Name
Title | ||
|---|---|---|
Data-Driven Learning of a Union of Sparsifying Transforms Model for Blind Compressed Sensing |
Abstract | ||
|---|---|---|
Compressed sensing is a powerful tool in applications such as magnetic resonance imaging (MRI). It enables accurate recovery of images from highly undersampled measurements by exploiting the sparsity of the images or image patches in a transform domain or dictionary. In this work, we focus on blind compressed sensing (BCS), where the underlying sparse signal model is a priori unknown, and propose ... |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TCI.2016.2567299 | IEEE Transactions on Computational Imaging |
Keywords | Field | DocType |
Transforms,Compressed sensing,Image reconstruction,Magnetic resonance imaging,Dictionaries,Convergence | Iterative reconstruction,Convergence (routing),Computer vision,Mathematical optimization,Data-driven learning,Medical imaging,A priori and a posteriori,Artificial intelligence,Inverse problem,Coordinate descent,Mathematics,Compressed sensing | Journal |
Volume | Issue | ISSN |
2 | 3 | 2573-0436 |
Citations | PageRank | References |
15 | 0.68 | 34 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saiprasad Ravishankar | 1 | 587 | 36.58 |
| Yoram Bresler | 2 | 1104 | 119.17 |