Search results for "wavelet."

Multi-scale analysis of shell growth increments using wavelet transform

1999

Abstract Shell increments contain information related to the evolution of the environment in which the organism grew during its biomineralization. To extract the information from variations in shell topography, a new and promising technique is presented, involving multi-scale analysis of the shell topography using a B-spline wavelet transform. An accurate non-contact optical system, based on laser triangulation, is used to map the shell surface. The resulting range image is treated as a grey-level image by using a multi-resolution approach based on the generalization of the cascade algorithm. This method allows reconstruction of non-subsampled images that correspond to the projection onto t…

Generalized wavelets design using Kernel methods. Application to signal processing

2013

Abstract Multiresolution representations of data are powerful tools in signal processing. In Harten’s framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called the prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact values and the predicted values. In this paper we present a multiresolution scheme using local polynomial regression theory in order to design a more accurate prediction operator. The stability of the scheme is proved and the order of the method is calculated. Finally, some results are presented comparing our method with the classical…

A Smart Sensing Method for Real- Time Monitoring of Low Voltage Series-Arc-Fault

2020

This paper proposes a smart sensing method for real-time monitoring of low voltage series arc fault. It is based on the wavelet coefficient mean-difference algorithm and the four spikes appearing within two fundamental periods criterion with adaptive threshold. The method also uses the hard thresholding wavelet denoising with the universal threshold. An arc fault factor and a load adaptation factor are introduced and combined with a correction factor, so allowing the selection of the adaptive threshold in real-time and the series arc fault detection.

A Comparative Study and an Evaluation Framework of Multi/Hyperspectral Image Compression

2009

In this paper, we investigate different approaches for multi/hyperspectral image compression. In particular, we compare the classic multi-2D compression approach and two different implementations of 3D approach (full 3D and hybrid) with regards to variations in spatial and spectral dimensions. All approaches are combined with a weighted Principal Component Analysis (PCA) decorrelation stage to optimize performance. For consistent evaluation, we propose a larger comparison framework than the conventionally used PSNR, including eight metrics divided into three families. The results show the weaknesses and strengths of each approach.

Segmentation and feature extraction in capillaroscopic videos

2015

This contribution describes a method to select regions of interest as capillaries of the oral mucosa and to extract their main features useful for real diagnosis purposes. A discrete version of the wavelet transform has been adopted for segmenting the images coming from video sequences acquired by a prototype capillaroscopic, able to put in evidence the red blood flow. A set of proper characteristics is automatically computed for a correct evaluation of the peripheral microcirculation.

A combined CWT-DWT method using model-based design simulator for partial discharges online detection

2009

The suppression of noises is fundamental in onsite Partial Discharge (PD) measurements. For this purpose, the wavelet transform analysis method has been developed and it is a powerful tool for processing the transient and suddenly changing signals. As the wavelet transform possesses the properties of multi-scale analysis and time-frequency domain localization, it is also particularly suitable to process the suddenly changing signals of the partial discharge pulse (PD). In this paper, an improved Wavelet denoising method developed by a model-based design software is presented. Simulations are provided as well as some results obtained during laboratory experiment and on-line PD measurements. …

UN METODO COMBINATO CWT-DWT PER IL RICONOSCIMENTO DI SEGNALI DI SCARICHE PARZIALI

2010

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…

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 …

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…