DocumentCode :
353911
Title :
Robust multisensor image registration with partial distance merits
Author :
Yang, Xiangjie ; Sheng, Yunlong ; Sevigny, L. ; Valin, Pierre
Author_Institution :
Image Sci. Group, Laval Univ., Que., Canada
Volume :
1
fYear :
2000
fDate :
10-13 July 2000
Abstract :
Challenge in the registration of battlefield images in visible and far-infrared bands is the feature inconsistency. We use a contour-based approach and propose robust free-form curve-matching algorithms using the adaptive hill climbing and the iterative closest point algorithm. Both algorithms do not require explicit curve feature correspondence, are designed to be robust against outliers. The originality of this work is the use of the mean partial distance as the objective function in the iterative closest point algorithm, so that outliers can be easily handled by using rank order statistics. A fast algorithm using the segment representation of Voronoi diagram for the nearest point transform and the distance transform is used.
Keywords :
curve fitting; image registration; sensor fusion; Voronoi diagram; adaptive hill climbing; battlefield images; closest point algorithm; contour-based; curve-matching; feature inconsistency; image registration; iterative closest point algorithm; mean partial distance; partial distance merits; segment representation; Cameras; Image registration; Image sensors; Iterative algorithms; Iterative closest point algorithm; Layout; Magneto electrical resistivity imaging technique; Optical imaging; Optical sensors; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location :
Paris, France
Print_ISBN :
2-7257-0000-0
Type :
conf
DOI :
10.1109/IFIC.2000.862645
Filename :
862645
Link To Document :
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