An extension of geman and reynolds' approach to constrained restoration and the recovery of discontinuities

Merrilee Hurn; Christopher Jennison

doi:10.1109/34.506418

An extension of geman and reynolds' approach to constrained restoration and the recovery of discontinuities

Merrilee Hurn, Christopher Jennison

Department of Mathematical Sciences

Research output: Contribution to journal › Article › peer-review

13 Citations (SciVal)

Abstract

Geman and Reynolds [7] present an approach to linear image restoration which provides for recovery of horizontal and vertical gray-level discontinuities from blurred and noisy observations. We extend their model and parameter selection method to include diagonal discontinuities. A hazard of this modeling approach is identified and addressed. We also comment on the truncated Gibbs sampler suggested in the paper [7].

Original language	English
Pages (from-to)	657-662
Number of pages	6
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	18
Issue number	6
DOIs	https://doi.org/10.1109/34.506418
Publication status	Published - 1996

Keywords

Discontinuity recovery
Gibbs sampler
Metropolis algorithm
Parameter selection
Simulated annealing
Statistical image reconstruction

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Artificial Intelligence
Applied Mathematics

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10.1109/34.506418

Cite this

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abstract = "Geman and Reynolds [7] present an approach to linear image restoration which provides for recovery of horizontal and vertical gray-level discontinuities from blurred and noisy observations. We extend their model and parameter selection method to include diagonal discontinuities. A hazard of this modeling approach is identified and addressed. We also comment on the truncated Gibbs sampler suggested in the paper [7].",

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AB - Geman and Reynolds [7] present an approach to linear image restoration which provides for recovery of horizontal and vertical gray-level discontinuities from blurred and noisy observations. We extend their model and parameter selection method to include diagonal discontinuities. A hazard of this modeling approach is identified and addressed. We also comment on the truncated Gibbs sampler suggested in the paper [7].

KW - Discontinuity recovery

KW - Gibbs sampler

KW - Metropolis algorithm

KW - Parameter selection

KW - Simulated annealing

KW - Statistical image reconstruction

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An extension of geman and reynolds' approach to constrained restoration and the recovery of discontinuities

Abstract

Keywords

ASJC Scopus subject areas

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