Search results for: lifting wavelet.
362 Multi-Focus Image Fusion Using SFM and Wavelet Packet
Authors: Somkait Udomhunsakul
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In this paper, a multi-focus image fusion method using Spatial Frequency Measurements (SFM) and Wavelet Packet was proposed. The proposed fusion approach, firstly, the two fused images were transformed and decomposed into sixteen subbands using Wavelet packet. Next, each subband was partitioned into sub-blocks and each block was identified the clearer regions by using the Spatial Frequency Measurement (SFM). Finally, the recovered fused image was reconstructed by performing the Inverse Wavelet Transform. From the experimental results, it was found that the proposed method outperformed the traditional SFM based methods in terms of objective and subjective assessments.
Keywords: Multi-focus image fusion, Wavelet Packet, Spatial Frequency Measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1602361 Defect Detection of Tiles Using 2D-Wavelet Transform and Statistical Features
Authors: M.Ghazvini, S. A. Monadjemi, N. Movahhedinia, K. Jamshidi
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In this article, a method has been offered to classify normal and defective tiles using wavelet transform and artificial neural networks. The proposed algorithm calculates max and min medians as well as the standard deviation and average of detail images obtained from wavelet filters, then comes by feature vectors and attempts to classify the given tile using a Perceptron neural network with a single hidden layer. In this study along with the proposal of using median of optimum points as the basic feature and its comparison with the rest of the statistical features in the wavelet field, the relational advantages of Haar wavelet is investigated. This method has been experimented on a number of various tile designs and in average, it has been valid for over 90% of the cases. Amongst the other advantages, high speed and low calculating load are prominent.Keywords: Defect detection, tile and ceramic quality inspection, wavelet transform, classification, neural networks, statistical features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2363360 Enhance Performance of Secure Image Using Wavelet Compression
Authors: Goh Han Keat, Azman Samsudin Zurinahni Zainol
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The increase popularity of multimedia application especially in image processing places a great demand on efficient data storage and transmission techniques. Network communication such as wireless network can easily be intercepted and cause of confidential information leaked. Unfortunately, conventional compression and encryption methods are too slow; it is impossible to carry out real time secure image processing. In this research, Embedded Zerotree Wavelet (EZW) encoder which specially designs for wavelet compression is examined. With this algorithm, three methods are proposed to reduce the processing time, space and security protection that will be secured enough to protect the data.
Keywords: Embedded Zerotree Wavelet (EZW), Imagecompression, Wavelet encoder, Entropy encoder, Encryption.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1662359 Design and Development of Automatic Leveling and Equalizing Hoist Device for Spacecraft
Authors: Fu Hao, Sun Gang, Tang Laiying, Cui Junfeng
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To solve the quick and accurate level-adjusting problem in the process of spacecraft precise mating, automatic leveling and equalizing hoist device for spacecraft is developed. Based on lifting point adjustment by utilizing XY-workbench, the leveling and equalizing controller by a self-adaptive control algorithm is proposed. By simulation analysis and lifting test using engineering prototype, validity and reliability of the hoist device is verified, which can meet the precision mating requirements of practical applications for spacecraft.Keywords: automatic leveling and equalizing, hoist device, lifting point adjustment, self-adaptive control
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2005358 Comparison between Haar and Daubechies Wavelet Transformations on FPGA Technology
Authors: Fatma H. Elfouly, Mohamed I. Mahmoud, Moawad I. M. Dessouky, Salah Deyab
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Recently, the Field Programmable Gate Array (FPGA) technology offers the potential of designing high performance systems at low cost. The discrete wavelet transform has gained the reputation of being a very effective signal analysis tool for many practical applications. However, due to its computation-intensive nature, current implementation of the transform falls short of meeting real-time processing requirements of most application. The objectives of this paper are implement the Haar and Daubechies wavelets using FPGA technology. In addition, the Bit Error Rate (BER) between the input audio signal and the reconstructed output signal for each wavelet is calculated. From the BER, it is seen that the implementations execute the operation of the wavelet transform correctly and satisfying the perfect reconstruction conditions. The design procedure has been explained and designed using the stat-ofart Electronic Design Automation (EDA) tools for system design on FPGA. Simulation, synthesis and implementation on the FPGA target technology has been carried out.
