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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lai, S.H. Vemuri, B.C. |
| Copyright Year | 1994 |
| Description | Author affiliation: Dept. of Electr. Eng., Florida Univ., Gainesville, FL, USA (Lai, S.H.) |
| Abstract | In this paper, we present a novel iterative numerical solution to the Poisson equation whose solution is needed in a variety of low-level vision problems. Our algorithm is an O(N) (N being the number of discretization points) iterative technique and does not make any assumptions on the shape of the input domain unlike the polyhedral domain assumption in the proof of convergence of multigrid techniques. We present two major results namely, a generalized version of the capacitance matrix theorem and a theorem on O(N) convergence of the alternating direction implicit method (ADI) used in our algorithm. Using this generalized theorem, we express the linear system corresponding to the discretized Poisson equation as a Lyapunov and a capacitance matrix equation. The former is solved using the ADI method while the solution to the later is obtained using a modified bi-conjugate gradient algorithm. We demonstrate the algorithm performance on synthesized data for the surface reconstruction and the SFS problems.<> |
| Starting Page | 9 |
| Ending Page | 14 |
| File Size | 692577 |
| Page Count | 6 |
| File Format | |
| ISBN | 0818658258 |
| ISSN | 10636919 |
| DOI | 10.1109/CVPR.1994.323804 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1994-06-21 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Machine vision Iterative methods Image reconstruction |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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