Pulse-stream models in time-of-flight imaging

Adrien Besson, Dimitris Perdios, Marcel Arditi, Yves Wiaux and Jean-Philippe Thiran. submitted to IEEE ICASSP 2018

Introduction

This repository contains all the code to reproduce the results of the paper: Pulse-stream models in time-of-flight imaging.

Abstract:

This paper considers the problem of reconstructing raw signals from random projections in the context of time-of-flight imaging with an array of sensors. It presents a new signal model, coined as multichannel pulse-stream model, which exploits pulse-stream models and accounts for additional structure induced by inter-sensor dependencies. We propose a sampling theorem and a reconstruction algorithm, based on l1-minimization, for signals belonging to such a model. We show the benefits of the proposed approach by means of numerical simulations and on a real non-destructive-evaluation application.

Citation (BibTex):

If you are using this code, please cite the following paper: A. G. J. Besson, D. Perdios, Y. Wiaux and J.-P. Thiran. PULSE-STREAM MODELS IN TIME-OF-FLIGHT IMAGING submitted to 2018 IEEE International Conference on Acoustics, Speech and Signal Processing.

System Requirements:

This software has been tested on Linux 64-bit system (Ubuntu 16-04, Mint distribution) and on Windows 10 system.

Prerequisites

1. MATLAB (Tested on R2017a)

Running the code:

1. Download and unzip ICASSP2018-pulse-streams-master.zip
2. Open MATLAB and navigate in the folder ICASSP2018-pulse-streams-master
3. If you want to reproduce the Figures of the paper, run the script 'Script_reproduce_figure_ICASSP.m'
4. If you want to regenerate:
   • The results of the noiseless experiments (used to generate Figure 2), run the script 'Script_reproduce_noiseless_experiment.m'
   • The results of the noisy experiments (used to generate Figure 3), run the script 'Script_reproduce_noisy_experiment.m'
   • The results of the noisy experiment (used to generate Figure 4), run the script 'Script_reproduce_invivo_experiment.m'
5. If you are interested in testing the least-square solution of the problem, explained in Section 2.4.1 of the paper, for the noiseless experiment, you can run the script 'Script_least_squares_noiseless_experiment.m'

Contact:

Adrien Besson, ([email protected])