Keywords: Daubechies wavelet, discrete wavelet transform, Haar wavelet, Xilinx FPGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7219357 Microarrays Denoising via Smoothing of Coefficients in Wavelet Domain
Authors: Mario Mastriani, Alberto E. Giraldez
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We describe a novel method for removing noise (in wavelet domain) of unknown variance from microarrays. The method is based on a smoothing of the coefficients of the highest subbands. Specifically, we decompose the noisy microarray into wavelet subbands, apply smoothing within each highest subband, and reconstruct a microarray from the modified wavelet coefficients. This process is applied a single time, and exclusively to the first level of decomposition, i.e., in most of the cases, it is not necessary a multirresoltuion analysis. Denoising results compare favorably to the most of methods in use at the moment.
Keywords: Directional smoothing, denoising, edge preservation, microarrays, thresholding, wavelets
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1495356 Lagrange and Multilevel Wavelet-Galerkin with Polynomial Time Basis for Heat Equation
Authors: Watcharakorn Thongchuay, Puntip Toghaw, Montri Maleewong
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The Wavelet-Galerkin finite element method for solving the one-dimensional heat equation is presented in this work. Two types of basis functions which are the Lagrange and multi-level wavelet bases are employed to derive the full form of matrix system. We consider both linear and quadratic bases in the Galerkin method. Time derivative is approximated by polynomial time basis that provides easily extend the order of approximation in time space. Our numerical results show that the rate of convergences for the linear Lagrange and the linear wavelet bases are the same and in order 2 while the rate of convergences for the quadratic Lagrange and the quadratic wavelet bases are approximately in order 4. It also reveals that the wavelet basis provides an easy treatment to improve numerical resolutions that can be done by increasing just its desired levels in the multilevel construction process.Keywords: Galerkin finite element method, Heat equation , Lagrange basis function, Wavelet basis function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1721355 Journals Subheadlines Text Extraction Using Wavelet Thresholding and New Projection Profile
Authors: Davod Zaravi, Habib Rostami, Alireza Malahzaheh, S. S. Mortazavi
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In this paper a new robust and efficient algorithm to automatic text extraction from colored book and journal cover sheets is proposed. First, we perform wavelet transform. Next for edge detecting from detail wavelet coefficient, we use dynamic threshold. By blurring approximate coefficients with alternative heuristic thresholding, achieve effective edge,. Afterward, with ROI technique get binary image. Finally text boxes would be extracted with new projection profile.
Keywords: Text extraction, colored cover sheet, wavelet threshold, region of interest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1637354 Improvements in Edge Detection Based on Mathematical Morphology and Wavelet Transform using Fuzzy Rules
Authors: Masrour Dowlatabadi, Jalil Shirazi
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In this paper, an improved edge detection algorithm based on fuzzy combination of mathematical morphology and wavelet transform is proposed. The combined method is proposed to overcome the limitation of wavelet based edge detection and mathematical morphology based edge detection in noisy images. Experimental results show superiority of the proposed method, as compared to the traditional Prewitt, wavelet based and morphology based edge detection methods. The proposed method is an effective edge detection method for noisy image and keeps clear and continuous edges.Keywords: Edge detection, Wavelet transform, Mathematical morphology, Fuzzy logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2394353 Performance Analysis of Wavelet Based Multiuser MIMO OFDM
Authors: Md. Mahmudul Hasan
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Wavelet analysis has some strong advantages over Fourier analysis, as it allows a time-frequency domain analysis, allowing optimal resolution and flexibility. As a result, they have been satisfactorily applied in almost all the fields of communication systems including OFDM which is a strong candidate for next generation of wireless technology. In this paper, the performances of wavelet based Multiuser Multiple Input and Multiple Output Orthogonal Frequency Division Multiplexing (MU-MIMO OFDM) systems are analyzed in terms of BER. It has been shown that the wavelet based systems outperform the classical FFT based systems. This analysis also unfolds an interesting result, where wavelet based OFDM system will have a constant error performance using Regularized Channel Inversion (RCI) beamforming for any number of users, and outperforms in all possible scenario in a multiuser environment. An extensive computer simulations show that a PAPR reduction of up to 6.8dB can be obtained with M=64.
