Kernel based image registration versus MLESAC: A comparative study

This paper evaluates the performance of a nonparametric robust image registration method based on the mean shift algorithm, which could successfully replace the random sampling algorithms. Therefore it realizes a comparative study between the proposed nonparametric method and other two important rob...

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Bibliographische Detailangaben
Hauptverfasser:	Fuiorea, D., Gui, V., Pescaru, D., Toma, C.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Cost function Image registration Image sampling Iterative algorithms Kernel Maximum likelihood estimation Noise robustness Parameter estimation Probability density function Solid modeling
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Beschreibung
Zusammenfassung:	This paper evaluates the performance of a nonparametric robust image registration method based on the mean shift algorithm, which could successfully replace the random sampling algorithms. Therefore it realizes a comparative study between the proposed nonparametric method and other two important robust random sampling methods, RANSAC and MLESAC. These techniques are analyzed and tested for performance evaluation in several image registration scenarios.
DOI:	10.1109/SACI.2009.5136252