Search results for " Wavelets"

showing 10 items of 15 documents

Cartoon filter via adaptive abstraction

2016

We propose a non-parametric methodology to realize abstraction images.The redundant wavelet "a trous" algorithm is applied for details detection.An multi-scale circular median filter is used as a smoothing filter.The proposed algorithm is simple and fast on low-cost entry-level hardware. Abstraction in computer graphics defines a procedure that discriminates the essential information that is worth keeping. Usually details, that correspond to higher frequency components, allow to distinguish otherwise similar images. Vice versa, low frequencies are related to the main information, which are larger structures. Contours themselves may also be identified by high frequencies and separate each pi…

Cartoon filterRedundant wavelet02 engineering and technologyEdge-preserving smoothingRedundant waveletsMultiresolution abstractionComputer graphicsCircular median filterWaveletFast multi-scale median0202 electrical engineering electronic engineering information engineeringMedian filterMedia TechnologyComputer visionElectrical and Electronic EngineeringMathematicsAbstraction (linguistics)1707Settore INF/01 - Informaticabusiness.industryEdge preserving smoothingWavelet transform[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringFilter (video)Mathematical morphologyEuclidean distance transformSignal Processing020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligencebusinessAlgorithmSmoothing
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Optimal extension of multispectral image demosaicking algorithms for setting up a one-shot camera video acquisition system

2022

Multispectral images are acquired using multispectral cameras equipped with CCD or CMOS sensors which sample the visible or near infrared spectrum according to specific spectral bands. A mosaic of multispectral MSFA filters is superimposed on the surface of the sensors to acquire a raw image called an MSFA image. In the MSFA image, only one spectral band is available per pixel, the demosaicking process is necessary to estimate the multispectral image at full spatio-spectral resolution. Motivated by the success of single-sensor cameras capturing the image in a single exposure that use CFA filters, we performed a comparative study of a few recent color image demosaicking algorithms and experi…

Demosaicking algorithmAdaptive Kernel regressionInterpolation bilinéaire pondéréeMultispectral imagesnoyau adaptatif de régressionBiorthogonal waveletsMultispectral filter arrayRéseau de filtres multispectrauxImages multispectralesConvolutionComposante de luminance[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]LMMSEWeighted bilinear interpolationAlgorithme de démosaïquageLuminance componentOndelettes biorthogonales
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Volatility co-movements: a time-scale decomposition analysis

2015

In this paper, we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers collapse. The analysis is based on a factor decomposition of the covariance matrix, in the time and frequency domain, using wavelets. The analysis aims to disentangle two components of volatility contagion (anticipated and unanticipated by the market). Once we focus on standardized factor loadings, the results show no evidence of contagion (from the US) in market expectations (coming from implied volatility) and evidence of unanticipated contagion (coming from the volatility risk premium) for almost any European country. Finally, the estim…

Economics and EconometricsVariance swapStochastic volatilityFinancial economicsSettore SECS-P/05 - Econometriaheteroskedasticity biasImplied volatilityVolatility risk premiumwaveletsrealized volatilityvolatility risk premiumcontagionVolatility swapImplied volatility Realized volatility Volatility risk premium Contagion Heteroskedasticity bias WaveletsVolatility smileForward volatilityEconometricsEconomicsimplied volatility; realized volatility; volatility risk premium; contagion; heteroskedasticity bias; wavelets.Volatility (finance)Financeimplied volatility
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Testing for Contagion: a Time-Scale Decomposition

2010

The aim of the paper is to test for financial contagion by estimating a simultaneous equation model subject to structural breaks. For this purpose, we use the Maximum Overlapping Discrete Wavelet Transform, MODWT, to decompose four asset returns into different scale components (each associated with a given frequency range). The decomposition will enable us to obtain the moment conditions necessary to (over)identify a structural form model with a single dummy and the one with multiple dummies capturing shifts in the co-movement of asset returns occurring during periods of financial turmoil. A Montecarlo simulation exercise shows that test based on a single dummy structural form model has goo…

