Joint image registration and reconstruction from compressed multi-view measurements

Gilles Puy, Pierre Vandergheynst
Spie-Int Soc Optical Engineering, 2013
Article de conférence

We present a method for joint reconstruction of a set of images representing a given scene from few multi-view measurements obtained by compressed sensing. We model the correlation between measurements using global geometric transformations represented by few parameters. Then, we propose an algorithm able to jointly estimate these transformation parameters and the observed images from the available measurements. This method is also robust to occlusions appearing in the scene. The reconstruction algorithm minimizes a non-convex functional and generates a sequence of estimates converging to a critical point of this functional. Finally, we demonstrate the efficiency of the proposed method using numerical simulations.

À propos de ce résultat

Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Concepts associés

Chargement

Publications associées

Chargement

Gilles Puy, Pierre Vandergheynst
Spie-Int Soc Optical Engineering, 2013
Article de conférence

Résumé

Official source

https://infoscience.epfl.ch/record/188611?ln=fr

À propos de ce résultat

Concepts associés (10)

Concepts associés

Chargement

Publications associées (11)

Publications associées

Chargement

Algorithme

thumb|Algorithme de découpe d'un polygone quelconque en triangles (triangulation). Un algorithme est une suite finie et non ambiguë d'instructions et d’opérations permettant de résoudre une classe de

Mesure physique

La mesure physique est l'action de déterminer la ou les valeurs d'une grandeur (longueur, capacité), par comparaison avec une grandeur constante de même espèce prise comme terme de référence (étalon

Simulation informatique

vignette|upright=1|Une simulation informatique, sur une étendue de , de l'évolution du typhon Mawar produite par le Modèle météorologique Weather Research and Forecasting La simulation informatique

Joint image registration and reconstruction from compressed multi-view measurements

Gilles Puy, Pierre Vandergheynst

We present a method for joint reconstruction of a set of images representing a given scene from few multi-view measurements obtained by compressed sensing. We model the correlation between measurements using global geometric transformations represented by few parameters. Then, we propose an algorithm able to jointly estimate these transformation parameters and the observed images from the available measurements. This method is also robust to occlusions appearing in the scene. The reconstruction algorithm minimizes a non-convex functional and generates a. sequence of estimates converging to a critical point of this functional. Finally, we demonstrate the efficiency of the proposed method using numerical simulations.

Spie-Int Soc Optical Engineering2013

Chargement

Robust image reconstruction from multi-view measurements

Gilles Puy, Pierre Vandergheynst

We propose a novel method to accurately reconstruct a set of images representing a single scene from few linear multi-view measurements. Each observed image is modeled as the sum of a background image and a foreground one. The background image is common to all observed images but undergoes geometric transformations, as the scene is observed from different viewpoints. In this paper, we assume that these geometric transformations are represented by a few parameters, e.g., translations, rotations, affine transformations, etc.. The foreground images differ from one observed image to another, and are used to model possible occlusions of the scene. The proposed reconstruction algorithm estimates jointly the images and the transformation parameters from the available multi-view measurements. The ideal solution of this multi-view imaging problem minimizes a non-convex functional, and the reconstruction technique is an alternating descent method built to minimize this functional. The convergence of the proposed algorithm is studied, and conditions under which the sequence of estimated images and parameters converges to a critical point of the non-convex functional are provided. Finally, the efficiency of the algorithm is demonstrated using numerical simulations for applications such as compressed sensing or super-resolution. Code available at http://lts2www.epfl.ch/people/gilles/softwares.

2014

Chargement

Joint reconstruction of misaligned images from incomplete measurements for cardiac MRI

Gabriele Vincenzo Bonanno, Gilles Puy, Pierre Vandergheynst

We present a novel method for robust reconstruction of the image of a moving object from incomplete linear measurements. We assume that only few measurements of this object can be acquired at different instants and model the correlation between measurements using global geometric transformations represented by few parameters. Then, we design a method that is able to jointly estimate these transformation parameters and an image of the object, while taking into account possible occlusions of parts of the object during the acquisitions. The reconstruction algorithm minimizes a non-convex functional and generates a sequence of estimates converging to a critical point of this functional. Finally, we show how to apply this algorithm on a real cardiac acquisition for free breathing coronary magnetic resonance imaging.

2013

Chargement