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Outlier robust corner-preserving methods for reconstructing noisy images

Збережено в:
Опубліковано в::arXiv.org (Aug 3, 2007), p. n/a
Автор: Hillebrand, Martin
Інші автори: Müller, Christine H
Опубліковано:
Cornell University Library, arXiv.org
Предмети:
Data analysis
Image reconstruction
Properties (attributes)
Differential geometry
Image processing
Robustness
Preservation
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Короткий огляд: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.
ISSN:2331-8422
DOI:10.1214/009053606000001109
Джерело:Engineering Database