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Inference on binary images from binary data

Published online by Cambridge University Press:  01 July 2016

C. A. Glasbey*
Affiliation:
University of Edinburgh
*
Postal address: Biomathematics and Statistics Scotland, The University of Edinburgh, James Clerk Maxwell Building, King's Buildings, Edinburgh, EH9 3JZ, UK.

Abstract

The problem addressed is to reverse the degradation which occurs when images are digitised: they are blurred, subjected to noise and rounding error, and sampled only at a lattice of points. Inference is considered for the fundamental case of binary scenes, binary data and isotropic blur. The inferential process is separable into two stages: first from the lattice points to a binary image in continuous space and then the reversal of thresholding and blur. Methods are motivated by, and illustrated using, an electron micrograph of an immunogold-labelled section of tulip virus.

Type
Stochastic Geometry and Statistical Applications
Copyright
Copyright © Applied Probability Trust 1996 

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