Search results for " Wavelets"
showing 10 items of 15 documents
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 …
Optical flow estimation from multichannel spherical image decomposition
2011
International audience; The problem of optical flow estimation is largely discussed in computer vision domain for perspective images. It was also proven that, in terms of optical flow analysis from these images, we have difficulty distinguishing between some motion fields obtained with little camera motion. The omnidirectional cameras provided images with large filed of view. These images contain global information about motion and allow to remove the ambiguity present in perspective case. Nevertheless, these images contain significant radial distortions that is necessary to take into account when treating these images to estimate the motion. In this paper, we shall describe new way to comp…
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.
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…
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…
A Study on Patch-Based Progressive Coding Schemes of Semi-Regular 3D Meshes for Local Wavelet Compression and View-Dependent Transmission
2010
International audience; This paper firstly introduces a wavelet-based segmentation for three-dimensional (3D) Semi-Regular (SR) meshes, as a pre-processing step, in a region-independent progressive coding algorithm. The proposed segmentation process aims at producing homogeneous regions with respect to their frequency amplitudes on the mesh surface, in other words: patches with different degrees of roughness. We have then studied the behavior of the wavelets, obtained during the independent coding of each region, especially close to the patch boundaries. The main contribution of this paper consists in considering three different possible wavelet decompositions, close to the region borders, …
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…
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…
Volatility co-movements: a time scale decomposition analysis
2014
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, based on a factor decomposition of the covariance matrix of implied and realized volatilities, is carried for different sub-samples (identified as normal and crisis periods) and across different (high) frequency bands. In particular, the analysis is split in two stages. In the first stage, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and, in a second stage, we apply Maximum Likelihood for a factor de…
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…