Keywords: Wavelet Based OFDM, Optimal Beam-forming, Multiuser MIMO OFDM, Signal to Leakage Ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2609352 Despeckling of Synthetic Aperture Radar Images Using Inner Product Spaces in Undecimated Wavelet Domain
Authors: Syed Musharaf Ali, Muhammad Younus Javed, Naveed Sarfraz Khattak, Athar Mohsin, UmarFarooq
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This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely directional smoothing filter which is an additional step. Proposed method does not need any noise estimation and thresholding technique. More over proposed method gives good results on both single polarimetric and fully polarimetric SAR images.Keywords: Directional Smoothing, Inner product, Length ofvector, Undecimated wavelet transformation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1595351 Multi-algorithmic Iris Authentication System
Authors: Hunny Mehrotra, Banshidhar Majhi, Phalguni Gupta
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The paper proposes a novel technique for iris recognition using texture and phase features. Texture features are extracted on the normalized iris strip using Haar Wavelet while phase features are obtained using LOG Gabor Wavelet. The matching scores generated from individual modules are combined using sum of score technique. The system is tested on database obtained from Bath University and Indian Institute of Technology Kanpur and is giving an accuracy of 95.62% and 97.66% respectively. The FAR and FRR of the combined system is also reduced comparatively.Keywords: Fusion, Haar Wavelet, Iris, LOG Gabor Wavelet, Phase, Texture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1687350 Frequency-Energy Characteristics of Local Earthquakes using Discrete Wavelet Transform(DWT)
Authors: O. H. Colak, T. C. Destici, S. Ozen, H. Arman, O. Cerezci
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The wavelet transform is one of the most important method used in signal processing. In this study, we have introduced frequency-energy characteristics of local earthquakes using discrete wavelet transform. Frequency-energy characteristic was analyzed depend on difference between P and S wave arrival time and noise within records. We have found that local earthquakes have similar characteristics. If frequency-energy characteristics can be found accurately, this gives us a hint to calculate P and S wave arrival time. It can be seen that wavelet transform provides successful approximation for this. In this study, 100 earthquakes with 500 records were analyzed approximately.Keywords: Discrete Wavelet Transform, Frequency-EnergyCharacteristics, P and S waves arrival time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2256349 Application of EEG Wavelet Power to Prediction of Antidepressant Treatment Response
Authors: Dorota Witkowska, Paweł Gosek, Lukasz Swiecicki, Wojciech Jernajczyk, Bruce J. West, Miroslaw Latka
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In clinical practice, the selection of an antidepressant often degrades to lengthy trial-and-error. In this work we employ a normalized wavelet power of alpha waves as a biomarker of antidepressant treatment response. This novel EEG metric takes into account both non-stationarity and intersubject variability of alpha waves. We recorded resting, 19-channel EEG (closed eyes) in 22 inpatients suffering from unipolar (UD, n=10) or bipolar (BD, n=12) depression. The EEG measurement was done at the end of the short washout period which followed previously unsuccessful pharmacotherapy. The normalized alpha wavelet power of 11 responders was markedly different than that of 11 nonresponders at several, mostly temporoparietal sites. Using the prediction of treatment response based on the normalized alpha wavelet power, we achieved 81.8% sensitivity and 81.8% specificity for channel T4.
