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Abstract

The ability to remove a large amount of noise and the ability to preserve most structure are desirable properties of an image smoother. Unfortunately, they usually seem to be at odds with each other; one can only improve one property at the cost of the other. By combining M-smoothing and least-squares-trimming, the TM-smoother is introduced as a means to unify corner-preserving properties and outlier robustness. To identify edge- and corner-preserving properties, a new theory based on differential geometry is developed. Further, robustness concepts are transferred to image processing. In two examples, the TM-smoother outperforms other corner-preserving smoothers. A software package containing both the TM- and the M-smoother can be downloaded from the Internet.

Details

1009240
Title
Outlier robust corner-preserving methods for reconstructing noisy images
Publication title
arXiv.org; Ithaca
Publication year
2007
Publication date
Aug 3, 2007
Section
Mathematics; Statistics
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2009-09-29
Milestone dates
2007-08-03 (Submission v1)
Publication history
 
 
   First posting date
29 Sep 2009
ProQuest document ID
2088010612
Document URL
https://www.proquest.com/working-papers/outlier-robust-corner-preserving-methods/docview/2088010612/se-2?accountid=208611
Full text outside of ProQuest
Copyright
Notwithstanding the ProQuest Terms and conditions, you may use this content in accordance with the associated terms available at http://arxiv.org/abs/0708.0481.
Last updated
2019-04-17
Database
ProQuest One Academic