Refereed full papers (journals, book chapters, international conferences)

2003

@article{WiL2003,
	vgclass =	{refpap},
	author =	{Wilson, R. and Chang-Tsun Li},
	title =	{A class of discrete multiresolution random fields and its
	application to image segmentation},
	journal =	{IEEE Transactions on Pattern Analysis and Machine Intelligence},
	volume =	{25},
	number =	{1},
	pages =	{42-56},
	year =	{2003},
	url =	{http://dx.doi.org/10.1109/TPAMI.2003.1159945},
	abstract =	{In this paper, a class of Random Field model, defined on a
	multiresolution array is used in the segmentation of gray level and
	textured images. The novel feature of one form of the model is that it
	is able to segment images containing unknown numbers of regions, where
	there may be significant variation of properties within each region.
	The estimation algorithms used are stochastic, but because of the
	multiresolution representation, are fast computationally, requiring
	only a few iterations per pixel to converge to accurate results, with
	error rates of 1-2 percent across a range of image structures and
	textures. The addition of a simple boundary process gives accurate
	results even at low resolutions, and consequently at very low
	computational cost.},
}