activity
20152018
most citedOptimising Spatial and Tonal Data for PDE-based Inpainting

18 citations · 18 across the 4 of their papers we have counts for

collaborators

5 papers

math.AP2018

Theoretical Foundation of the Weighted Laplace Inpainting Problem

Laurent Hoeltgen, Andreas Kleefeld, Isaac Harris +1

Laplace interpolation is a popular approach in image inpainting using partial differential equations. The classic approach considers the Laplace equation with mixed boundary condit…

cs.CV2017

Optimisation of photometric stereo methods by non-convex variational minimisation

Georg Radow, Laurent Hoeltgen, Yvain Quéau +1

Estimating shape and appearance of a three dimensional object from a given set of images is a classic research topic that is still actively pursued. Among the various techniques av…

cs.CV2017

Clustering-Based Quantisation for PDE-Based Image Compression

Laurent Hoeltgen, Pascal Peter, Michael Breuß

Finding optimal data for inpainting is a key problem in the context of partial differential equation based image compression. The data that yields the most accurate reconstruction…

math.OC2016

Sparse l1 Regularisation of Matrix Valued Models for Acoustic Source Characterisation

Laurent Hoeltgen, Michael Breuß, Gert Herold +1

We present a strategy for the recovery of a sparse solution of a common problem in acoustic engineering, which is the reconstruction of sound source levels and locations applying m…

cs.CV201518 cited

Optimising Spatial and Tonal Data for PDE-based Inpainting

Laurent Hoeltgen, Markus Mainberger, Sebastian Hoffmann +6

Some recent methods for lossy signal and image compression store only a few selected pixels and fill in the missing structures by inpainting with a partial differential equation (P…