Keywords: Alpha waves, antidepressant, treatment outcome, wavelet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1960348 High Sensitivity Crack Detection and Locating with Optimized Spatial Wavelet Analysis
Authors: A. Ghanbari Mardasi, N. Wu, C. Wu
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In this study, a spatial wavelet-based crack localization technique for a thick beam is presented. Wavelet scale in spatial wavelet transformation is optimized to enhance crack detection sensitivity. A windowing function is also employed to erase the edge effect of the wavelet transformation, which enables the method to detect and localize cracks near the beam/measurement boundaries. Theoretical model and vibration analysis considering the crack effect are first proposed and performed in MATLAB based on the Timoshenko beam model. Gabor wavelet family is applied to the beam vibration mode shapes derived from the theoretical beam model to magnify the crack effect so as to locate the crack. Relative wavelet coefficient is obtained for sensitivity analysis by comparing the coefficient values at different positions of the beam with the lowest value in the intact area of the beam. Afterward, the optimal wavelet scale corresponding to the highest relative wavelet coefficient at the crack position is obtained for each vibration mode, through numerical simulations. The same procedure is performed for cracks with different sizes and positions in order to find the optimal scale range for the Gabor wavelet family. Finally, Hanning window is applied to different vibration mode shapes in order to overcome the edge effect problem of wavelet transformation and its effect on the localization of crack close to the measurement boundaries. Comparison of the wavelet coefficients distribution of windowed and initial mode shapes demonstrates that window function eases the identification of the cracks close to the boundaries.
Keywords: Edge effect, scale optimization, small crack locating, spatial wavelet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 944347 Hidden State Probabilistic Modeling for Complex Wavelet Based Image Registration
Authors: F. C. Calnegru
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This article presents a computationally tractable probabilistic model for the relation between the complex wavelet coefficients of two images of the same scene. The two images are acquisitioned at distinct moments of times, or from distinct viewpoints, or by distinct sensors. By means of the introduced probabilistic model, we argue that the similarity between the two images is controlled not by the values of the wavelet coefficients, which can be altered by many factors, but by the nature of the wavelet coefficients, that we model with the help of hidden state variables. We integrate this probabilistic framework in the construction of a new image registration algorithm. This algorithm has sub-pixel accuracy and is robust to noise and to other variations like local illumination changes. We present the performance of our algorithm on various image types.
Keywords: Complex wavelet transform, image registration, modeling using hidden state variables, probabilistic similaritymeasure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1368346 Envelope-Wavelet Packet Transform for Machine Condition Monitoring
Authors: M. F. Yaqub, I. Gondal, J. Kamruzzaman
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Wavelet transform has been extensively used in machine fault diagnosis and prognosis owing to its strength to deal with non-stationary signals. The existing Wavelet transform based schemes for fault diagnosis employ wavelet decomposition of the entire vibration frequency which not only involve huge computational overhead in extracting the features but also increases the dimensionality of the feature vector. This increase in the dimensionality has the tendency to 'over-fit' the training data and could mislead the fault diagnostic model. In this paper a novel technique, envelope wavelet packet transform (EWPT) is proposed in which features are extracted based on wavelet packet transform of the filtered envelope signal rather than the overall vibration signal. It not only reduces the computational overhead in terms of reduced number of wavelet decomposition levels and features but also improves the fault detection accuracy. Analytical expressions are provided for the optimal frequency resolution and decomposition level selection in EWPT. Experimental results with both actual and simulated machine fault data demonstrate significant gain in fault detection ability by EWPT at reduced complexity compared to existing techniques.Keywords: Envelope Detection, Wavelet Transform, Bearing Faults, Machine Health Monitoring.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1949345 Wavelet-Based ECG Signal Analysis and Classification
Authors: Madina Hamiane, May Hashim Ali
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This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further de-noising through wavelet transform and metrics such as signal-to noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the de-noising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm. The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.
