We study the problem of learning to rank images for image retrieval. For a noisy set of images indexed or tagged by the same keyword, we learn a ranking model from some training e...
Learning-based superresolution (SR) are popular SR techniques that use application dependent priors to infer the missing details in low resolution images (LRIs). However, their pe...
In this paper, we overcome a major drawback of the level set framework: the lack of point correspondences. We maintain explicit backward correspondences from the evolving interfac...
An approach is presented for imposing generic hard constraints on deformable models at a low computational cost, while preserving the good convergence properties of snake-like mod...
In this paper we propose a new joint encryption and lossless compression technique designed for large images 1 . The proposed technique takes advantage of the Mojette transform pr...
Andrew Kingston, Simone Colosimo, Patrizio Campisi...