Journal article
Outlier robust corner-preserving methods for reconstructing noisy images



Publication Details
Authors:
Hillebrand, M.; Müller, C.
Publication year:
2007
Journal:
Annals of Statistics
Pages range:
132-165
Volume number:
35
ISSN:
0090-5364

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 comer-preserving smoothers. A software package containing both the TM- and the M-smoother can be downloaded from the Internet.


Authors/Editors

Last updated on 2019-01-11 at 16:06