Keywords: ECG Signal, QRS detection, thresholding, wavelet decomposition, feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1253344 Applying Wavelet Transform to Ferroresonance Detection and Protection
Authors: Chun-Wei Huang, Jyh-Cherng Gu, Ming-Ta Yang
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Non-synchronous breakage or line failure in power systems with light or no loads can lead to core saturation in transformers or potential transformers. This can cause component and capacitance matching resulting in the formation of resonant circuits, which trigger ferroresonance. This study employed a wavelet transform for the detection of ferroresonance. Simulation results demonstrate the efficacy of the proposed method.
Keywords: Ferroresonance, Wavelet Transform, Intelligent Electronic Device, Transformer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1647343 Parallel Image Compression and Analysis with Wavelets
Authors: M. Kutila, J. Viitanen
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This paper presents image compression with wavelet based method. The wavelet transformation divides image to low- and high pass filtered parts. The traditional JPEG compression technique requires lower computation power with feasible losses, when only compression is needed. However, there is obvious need for wavelet based methods in certain circumstances. The methods are intended to the applications in which the image analyzing is done parallel with compression. Furthermore, high frequency bands can be used to detect changes or edges. Wavelets enable hierarchical analysis for low pass filtered sub-images. The first analysis can be done for a small image, and only if any interesting is found, the whole image is processed or reconstructed.
Keywords: image compression, jpeg, wavelet, vlc
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1769342 Design of Orientation-Free Handler and Fuzzy Controller for Wire-Driven Heavy Object Lifting System
Authors: Bo-Wei Song, Yun-Jung Lee
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This paper presents an intention interface and controller for a wire-driven heavy object lifting system that assists the operator with moving a heavy object. The handler is designed to allow a comfortable working posture for the operator. Plus, as a human assistive system, the operator is involved in the control loop, where a fuzzy control system is used to consider the human control characteristics. The effectiveness and performance of the proposed system are proved by experiments.
Keywords: Fuzzy controller, Handler design, Heavy object lifting system, Human-assistive device, Human-in-the-loop system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1646341 Nonstational Dual Wavelet Frames in Sobolev Spaces
Authors: Yingchun Jiang, Yan Tang
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In view of the good properties of nonstationary wavelet frames and the better flexibility of wavelets in Sobolev spaces, the nonstationary dual wavelet frames in a pair of dual Sobolev spaces are studied in this paper. We mainly give the oblique extension principle and the mixed extension principle for nonstationary dual wavelet frames in a pair of dual Sobolev spaces Hs(Rd) and H-s(Rd).
Keywords: Nonstationary, dual frames, dual Sobolev spaces, extension principle.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1667340 Classification of Non Stationary Signals Using Ben Wavelet and Artificial Neural Networks
Authors: Mohammed Benbrahim, Khalid Benjelloun, Aomar Ibenbrahim, Adil Daoudi
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The automatic classification of non stationary signals is an important practical goal in several domains. An essential classification task is to allocate the incoming signal to a group associated with the kind of physical phenomena producing it. In this paper, we present a modular system composed by three blocs: 1) Representation, 2) Dimensionality reduction and 3) Classification. The originality of our work consists in the use of a new wavelet called "Ben wavelet" in the representation stage. For the dimensionality reduction, we propose a new algorithm based on the random projection and the principal component analysis.
Keywords: Seismic signals, Ben Wavelet, Dimensionality reduction, Artificial neural networks, Classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1437339 Analysis of EEG Signals Using Wavelet Entropy and Approximate Entropy: A Case Study on Depression Patients
Authors: Subha D. Puthankattil, Paul K. Joseph
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Analyzing brain signals of the patients suffering from the state of depression may lead to interesting observations in the signal parameters that is quite different from a normal control. The present study adopts two different methods: Time frequency domain and nonlinear method for the analysis of EEG signals acquired from depression patients and age and sex matched normal controls. The time frequency domain analysis is realized using wavelet entropy and approximate entropy is employed for the nonlinear method of analysis. The ability of the signal processing technique and the nonlinear method in differentiating the physiological aspects of the brain state are revealed using Wavelet entropy and Approximate entropy.
