@conference {
	title = {On Morphological Openings and Closings of Signals in Shaped Noise},
	author = {Sidiropoulos, N D., Baras, John S., Berenstein, Carlos A.},
	year = {1995},
	month = {10/1995},
	abstract = {In recent work, we have shown that morphological Openings and closingS can be viewed as consistent MAP estimators of morphologically Smooth binary image signals immersed in i.i.d. union (clutter) noise, or suffering from i.i.d. random dropouts. We revisit this viewpoint under a different set of assumptions, which allows the explicit incorporation of geometric and morphological constraints into the noise model, i.e., the noise may now exhibit geometric Structure; surprisingly, it turns out that this affects neither the optimality nor the consistency of these filters.},
	address = {Washington DC},
	booktitle = {The IEEE 1995 International Conference on Image Processing},
	pages = {pp. 518-521}
}
@conference {
	title = {New Results on Optimality and Consistency of Morphological Openings and Closings},
	author = {Sidiropoulos, N D., Baras, John S., Berenstein, Carlos A.},
	year = {1995},
	month = {07/1995},
	abstract = {It has been recently shown that morphological openings and closings can be viewed as consistent MAP estimators of morphologically smooth signals in i.i.d. noise. We revisit this viewpoint under a different set of assumptions, which allows the explicit incorporation of geometric and morphological constraints into the noise model, i.e., the noise may now exhibit geometric structure; surprisingly, it turns out that this affects neither the optimality nor the consistency of these filters.},
	address = {San Diego, CA},
	booktitle = {The Morphological Image Processing and Random Image Modeling},
	pages = {pp. 118-122}
}
@conference {
	title = {The Combinatorial Basis of Uniformly Bounded Discrete Random Set Theory},
	author = {Sidiropoulos, N D., Baras, John S., Berenstein, Carlos A.},
	year = {1995},
	month = {03/1995},
	abstract = {We provide a purely combinatorial view of the essential structure of uniformly bounded DRS theory without any reference to discrete probability and highlight the two fundamental functionals arising out of this exposition. The key tool is Moebius inversion. We conclude that the study of uniformly bounded DRS theory is the study of Incidence functions on Boolean algebras of finite rank. Some useful results arise as a by-product of this investigation.},
	address = {Baltimore, MD},
	booktitle = {The 29th Annual Conference on Information Sciences and Systems},
	pages = {pp. 463-467},
	organization = {Johns Hopkins University}
}
