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An O(n 2 Log N) Multilevel Backprojection Method
| Content Provider | Semantic Scholar |
|---|---|
| Author | Brandt, Achi Mann, Jordan Brodski, Matvei |
| Copyright Year | 2008 |
| Abstract | A number of imaging technologies reconstruct an image function from its Radon projection using the convolution backprojection method. The convolution is an O(N 2 log N) algorithm, where the image consists of N N pixels, while the backpro-jection is an O(N 3) algorithm, thus constituting the major computational burden of the convolution backprojection method. An O(N 2 logN) multilevel backprojection method is presented here. When implemented with a Fourier-domain postprocessing technique, also presented here, the resulting image quality is similar to or superior than the image quality of the classical backprojection technique. 1 Background Reconstruction of a function of two or three variables from its Radon transform has proven vital in computed tomography (CT), nuclear magnetic resonance imaging, astronomy, geophysics, and a number of other eldss3]. One of the best known reconstruction algorithms is the convolution backprojection method (CB), which is widely used in commercial CT devicess3] (with rebinning for divergent-beam projectionss6]). Recently, it has been applied to spotlight-mode synthetic aperture radar image reconstructionn4], in which the conventional method is the direct Fourier method (DF), i.e., Fourier-domain interpolation followed by 2-D FFTT9]. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.wisdom.weizmann.ac.il/~achi/gmc-6.ps |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
