet decomposition, we analyze the variation rule of normal background and noise data from Shandong digital deformation observation data. The research results indicate that: a) 1/4 daily wave, semi-diurnal tide wave, daily wave and half lunar wave and so on quasi-periodic signal exist in the detail decomposing signal of wavelet when scale are equal to 2, 3 and 4; b) The amplitude of detail decomposing signal is the biggest when scale is equal to 3; c) The detail decomposing signal contains mainly noise corresponding to scale 1 and 5, respectively; d) We may trace the abnormal precursory which is related to earthquake by analyzing non-earthquake wavelet decomposing signal whose scale is specified from digital deformation observation data.
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.
Institute of Scientific and Technical Information of China (English)
CEN Wei; YANG ShiFeng; XUE Rong; XU RiWei; YU DingSheng
2007-01-01
Surface morphologies of supported polyethylene (PE) catalysts are investigated by an approach combining fractal with wavelet. The multiscale edge (detail) pictures of catalyst surface are extracted by wavelet transform modulus maxima (WTMM) method. And, the distribution of edge points on the edge image at every scale is studied with fractal and multifractal method. Furthermore, the singularity intensity distribution of edge points in the PE catalyst is analyzed by multifractal spectrum based on WTMM. The results reveal that the fractal dimension values and multifractal spectrums of edge images at small scales have a good relation with the activity and surface morphology of PE catalyst. Meanwhile the catalyst exhibiting the higher activity shows the wider singular strength span of multifractal spectrum based on WTMM, as well as the more edge points with the higher singular intensity. The research on catalyst surface morphology with hybrid fractal and wavelet method exerts the superiorities of wavelet and fractal theories and offers a thought for studying solid surfaces morphologies.
Directory of Open Access Journals (Sweden)
Sarunya Kanjanawattana
2017-07-01
Full Text Available Image classification plays a vital role in many areas of study, such as data mining and image processing; however, serious problems collectively referred to as the course of dimensionality have been encountered in previous studies as factors that reduce system performance. Furthermore, we also confront the problem of different graph characteristics even if graphs belong to same types. In this study, we propose a novel method of graph-type classification. Using our approach, we open up a new solution of high-dimensional images and address problems of different characteristics by converting graph images to one dimension with a discrete Fourier transformation and creating numeric datasets using wavelet and Hough transformations. Moreover, we introduce a new classifier, which is a combination between artificial neuron networks (ANNs and support vector machines (SVMs, which we call ANNSVM, to enhance accuracy. The objectives of our study are to propose an effective graph-type classification method that includes finding a new data representative used for classification instead of two-dimensional images and to investigate what features make our data separable. To evaluate the method of our study, we conducted five experiments with different methods and datasets. The input dataset we focused on was a numeric dataset containing wavelet coefficients and outputs of a Hough transformation. From our experimental results, we observed that the highest accuracy was provided using our method with Coiflet 1, which achieved a 0.91 accuracy.
[Detection of R-wave in Fetal EGG Based on Wavelet Transform and Matched Filtering].
Yan, Wenhong; Jiang, Ning
2015-09-01
By analyzing the characteristics of maternal abdominal ECG (Electrocardiogram), a method based on wavelet transform and matched filtering is proposed to detect the R-wave in fetal EGG (FECG). In this method, the high-frequency coefficients are calculated by using wavelet transform. First, the maternal QRS template is obtained by using the arithmetic mean scheme. Finally, the R-wave of FECG is detected based on matched filtering. The experimental results show that this method can effectively eliminate the noises, such as the maternal ECG signal and baseline drift, enhancing the accuracy of the detection of fetal ECG.
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.
Classification of melanoma using wavelet-transform-based optimal feature set
Walvick, Ronn P.; Patel, Ketan; Patwardhan, Sachin V.; Dhawan, Atam P.
2004-05-01
The features used in the ABCD rule for characterization of skin lesions suggest that the spatial and frequency information in the nevi changes at various stages of melanoma development. To analyze these changes wavelet transform based features have been reported. The classification of melanoma using these features has produced varying results. In this work, all the reported wavelet transform based features are combined to form a single feature set. This feature set is then optimized by removing redundancies using principal component analysis. A feed forward neural network trained with the back propagation algorithm is then used in the classification process to obtain better classification results.
An Improved Singularity Computing Algorithm Based on Wavelet Transform Modulus Maxima Method
Institute of Scientific and Technical Information of China (English)
ZHAO Jian; XIE Duan; FAN Xun-li
2006-01-01
In order to reduce the hidden danger of noise which can be charactered by singularity spectrum, a new algorithm based on wavelet transform modulus maxima method was proposed. Singularity analysis is one of the most promising new approaches for extracting noise hidden information from noisy time series . Because of singularity strength is hard to calculate accurately, a wavelet transform modulus maxima method was used to get singularity spectrum. The singularity spectrum of white noise and aluminium interconnection electromigration noise was calculated and analyzed. The experimental results show that the new algorithm is more accurate than tradition estimating algorithm. The proposed method is feasible and efficient.
Min Wang; Zhen Li; Xiangjun Duan; Wei Li
2015-01-01
This paper proposes an image denoising method, using the wavelet transform and the singular value decomposition (SVD), with the enhancement of the directional features. First, use the single-level discrete 2D wavelet transform to decompose the noised image into the low-frequency image part and the high-frequency parts (the horizontal, vertical, and diagonal parts), with the edge extracted and retained to avoid edge loss. Then, use the SVD to filter the noise of the high-frequency parts with i...
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.