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Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction
Abstract
Piecewise continuous reconstruction of real-valued data can be formulated in terms of nonconvex optimization problems. Both stochastic and deterministic algorithms have been devised to solve them. The simplest such reconstruction process is the weak string. Exact solutions can be obtained for it and are used to determine the success or failure of the algorithms under precisely controlled conditions. It is concluded that the deterministic algorithm (graduated nonconvexity) outstrips stochastic (simulated annealing) algorithms both in computational efficiency and in problem-solving power.>
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Cited by
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Boykov, Y., Veksler, O., & Zabih, R. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.969114 · Cited by 6,988
Phase Unwrapping via Graph Cuts
Bioucas-Dias, J. M., & Valadao, G. (2007) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.888351 · Cited by 572
Robust Multiresolution Estimation of Parametric Motion Models
Odobez, J. M., & Bouthemy, P. (1995) · Journal of Visual Communication and Image Representation · doi:10.1006/jvci.1995.1029 · Cited by 537
Regularization of Wavelet Approximations
Antoniadis, A., & Fan, J. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753208942 · Cited by 498
Fast approximate energy minimization via graph cuts
Boykov, Y., Veksler, O., & Zabih, R. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.791245 · Cited by 470
Metadata
- Authors
- Blake, A.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 1989
- Volume
- 11
- Issue
- 1
- Pages
- 2-12
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2063494315
- Cited by
- 178
- References
- 0
- FWCI
- 16.92
- Type
- journal article
- Language
- en
- Open access
- closed
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- Blake, A. (1989). Comparison of the efficiency of deterministic and stochastic algorithms for visual reconstruction. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/34.23109
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