@INPROCEEDINGS{0995Krutz2006,
	AUTHOR = {Andreas Krutz and Michael Frater and Matthias Kunter and Thomas Sikora},
	TITLE = {Windowed Image Registration for Robust Mosaicing of Scenes with Large Background Occlusions},
	BOOKTITLE = {IEEE Int. Conf. on Image Processing (ICIP\'06)},
	YEAR = {2006},
	MONTH = oct,
	ADDRESS = {Atlanta, GA, USA},
	NOTE = {M. Frater: University of New South Wales, Canberra, Australia},
	PDF = {http://elvera.nue.tu-berlin.de/files/0995Krutz2006.pdf},
	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.}
}