@inproceedings {491,
	title = {Multiscale Methods for the Segmentation of Images},
	booktitle = {ICASSP {\textquoteright}96},
	year = {1996},
	abstract = {<p>This work presents a method for segmenting images based on gradients in the intensity function. Past approaches have centered on formulating the problem in the context of variational calculus as the minimization of a functional involving the image intensity and edge functions. Computational methods for finding the minima of such variational problems are prone to two shortfalls: they are often computationally intensive and almost always incapable of computing error statistics associated with the segmentation. Using a particular variational formulation as a starting point, this paper presents a derivation of an associated statistical formulation using multiscale models. The result is an algorithm which is fast and capable of computing error statistics</p>
},
	keywords = {error statistics, functional, functional equations, gradients, image segmentation, images, intensity function, minimisation, minimization, multiscale models, Segmentation, statistical formulation, variational calculus, variational techniques},
	doi = {http://dx.doi.org/10.1109/ICASSP.1996.545869},
	author = {M Schneider and P Fieguth and W C. Karl and A S. Willsky}
}
