Depth and image recovery using a MRF model
This paper deals with the problem of depth recovery and image restoration from sparse and noisy image data. The image is modeled as a Markov random field and a new energy function is developed to effectively detect discontinuities in highly sparse and noisy images. The model provides an alternative...
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| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence 1994-11, Vol.16 (11), p.1117-1122 |
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| container_title | IEEE transactions on pattern analysis and machine intelligence |
| container_volume | 16 |
| creator | Kapoor, S. Mundkur, P.Y. Desai, U.B. |
| description | This paper deals with the problem of depth recovery and image restoration from sparse and noisy image data. The image is modeled as a Markov random field and a new energy function is developed to effectively detect discontinuities in highly sparse and noisy images. The model provides an alternative to the use of a line process. Interpolation over missing data sites is first done using local characteristics to obtain initial estimates and then simulated annealing is used to compute the maximum a posteriori (MAP) estimate. A threshold on energy reduction per iteration is used to speed up simulated annealing by avoiding computation that contributes little to the energy minimization. Moreover, a minor modification of the posterior energy function gives improved results for random as well as structured sparsing problems. Results of simulations carried out on real range and intensity images along with details of the simulations are presented.< > |
| doi_str_mv | 10.1109/34.334392 |
| format | Article |
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Results of simulations carried out on real range and intensity images along with details of the simulations are presented.< ></description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computational modeling</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Image converters</subject><subject>Image reconstruction</subject><subject>Image restoration</subject><subject>Interpolation</subject><subject>Lattices</subject><subject>Markov random fields</subject><subject>Pattern recognition. Digital image processing. 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| identifier | ISSN: 0162-8828 |
| ispartof | IEEE transactions on pattern analysis and machine intelligence, 1994-11, Vol.16 (11), p.1117-1122 |
| issn | 0162-8828 1939-3539 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_26324920 |
| source | IEEE Electronic Library (IEL) |
| subjects | Applied sciences Artificial intelligence Computational modeling Computer science control theory systems Exact sciences and technology Image converters Image reconstruction Image restoration Interpolation Lattices Markov random fields Pattern recognition. Digital image processing. Computational geometry Simulated annealing Stochastic processes Surface reconstruction |
| title | Depth and image recovery using a MRF model |
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