Article ID: | iaor19971047 |
Country: | United Kingdom |
Volume: | 28 |
Issue: | 3 |
Start Page Number: | 627 |
End Page Number: | 640 |
Publication Date: | Sep 1996 |
Journal: | Advances in Applied Probability |
Authors: | Glasbey C.A. |
Keywords: | artificial intelligence |
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.