In this paper we propose novel algorithms for total variation (TV) based image restoration and parameter estimation utilizing variational distribution approximations. By following...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
In this paper we model the components of the compressive sensing (CS) problem using the Bayesian framework by utilizing a hierarchical form of the Laplace prior to model sparsity ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
This paper addresses the problem of reconstructing the density of a scene from multiple projection images produced by modalities such as x-ray, electron microscopy, etc. where an ...
Satya P. Mallick, Sameer Agarwal, David J. Kriegma...
In conventional tomography, the interior of an object is reconstructed from tomographic projections such as X-ray or electron microscope images. All the current reconstruction met...
This paper presents an approach to reconstruct nonstationary, articulated objects from silhouettes obtained with a monocular video sequence. We introduce the concept of motion blu...