Abstract
Smoothness is a generic assumption underlying a wide range of physical phenomena. It characterizes the coherence and homogeneity of matter within a scope of space (or an interval of time). It is one of the most common assumptions in computer vision models, in particular, those formulated in terms of Markov random fields (MRFs) (Geman and Geman 1984; Elliott et al. 1984; Marroquin 1985) and regularization (Poggio et al. 1985). Its applications are seen widely in image restoration, surface reconstruction, optical flow and motion, shape from X, texture, edge detection, region segmentation, visual integration and so on.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer Japan
About this chapter
Cite this chapter
Li, S.Z. (2001). Discontinuities in MRFs. In: Markov Random Field Modeling in Image Analysis. Computer Science Workbench. Springer, Tokyo. https://doi.org/10.1007/978-4-431-67044-5_4
Download citation
DOI: https://doi.org/10.1007/978-4-431-67044-5_4
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-70309-9
Online ISBN: 978-4-431-67044-5
eBook Packages: Springer Book Archive