Search results for "Wavelet"

showing 10 items of 329 documents

Subsignal-based denoising from piecewise linear or constant signal

2011

15 pages; International audience; n the present work, a novel signal denoising technique for piecewise constant or linear signals is presented termed as "signal split." The proposed method separates the sharp edges or transitions from the noise elements by splitting the signal into different parts. Unlike many noise removal techniques, the method works only in the nonorthogonal domain. The new method utilizes Stein unbiased risk estimate (SURE) to split the signal, Lipschitz exponents to identify noise elements, and a polynomial fitting approach for the sub signal reconstruction. At the final stage, merging of all parts yield in the fully denoised signal at a very low computational cost. St…

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer scienceStochastic resonanceNoise reduction[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology01 natural sciencesMultiplicative noisePiecewise linear function010104 statistics & probabilitySpeckle patternsymbols.namesakeSignal-to-noise ratioWavelet[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineering0101 mathematicsSignal transfer functionShrinkageSignal reconstructionNoise (signal processing)General EngineeringNonlinear opticsWavelet transform020206 networking & telecommunicationsTotal variation denoisingAtomic and Molecular Physics and OpticsAdditive white Gaussian noiseGaussian noisePiecewisesymbolsStep detectionAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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Signal Restoration via a Splitting Approach

2012

International audience; In the present study, a novel signal restoration method from noisy data samples is presented and is termed as "signal split (SSplit)" approach. The new method utilizes Stein unbiased risk estimate estimator to split the signal, the Lipschitz exponents to identify noise elements and a heuristic approach for the signal reconstruction. However, unlike many noise removal techniques, the present method works only in the non-orthogonal domain. Signal restoration was performed on each individual part by finding the best compromise between the data samples and the smoothing criteria. Statistical results are quite promising and suggest better performance than the conventional…

Mathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingsplit or segmentationthresholding02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingSignalmodulus maxima[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0202 electrical engineering electronic engineering information engineeringLipschitz exponentMathematicscontinuous wavelet transformSignal reconstructionHeuristicNoise (signal processing)Estimator020206 networking & telecommunicationsLipschitz continuityStein unbiased risk estimatewavelet transform modulus maxima020201 artificial intelligence & image processingAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSmoothingEnergy (signal processing)
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Representation and estimation of spectral reflectances using projection on PCA and wavelet bases

2008

In this article, we deal with the problem of spectral reflectance function representation and estimation in the context of multispectral imaging. Because the reconstruction of such functions is an inverse problem, slight variations in input data completely skew the expected results. Therefore, stabilizing the reconstruction process is necessary. To do this, we propose to use wavelets as basis functions, and we compare those with Fourier and PCA bases. We present the idea and compare these three methods, which belong to the class of linear models. The PCA method is training-set dependent and confirms its robustness when applied to reflectance estimation of the training sets. Fourier and wave…

Mathematical optimizationbusiness.industryGeneral Chemical EngineeringMultispectral imageHuman Factors and ErgonomicsBasis functionPattern recognitionGeneral ChemistryInverse problemsymbols.namesakeWaveletFourier transformRobustness (computer science)Principal component analysissymbolsFunction representationArtificial intelligencebusinessMathematicsColor Research & Application
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A fully adaptive multiresolution scheme for image processing

2007

A nonlinear multiresolution scheme within Harten's framework [A. Harten, Discrete multiresolution analysis and generalized wavelets, J. Appl. Numer. Math. 12 (1993) 153-192; A. Harten, Multiresolution representation of data II, SIAM J. Numer. Anal. 33 (3) (1996) 1205-1256] is presented. It is based on a centered piecewise polynomial interpolation fully adapted to discontinuities. Compression properties of the multiresolution scheme are studied on various numerical experiments on images.

Mathematics::Functional AnalysisPolynomialNumerical analysisMultiresolution analysisImage processingComputer Science ApplicationsPolynomial interpolationWaveletModelling and SimulationComputer Science::Computer Vision and Pattern RecognitionModeling and SimulationCompression (functional analysis)CalculusPiecewiseAlgorithmMathematicsMathematical and Computer Modelling
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Spatial Besov regularity for stochastic partial differential equations on Lipschitz domains

2010

We use the scale of Besov spaces B^\alpha_{\tau,\tau}(O), \alpha>0, 1/\tau=\alpha/d+1/p, p fixed, to study the spatial regularity of the solutions of linear parabolic stochastic partial differential equations on bounded Lipschitz domains O\subset R^d. The Besov smoothness determines the order of convergence that can be achieved by nonlinear approximation schemes. The proofs are based on a combination of weighted Sobolev estimates and characterizations of Besov spaces by wavelet expansions.

