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Overall Objectives
Application Domains
New Software and Platforms
Bilateral Contracts and Grants with Industry
Bibliography
Overall Objectives
Application Domains
New Software and Platforms
Bilateral Contracts and Grants with Industry
Bibliography


Section: New Results

Image Reconstruction from Highly Corrupted Gradients

Participants : Hicham Badri, Hussein Yahia, Driss Aboutajdine.

Surface-from-Gradients (SfG) is an important step in many imaging applications. It consists in reconstructing an image/surface from corrupted gradient fields, which results in an ill-posed problem. We propose to use sparsity to regularize the problem. The first approach uses sparsity in the gradient field together with a robust norm on the data-fitting term and was presented at CVPR 2014. The new approach uses a non-local regularization that manipulates non-local similar patches of the corrupted gradient and forcing them to be low-rank. The two approaches significantly outperform previous optimization-based SfG methods on both synthetic and real data.

One submitted publication.