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Mauro Dalla Mura

7 accepted papers

2024

Spectro-Spatial Hyperspectral Image Reconstruction From Interferometric Acquisitions

ICASSP 2024accepted

In the last decade, novel hyperspectral cameras have been developed with particularly desirable characteristics of compactness and short acquisition time, retaining their potential to obtain spectral/spatial resolution competitive with respect to traditional cameras. However, a computational effort…

Cited by 0SourceScholar
2023

Leveraging Neural Koopman Operators to Learn Continuous Representations of Dynamical Systems from Scarce Data

ICASSP 2023accepted

Over the last few years, several works have proposed deep learning architectures to learn dynamical systems from observation data with no or little knowledge of the underlying physics. A line of work relies on learning representations where the dynamics of the underlying phenomenon can be described…

Cited by 0SourceScholar
2023

Model-Based Spectral Reconstruction Of Interferometric Acquisitions

ICASSP 2023accepted

Spectral information of the scene can be reconstructed from processing observations acquired by interferometric devices. In the case of devices that have multiple wave interference (e.g., Fabry-Pérot etalons), a simple inversion such as inverse Fourier transform (e.g., for Michelson-like interferome…

Cited by 0SourceScholar
2020

Characterisation of a Snapshot Fourier Transform Imaging Spectrometer Based on an Array of Fabry-Perot Interferometers

ICASSP 2020accepted

This study focuses on a novel snapshot Fourier Transform imaging spectrometer based on an array of Fabry-Perot interferometers. This device fully relies on signal processing in order to provide intelligible outputs and thus requires a precise characterisation. In this paper, we present a strategy fo…

Cited by 0SourceScholar
2020

Learning Endmember Dynamics in Multitemporal Hyperspectral Data Using A State-Space Model Formulation

ICASSP 2020accepted

Hyperspectral image unmixing is an inverse problem aiming at recovering the spectral signatures of pure materials of interest (called endmembers) and estimating their proportions (called abundances) in every pixel of the image. However, in spite of a tremendous applicative potential and the avent of…

Cited by 7SourceScholar
2020

Tree of Shapes Cut for Material Segmentation Guided by a Design

ICASSP 2020accepted

In manufacturing, the monitoring of the fabrication process is crucial in order to be sure that objects are compliant. For nano-objects, most of this monitoring is done manually. In this paper, we propose a method to segment different materials in a manufactured object. The method uses design inform…

Cited by 0SourceScholar
2017

A comparison between real and complex Schott spherical symmetry test for PolSAR data analysis

ICASSP 2017accepted

Most of the tests proposed in the literature to verify if a given random multivariate dataset fits a spherical or elliptical distribution are designed for real valued data and rely on the estimation of high order moment matrices. Recently, a test that considers complex random vectors, derived based…

Cited by 0SourceScholar