| 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.