Publication

The Pairing of a Wavelet Basis With a Mildly Redundant Analysis via Subband Regression

Publications associées (26)

Benchmarking of single imaging datasets

Aleksandra Radenovic, Adrien Charles-François Raymond Descloux

A method of estimating a value (311-313) indicative of a signal component of an input imaging dataset (190) includes determining a normalized Fourier-domain representation of the input imaging dataset (190); and for each one of multiple low-pass filters (3 ...

2020

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

Fabian Guignard, Dasaraden Mauree

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

A comparative study on wavelets and residuals in deep super resolution

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

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

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

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

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

Eugen Brühwiler, Ayaho Miyamoto

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