Name
Title | ||
|---|---|---|
Image representation by blob and its application in CT reconstruction from few projections |
Abstract | ||
|---|---|---|
The localized radial symmetric function, or blob, is an ideal alternative to the pixel basis for X-ray computed tomography (CT) image reconstruction. In this paper we develop image representation models using blob, and propose reconstruction methods for few projections data. The image is represented in a shift invariant space generated by a Gaussian blob or a multiscale blob system of different frequency selectivity, and the reconstruction is done through minimizing the Total Variation or the 1 norm of blob coefficients. Some 2D numerical results are presented, where we use GPU platform for accelerating the X-ray projection and back-projection, the interpolation and the gradient computations. |
Year | Venue | Keywords |
|---|---|---|
2011 | arXiv: Numerical Analysis | total variation,image reconstruction,numerical analysis,symmetric function |
Field | DocType | Volume |
Iterative reconstruction,Computer vision,Mathematical optimization,Corner detection,Interpolation,Gaussian,Blob detection,Artificial intelligence,Invariant (mathematics),Pixel,Numerical analysis,Mathematics | Journal | abs/1107.5087 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Han Wang | 1 | 46 | 10.87 |
| Laurent Desbat | 2 | 33 | 6.39 |
| Samuel Legoupil | 3 | 9 | 2.02 |