Abstract
A class of image processing problems is considered from the standpoint of treating them as those of co-ordinating the local image-dependent information and a priori smoothness constraints. Such a generalized problem is set as the formal problem of minimization of a separable objective function defined on an appropriate pixel neighborhood graph. For attaining a higher computation speed, the full pixel lattice is replaced by a succession of partial identical neighborhood trees. Two versions of a high-speed minimization procedure are proposed for, respectively, discretely defined and quadratic objective functions.
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© 1998 Springer-Verlag Wien
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Mottl, V.V., Blinov, A.B., Kopylov, A.V., Kostin, A.A. (1998). Optimization Techniques on Pixel Neighborhood Graphs for Image Processing. In: Jolion, JM., Kropatsch, W.G. (eds) Graph Based Representations in Pattern Recognition. Computing Supplement, vol 12. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6487-7_14
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DOI: https://doi.org/10.1007/978-3-7091-6487-7_14
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83121-2
Online ISBN: 978-3-7091-6487-7
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