Maximally Localized Radial Profiles for Tight Steerable Wavelet Frames

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On the 2D Post-Processing of Brillouin Optical Time-Domain Analysis

Luc Thévenaz, Zhisheng Yang, Simon Adrien Zaslawski

The benefits and limitations inherent to the 2D post-processing of measurements from Brillouin optical time-domain analyzers are investigated from a fundamental point of view. In a preliminary step, the impact of curve fitting on the precision of the estim ...

IEEE Institute of Electrical and Electronics Engineers2020

The n-term Approximation of Periodic Generalized Levy Processes

Michaël Unser, Julien René Fageot, John Paul Ward

In this paper, we study the compressibility of random processes and fields, called generalized Levy processes, that are solutions of stochastic differential equations driven by d-dimensional periodic Levy white noises. Our results are based on the estimati ...

2020

Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration

Jan Skaloud, Stéphane Guerrier, Mehran Khaghani

The task of inertial sensor calibration has required the development of various techniques to take into account the sources of measurement error coming from such devices. The calibration of the stochastic errors of these sensors has been the focus of incre ...

2020

Wavelet variance scale-dependence as a dynamics discriminating tool in high-frequency urban wind speed time series

Dasaraden Mauree, Fabian Guignard

High frequency wind time series measured at different heights from the ground (from 1.5 to 25.5 meters) in an urban area were investigated by using the variance of the coefficients of their wavelet transform. Two ranges of scales were identified, sensitive ...

2019

Learning-Based Image Compression using Convolutional Autoencoder and Wavelet Decomposition

Touradj Ebrahimi, Pinar Akyazi

In this paper, a learning-based image compression method that employs wavelet decomposition as a preprocessing step is presented. The proposed convolutional autoencoder is trained end-to-end to yield a target bitrate smaller than 0.15 bits per pixel across ...

2019

A comparative study on wavelets and residuals in deep super resolution

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou, Fayez Lahoud

Despite the advances in single-image super resolution using deep convolutional networks, the main problem remains unsolved: recovering fine texture details. Recent works in super resolution aim at modifying the training of neural networks to enable the rec ...

2019

Characteristics of a bridge condition assessment method based on state representation methodology (SRM) and damage detection sensitivity

Eugen Brühwiler

The State Representation Methodology (SRM) combined with the Frequency Slice Wavelet Transform (FSWT), which is a new time-frequency analysis tool, is proposed for assessing the condition of bridges on the basis of bridge monitoring data. First, this paper ...

Springer2019

Sparse Lens Inversion Technique (SLIT): lens and source separability from linear inversion of the source reconstruction problem

Frédéric Courbin, Rémy Elie Joseph

Strong gravitational lensing offers a wealth of astrophysical information on the background source it affects, provided the lensed source can be reconstructed as if it was seen in the absence of lensing. In the present work, we illustrate how sparse optimi ...

EDP SCIENCES S A2019

On the Shiftability of Dual-Tree Complex Wavelet Transforms

Michaël Unser, Kunal Narayan Chaudhury

The dual-tree complex wavelet transform (DT-ℂWT) is known to exhibit better shift-invariance than the conventional discrete wavelet transform. We propose an amplitude-phase representation of the DT-ℂWT which, among other things, offers a direct explanation ...

IEEE2010

Image compression using an edge adapted redundant dictionary and wavelets

Pierre Vandergheynst, Lorenzo Granai, Lorenzo Peotta

Low bit rate image coding is an important problem regarding applications such as storage on low memory devices or streaming data on the internet. The state of the art in image compression is to use 2-D wavelets. The advantages of wavelet bases lie in their ...

2006