Mathematics::Functional AnalysisSmoothness (probability theory)General MathematicsProbability (math.PR)Mathematics::Analysis of PDEsScale (descriptive set theory)Numerical Analysis (math.NA)Lipschitz continuitySobolev spaceStochastic partial differential equation60H15 Secondary: 46E35 65C30WaveletRate of convergenceBounded functionFOS: MathematicsApplied mathematicsMathematics - Numerical AnalysisMathematics - ProbabilityMathematicsStudia Mathematica
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A Linear Cost Algorithm to Compute the Discrete Gabor Transform

2010

In this paper, we propose an alternative efficient method to calculate the Gabor coefficients of a signal given a synthesis window with a support of size much lesser than the length of the signal. The algorithm uses the canonical dual of the window (which does not need to be calculated beforehand) and achieves a computational cost that is linear with the signal length in both analysis and synthesis. This is done by exploiting the block structure of the matrices and using an ad hoc Cholesky decomposition of the Gabor frame matrix.

Matrix (mathematics)Signal ProcessingGabor waveletShort-time Fourier transformGabor transformElectrical and Electronic EngineeringAlgorithmSparse matrixMathematicsMatrix decompositionCholesky decompositionTime–frequency analysisIEEE Transactions on Signal Processing
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New method of grain-boundary extraction by directional optimal filtering: application to estimating creep in metals

2002

It is economically important for manufacturers of high- temperature machines to be able to measure creep so they can predict residual service life more accurately. This paper describes and refines an image analysis method for evaluating creep in laboratory test pieces. It is a preliminary study of how to extract relevant information for creep mea- surement by counting cavities. Sample preparation for quantification by image analysis is an important step determining the further development of the image analysis technique. Grain-boundary extraction, which in- volves directional information, is the major problem to be solved before measurement can be automated. The search for a crest-line extr…

Measure (data warehouse)business.industryComputer scienceGeneral EngineeringFilter (signal processing)Atomic and Molecular Physics and Opticssymbols.namesakeFourier transformWaveletCreepsymbolsGrain boundaryComputer visionArtificial intelligenceInstrumentation (computer programming)businessAlgorithmDigital filterLinear filterOptical Engineering
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A Watermarking of Medical Image : New Approach Based On "Multi-Layer" Method

2011

In order to contribute to security sharing and transmission of medical images, this paper propose a new approach for Watermarking image based on the techniques of Code Division Multiple Access (CDMA), Discrete Wavelet transform (DWT) and Error Correcting Code (ECC). The motivation of this approach is to improve the quantity of data integration with the conservation of the image visual quality. Therefore, this work permits to the user the capacity to correct the possible alterations if it exists. IRM and Echographic medical image are used to experiment this approach.

Medical image[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Error Correcting CodeCode Division Multiple Access[ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWatermarkingDiscrete Wavelet transformMedical image.
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Adaptive surface compression with geometric wavelets.

2008

The recent advances in computer graphics and digitization allow access to an ever finer three-dimensional modelling of the world. The critical challenges with 3D models lie in their transmission and rendering, which must fit the heterogeneity of the end resources (network bandwidth, display terminals . . . ). In this context, this thesis investigates the progressive compression and transmission of 3D models, based on multiresolution analysis, to provide a scalable representation of these geometric models. This work is part of "CoSurf", a collaborative research project involving LIRIS laboratory and France Télécom R&D in Rennes. The proposed hierarchical compression method is based on a wave…

Mesheslifting schemegeometric waveletssegmentationanalyse multirésolutionschéma liftingtransmission sélective.multiresolution analysis3-D mesh partitioning[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Maillages surfaciquescompression progressiveprogressive compressionview-dependent transmission.ondelettes géometriques
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Using Matlab's wavelet toolbox to compare electric signals outputted by microbial fuel cells

2019

Motivation: microbial fuel cells (MFC) represents a wastewater treatment technology with the potential for a relevant electric energy generation. The monitoring of the electric current outputted generates time series of data. It was generated two time series using an experimental setup with a low-cost dual chamber microbial fuel cell treating cassava wastewater and, also, it was used the electric current data from a previously described experiment with this same setup treating cheese whey. All of this, innovatively, according our best knowledge, was studied using power spectral density, multifractal and wavelet coherence analysis. Results are promising and indeed point out this approach as …

Microbial fuel cellComputer science02 engineering and technology01 natural sciencesWaveletElectrical and Electronic EngineeringProcess engineeringMATLABcomputer.programming_languagebusiness.industry010401 analytical chemistrySpectral density021001 nanoscience & nanotechnologyToolbox0104 chemical sciencesElectronic Optical and Magnetic MaterialsAnodeWastewaterlcsh:TA1-2040Signal ProcessingElectric currentlcsh:Engineering (General). Civil engineering (General)0210 nano-technologybusinesscomputerBiotechnologySensing and Bio-Sensing Research
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