What question did this study set out to answer?

To calculate exact maximum a posteriori (MAP) estimates for degraded binary scenes using network flow algorithms and assess the accuracy of simulated annealing.

January 1, 1989Journal of the Royal Statistical Society Series B (Statistical Methodology)

Exact Maximum A Posteriori Estimation for Binary Images

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To calculate exact maximum a posteriori (MAP) estimates for degraded binary scenes using network flow algorithms and assess the accuracy of simulated annealing.
Mapped degraded two-color images into capacitated networks to compute exact MAP estimates via efficient variants of the Ford–Fulkerson maximum flow algorithm.
Tested image reconstruction across practical temperature cooling schedules using simulated annealing to evaluate convergence quality against exact solutions.
Network flow formulation enabled exact evaluation of MAP estimates for two-color images.
Simulated annealing with practicable temperature schedules produced poor approximations relative to the exact MAP configuration.
The network flow approach did not generalize in any obvious manner to multicolour scenes.

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Implication

Computational study demonstrates exact maximum a posteriori estimation in binary images via max-flow algorithms, revealing that simulated annealing often yields poor approximations.

Cite This Study

Greig et al. (1989) studied this question.

synapsesocial.com/papers/6a0efefd1c5e2d2319fa35ad https://doi.org/10.1111/j.2517-6161.1989.tb01764.x

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Implication

Computational study demonstrates exact maximum a posteriori estimation in binary images via max-flow algorithms, revealing that simulated annealing often yields poor approximations.

Exact Maximum A Posteriori Estimation for Binary Images

Key Points

Discussion

Implication

Cite This Study

Exact Maximum A Posteriori Estimation for Binary Images

Key Points

Discussion

Implication

Cite This Study

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