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Windowed Image Registration for Robust Mosaicing of Scenes with Large Background Occlusions
Citation key 0995Krutz2006
Author Andreas Krutz and Michael Frater and Matthias Kunter and Thomas Sikora
Title of Book IEEE Int. Conf. on Image Processing (ICIP\'06)
Year 2006
Address Atlanta, GA, USA
Month oct
Note M. Frater: University of New South Wales, Canberra, Australia
Abstract We propose an enhanced window-based approach to local image registration for robust video mosaicing in scenes with arbitrarily moving foreground objects. Unlike other approaches, we estimate accurately the image transformation without any pre-segmentation even if large background regions are occluded. We apply a windowed hierarchical frame-to-frame registration based on image pyramid decomposition. In the lowest resolution level phase correlation for initial parameter estimation is used while in the next levels robust Newton-based energy minimization of the compensated image mean-squared error is conducted. To overcome the degradation error caused by spatial image interpolation due to the warping process, i.e. aliasing effects from under-sampling, final pixel values are assigned in an up-sampled image domain using a Daubechies bi-orthogonal synthesis filter. Experimental results show the excellent performance of the method compared to recently published methods. The image registration is sufficiently accurate to allow open-loop parameter accumulation for long-term motion estimation.
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