Category Archives: Projets2018

Global stereo matching formulations rely on piecewise constant disparity priors. For satellite images this is adequate for near-nadir views, where discontinuities are naturally associated to vertical walls. However, for slanted views this yields an asymmetry in the handling of occlusions … Continue reading →

The objective of this project is to analyze and implement the method proposed in [1]. The proposed multi-view stereo method performs local fusion of disparity maps obtained with semi-global matching for reconstructing large scenes composed of hundreds of images. Careful … Continue reading →

The optical stereo pipeline described in the course is a simplified version of the S2P pipeline [1], which was developed for high resolution pushbroom satellites such as Pleiades or WorldView. One of the particularities of these satellites is that the … Continue reading →

The SkySat video products provide hundreds of projective camera frames of a single target. The goal of this project is to compute a 3D model by fusing independent reconstructions obtained from several image pairs. A method for selecting stereo pairs … Continue reading →

L’objectif de ce projet est de développer un algorithme d’estimation du relief 3D à partir d’une vidéo haute résolution en utilisant la méthode des images de plans épipolaires, introduite par Bolles en 1987 [1] et récemment raffinée par Kim et.al … Continue reading →

Context The process of acquiring interferometric hyperspectral images from airborne or satellite sensors [1,2] comprises several steps, including : Rectification of the image sequence to a common epipolar geometry to build an epipolar plane image (EPI) sequence. Decomposition of each … Continue reading →

Contexte : Le développement récent de l’imagerie Radar à Synthèse d’Ouverture (RSO) et la couverture régulière de la Terre par de tels capteurs ouvre de nouvelles perspectives pour l’observation de la Terre. Cependant ces images, obtenues en éclairage cohérent, présentent … Continue reading →

Context In lectures 3 and 7 we explain how to model radar image noise and how to adapt non-local patch based denoising approaches (that assume additive gaussian noise) to radar images, where the noise has different characteristics. More recently, some … Continue reading →

Encadrants : Florence Tupin, Jean-Marie Nicolas Email : florence.tupin@telecom-paristech.fr Contexte : Les images radar ont l’avantage de pouvoir être acquises par tout temps (de jour comme de nuit et quelles que soient les conditions météorologiques). Elles présentent néanmoins un fort … Continue reading →