On Robust Corner-Preserving Smoothingin Image Processing; .

Removing a high amount of noise and preserving most structureare desirable properties of an image smoother. Unfortunately, theyseem to be contradictory: usually one can only improve one propertyat the cost of the other one. This thesis shows how this can be resolved:for a deeper understanding of the problem, consistency, robustness anddiscontinuity-preserving issues of M-kernel estimators in one-and two-dimensional regression are treated in detail. To identify edge- andcorner-preserving properties, a new theory based on differential geometryis developed. Finally, by combining M-smoothing and leastsquares-trimming, the TM-smoother is introduced unifying cornerpreservingproperties and outlier robustness.

Dettagli sul prodotto

• Autori: Martin Hillebrand
• Editore: VDM Verlag Dr. Müller
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 01.01.2008
• EAN: 9783639002652
• ISBN: 978-3-639-00265-2
• Pagine: 108
• Dimensioni: 150 mm x 6 mm x 220 mm
• Peso: 179 g
• Categoria: Scienze naturali, medicina, informatica, tecnica > Matematica