Keywords: EEG, Depression, Wavelet entropy, Approximate entropy, Relative Wavelet energy, Multiresolution decomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3626338 Feature Extraction Technique for Prediction the Antigenic Variants of the Influenza Virus
Authors: Majid Forghani, Michael Khachay
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In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.Keywords: Antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 769337 Effects of Various Wavelet Transforms in Dynamic Analysis of Structures
Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar
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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.
Keywords: Wavelet transform, computational error, computational duration, strong ground motion data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1362336 A Video Watermarking Algorithm Based on Chaotic and Wavelet Neural Network
Authors: Jiadong Liang
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This paper presented a video watermarking algorithm based on wavelet chaotic neural network. First, to enhance binary image’s security, the algorithm encrypted it with double chaotic based on Arnold and Logistic map, Then, the host video was divided into some equal frames and distilled the key frame through chaotic sequence which generated by Logistic. Meanwhile, we distilled the low frequency coefficients of luminance component and self-adaptively embedded the processed image watermark into the low frequency coefficients of the wavelet transformed luminance component with the wavelet neural network. The experimental result suggested that the presented algorithm has better invisibility and robustness against noise, Gaussian filter, rotation, frame loss and other attacks.
Keywords: Video watermark, double chaotic encryption, wavelet neural network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1046335 Denoising and Compression in Wavelet Domainvia Projection on to Approximation Coefficients
Authors: Mario Mastriani
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We describe a new filtering approach in the wavelet domain for image denoising and compression, based on the projections of details subbands coefficients (resultants of the splitting procedure, typical in wavelet domain) onto the approximation subband coefficients (much less noisy). The new algorithm is called Projection Onto Approximation Coefficients (POAC). As a result of this approach, only the approximation subband coefficients and three scalars are stored and/or transmitted to the channel. Besides, with the elimination of the details subbands coefficients, we obtain a bigger compression rate. Experimental results demonstrate that our approach compares favorably to more typical methods of denoising and compression in wavelet domain.
Keywords: Compression, denoising, projections, wavelets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1606334 Comparison of S-transform and Wavelet Transform in Power Quality Analysis
Authors: Mohammad Javad Dehghani
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In the power quality analysis non-stationary nature of voltage distortions require some precise and powerful analytical techniques. The time-frequency representation (TFR) provides a powerful method for identification of the non-stationary of the signals. This paper investigates a comparative study on two techniques for analysis and visualization of voltage distortions with time-varying amplitudes. The techniques include the Discrete Wavelet Transform (DWT), and the S-Transform. Several power quality problems are analyzed using both the discrete wavelet transform and S–transform, showing clearly the advantage of the S– transform in detecting, localizing, and classifying the power quality problems.Keywords: Power quality, S-Transform, Short Time FourierTransform , Wavelet Transform, instantaneous sag, swell.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2801333 Optimal and Generalized Multiple Descriptions Image Coding Transform in the Wavelet Domain
Authors: Bahi brahim, El hassane Ibn Elhaj, Driss Aboutajdine
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In this paper we propose a Multiple Description Image Coding(MDIC) scheme to generate two compressed and balanced rates descriptions in the wavelet domain (Daubechies biorthogonal (9, 7) wavelet) using pairwise correlating transform optimal and application method for Generalized Multiple Description Coding (GMDC) to image coding in the wavelet domain. The GMDC produces statistically correlated streams such that lost streams can be estimated from the received data. Our performance test shown that the proposed method gives more improvement and good quality of the reconstructed image when the wavelet coefficients are normalized by Gaussian Scale Mixture (GSM) model then the Gaussian one ,.
Keywords: Multiple description coding (MDC), gaussian scale mixture (GSM) model, joint source-channel coding, pairwise correlating transform, GMDCT.
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