Identification Wavelets Financial Contagion .Settore SECS-P/05 - Econometria
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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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Correlation of oscillatory behaviour in Matlab using wavelets

2014

Here we present a novel computational signal processing approach for comparing two signals of equal length and sampling rate, suitable for application across widely varying areas within the geosciences. By performing a continuous wavelet transform (CWT) followed by Spearman?s rank correlation coefficient analysis, a graphical depiction of links between periodicities present in the two signals is generated via two or three dimensional images. In comparison with alternate approaches, e.g., wavelet coherence, this technique is simpler to implement and provides far clearer visual identification of the inter-series relationships. In particular, we report on a Matlab? code which executes this tec…

PeriodicityWavelet coherenceWaveletsMachine learningcomputer.software_genreSpearman's rank correlationCorrelationWaveletDe-noisingCode (cryptography)Computers in Earth SciencesMATLABContinuous wavelet transformRank correlationMathematicscomputer.programming_languageContinuous wavelet transformSignal processingbusiness.industryContinuous wavelet transform; De-noising; Oscillation; Periodicity; Spearman's rank correlation; WaveletsOscillationArtificial intelligencebusinessAlgorithmcomputerInformation SystemsComputers and Geosciences
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Inner functions and local shape of orthonormal wavelets

2011

Abstract Conditions characterizing all orthonormal wavelets of L 2 ( R ) are given in terms of suitable orthonormal bases (ONBs) related with the translation and dilation operators. A particular choice of the ONBs, the so-called Haar bases, leads to new methods for constructing orthonormal wavelets from certain families of Hardy functions. Inner functions and the corresponding backward shift invariant subspaces articulate the structure of these families. The new algorithms focus on the local shape of the wavelet.

Pure mathematicsHardy spacesApplied MathematicsMathematical analysisWavelet transformHardy spaceLinear subspacesymbols.namesakeGeneralized Fourier seriesWaveletOrthonormal waveletssymbolsOrthonormal basisInvariant (mathematics)OrthonormalityInner functionsMathematicsApplied and Computational Harmonic Analysis
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Testing for public debt sustainability using a time-scale decomposition analysis

2013

In this paper we estimate the response of primary surplus to lagged debt to test for debt sustainability within the 17 EMU countries by using a factor model. The analysis is split into two stages. In the first stage we retrieve the cyclical and long-run components of primary surplus and debt ratios of each EMU country using a wavelet decomposition for each fiscal covariate, based on the Maximal Overlapping Discrete Wavelet Transform. In the second stage, we use Full Information Maximum Likelihood for a factor decomposition of thecross covariance matrix of the wavelet coefficients of primary deficit and debt to GDP ratios in order to measure the short run and the long run reaction of the pri…

Settore SECS-P/05 - EconometriaDebt sustainability Wavelets FIML
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Wavelet analysis of financial contagion

2011

The aim is to estimate a factor model fitted to financial returns to disentagle the role played by common shock and idiosincratic shocks in shaping the comovement between asset returns during periods of calm and financial turbulence. For this purpose, we use wavelet analysis and, in particular, the Maximum Overlapping Discrete Wavelet Transform, to decompose the covariance matrix of the asset returns on a scale by scale basis, where each scale is associated to a given frequency range. This decomposition will give enough moment conditions to identify the role played by common and idiosincratic shocks. A Montecarlo simulation experiment shows that our testing methodology has good size and power …

Settore SECS-P/05 - EconometriaIdentification Wavelets Financial Contagion
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Testing for contagion: a time-scale decomposition

2011

The aim of the paper is to test for financial contagion by estimating a simultaneous equation model subject to structural breaks. For this purpose, we use the Maximum Overlapping Discrete Wavelet Transform, MODWT, to decompose four asset returns into different scale components (each associated with a given frequency range). The decomposition will enable us to obtain the moment conditions necessary to (over)identify a structural form model with a single dummy and the one with multiple dummies capturing shifts in the co-movement of asset returns occurring during periods of financial turmoil. A Montecarlo simulation exercise shows that test based on a single dummy structural form model has goo…

Settore SECS-P/05 - EconometriaIdentification Wavelets Financial Contagion
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