@inproceedings{d011d6a4712f470c88f9c4db67e1c9cf,
title = "Bayesian region merging probability for parametric image models",
abstract = "We describe a novel Bayesian approach to region merging, which directly uses statistical image models to determine the probability that the union of two regions is homogeneous, and does not require parameter estimation. This approach is particularly beneficial for cases in which the merging decision is most likely to be incorrect: when little information is contained in one or both of the regions and parameter estimates are unreliable. We apply the formulation to the implicit polynomial surface model for range data and texture models for intensity images.",
author = "Lavalle, {Steven M} and Hutchinson, {Seth Andrew}",
year = "1993",
language = "English (US)",
isbn = "0818638826",
series = "IEEE Computer Vision and Pattern Recognition",
publisher = "Publ by IEEE",
pages = "778--779",
editor = "Anon",
booktitle = "IEEE Computer Vision and Pattern Recognition",
note = "Proceedings of the 1993 IEEE Computer Society Conference on Computer Vision and Pattern Recognition ; Conference date: 15-06-1993 Through 18-06-1993",
}