Geometric registration of images with arbitrarily-shaped local intensity variations from shadows

Authors:
M. M. Fouad;R. M. Dansereau;A. D. Whitehead
Affiliations:
Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada;Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada;Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

In this paper, we focus on the sub-pixel geometric registration of images with arbitrarily-shaped local intensity variations, particularly due to shadows. Intensity variations tend to degrade the performance of geometric registration, thereby degrading subsequent processing. To handle intensity variations, we propose a model with illumination correction that can handle arbitrarily-shaped regions of local intensity variations. The approach is set in an iterative coarse-to-fine framework with steps to estimate the geometric registration with illumination correction and steps to refine the arbitrarily-shaped local intensity regions. The results show that this model outperforms linear scalar model by a factor of 6.8 in sub-pixel registration accuracy.